阅读说明：本技术 车辆监测器 (Vehicle monitor ) 是由 博阿兹·米兹拉希 亚龙·阿德勒 斯坦尼斯拉夫·沙皮拉 伊加尔·马图基 阿维夫·罗森伯格 于 2018-09-07 设计创作，主要内容包括：一种车辆监测器和用于监测车辆的方法。(A vehicle monitor and method for monitoring a vehicle.)

1. A method for estimating a height of a road segment, the method comprising:

measuring, by a barometer of the vehicle and during a given travel period, an internal vehicle pressure to provide a plurality of barometer measurements; wherein the measuring occurs as the vehicle traverses the road segment;

compensating, by the computer, the barometer for affecting the vehicle condition to provide a plurality of compensated barometer measurements; and

merging the plurality of compensated barometer measurements with barometer information obtained during a plurality of other travel periods performed by a plurality of vehicles, thereby providing an altitude estimate for the road segment; wherein the combining comprises performing slot-constant offset compensation and inter-slot offset compensation.

2. The method of claim 1, wherein the merging comprises searching for overlapping nodes, wherein each overlapping node corresponds to a same location and belongs to multiple time periods.

3. The method of claim 2, wherein the combining comprises a combining procedure for substantially equalizing altitude estimates for different time periods associated with the same overlapping node.

4. A method according to claim 3, comprising varying the height estimate for non-overlapping nodes based on changes in height estimates of overlapping nodes introduced during the bonding process.

5. The method of claim 4, wherein varying the altitude estimates for the non-overlapping nodes comprises distributing altitude adjustments along a time period according to a predefined altitude adjustment distribution.

6. The method of claim 5, wherein the predefined height adjustment profile is a uniformly distributed height adjustment profile.

7. The method of claim 3, wherein the time period constant offset compensation comprises reducing a height difference between overlapping nodes without joining the overlapping nodes.

8. The method of claim 3, wherein the time period offset compensation comprises the combining process.

9. The method of claim 1, wherein compensating for the barometer to affect the vehicle condition is based on information provided by the barometer and by at least one other vehicle sensor different from the barometer.

10. The method of claim 9, wherein the at least one other vehicle sensor is an accelerometer.

11. The method of claim 1, wherein the merging comprises computing statistics of altitude estimates associated with overlapping nodes; and excluding one or more altitude estimates based on the statistics.

12. The method of claim 1, comprising transmitting the plurality of compensated barometer measurements to a computerized system located outside the vehicle, and wherein the merging is performed by the computerized system.

13. The method of claim 1, wherein at least a portion of the merging is performed by a computer of the vehicle.

14. The method of claim 1, wherein compensating for the barometer affecting vehicle conditions comprises low pass filtering the barometer measurements.

15. The method of claim 1, wherein compensating for the barometer affecting vehicle conditions comprises determining to ignore at least some of the barometer measurements.

16. The method of claim 1, wherein compensating for the barometer affecting vehicle conditions comprises determining to ignore at least some of the barometer measurements.

17. The method of claim 1, wherein compensating for the barometer-affected vehicle condition comprises determining to ignore at least some of the barometer measurements when a slope of a portion of a road extending between two points as reflected by the barometer measurements associated with the two points exceeds a maximum slope threshold.

18. The method of claim 1, wherein compensating for the barometer affected vehicle condition comprises calculating an effect of a barometer affected event on a value of at least one barometer measurement.

19. The method of claim 1, wherein compensating for the barometer effect the vehicle is responsive to acceleration of the vehicle when the barometer measurements are taken.

20. The method of claim 1, wherein compensating for the barometer effect the vehicle is responsive to deceleration of the vehicle when the barometer measurements are taken.

21. A non-transitory computer program product for estimating an altitude for a road segment, the non-transitory computer program product storing instructions for:

measuring, by a barometer of the vehicle and during a given travel period, an internal vehicle pressure to provide a plurality of barometer measurements; wherein the measuring occurs as the vehicle traverses the road segment;

compensating, by the computer, the barometer for affecting the vehicle condition to provide a plurality of compensated barometer measurements; and

merging the plurality of compensated barometer measurements with barometer information obtained during a plurality of other travel periods performed by a plurality of vehicles, thereby providing an altitude estimate for the road segment; wherein the combining comprises performing slot-constant offset compensation and inter-slot offset compensation.

22. The non-transitory computer program product of claim 21, wherein the merging comprises searching for overlapping nodes, wherein each overlapping node corresponds to a same location and belongs to multiple time periods.

23. The non-transitory computer program product of claim 22, wherein the merging comprises a merging process for substantially equalizing altitude estimates for different time periods related to the same overlapping node.

24. The non-transitory computer program product of claim 23 storing instructions for changing a height estimate of a non-overlapping node based on changes in the height estimate of an overlapping node introduced during the bonding process.

25. The non-transitory computer program product of claim 24, wherein changing the altitude estimate of the non-overlapping node comprises distributing altitude adjustments along a time period according to a predefined altitude adjustment distribution.

26. The non-transitory computer program product of claim 25, wherein the predefined height adjustment distribution is a uniformly distributed height adjustment distribution.

27. The non-transitory computer program product of claim 26, wherein the time period constant offset compensation comprises reducing a height difference between overlapping nodes without joining the overlapping nodes.

28. The non-transitory computer program product of claim 26, wherein the inter-period offset compensation comprises the combining process.

29. The non-transitory computer program product of claim 21, wherein compensating for the barometer to affect a vehicle condition is based on information provided by the barometer and by at least one other vehicle sensor different from the barometer.

30. The non-transitory computer program product of claim 29, wherein the at least one other vehicle sensor is an accelerometer.

31. The non-transitory computer program product of claim 21, wherein compensating for the barometer from affecting the vehicle condition is based on a barometer measurement pattern.

32. The non-transitory computer program product of claim 21, wherein the merging comprises computing statistics of altitude estimates associated with overlapping nodes; and excluding one or more altitude estimates based on the statistics.

33. The non-transitory computer program product of claim 21, storing instructions for transmitting the plurality of compensated barometer measurements to a computerized system located outside the vehicle, and wherein the merging is performed by the computerized system.

34. The non-transitory computer program product of claim 21, wherein at least a portion of the compensating for the merging is performed by a computer of the vehicle.

35. The non-transitory computer program product of claim 21, wherein compensating for the barometer affecting vehicle conditions comprises low pass filtering the barometer measurements.

36. The non-transitory computer program product of claim 21, wherein compensating for the barometer affecting vehicle conditions comprises determining to ignore at least some of the barometer measurements.

37. The non-transitory computer program product of claim 21, wherein compensating for the barometer affecting vehicle conditions comprises determining to ignore at least some of the barometer measurements.

38. The non-transitory computer program product of claim 21, wherein compensating for the barometer-affected vehicle condition comprises determining to ignore at least some of the barometer measurements when a slope of a portion of a road extending between two points as reflected by barometer measurements related to the two points exceeds a maximum slope threshold.

39. The non-transitory computer program product of claim 21, wherein compensating for the barometer affecting vehicle condition comprises calculating an effect of a barometer affecting event on a value of at least one barometer measurement.

40. The non-transitory computer program product of claim 21, wherein compensating for the barometer effect the vehicle is responsive to acceleration of the vehicle when the barometer measurements are taken.

41. The non-transitory computer program product of claim 21, wherein compensating for the barometer effect the vehicle is responsive to deceleration of the vehicle when the barometer measurements are taken.

42. A method for measuring physical events associated with a plurality of road segments, the method comprising: measuring a first set of parameters by a first vehicle sensor; wherein the measuring occurs while the vehicle is traveling on the plurality of road segments; wherein the first set of parameters includes a wheel motion parameter and a vehicle acceleration parameter; wherein the first vehicle sensor is different from a road image sensor; detecting, by a vehicle computer, a detected physical event related to travel over the plurality of road segments, wherein the detecting is based on the first set of parameters; generating physical event information regarding the detected physical event; and storing or transmitting at least a portion of the physical event information.

43. The method of claim 42, wherein the detected physical event is selected from the group consisting of: collision, slip, sideslip, spin, latitude spin, and longitude spin.

44. The method of claim 42, wherein the detected physical event comprises a collision, a slip, a sideslip, a rotation, a latitude rotation, and a longitude rotation.

45. The method of claim 42, wherein the first vehicle sensor comprises an accelerometer and a plurality of wheel motion sensors.

46. The method of claim 42, comprising calculating a road segment attribute.

47. The method of claim 46, wherein the road segment attributes comprise at least one of: (i) a curvature of a set of road segments including the road segment; (ii) a longitudinal slope of the road segment, (iii) a lateral slope of the road segment, (iv) a level of grip associated with the road segment, and (v) a degree of undulation of the road segment.

48. The method according to claim 46, wherein the road segment attributes include at least three road segment attributes of: (i) a curvature of a set of road segments including the road segment; (ii) a longitudinal slope of the road segment, (iii) a lateral slope of the road segment, (iv) a level of grip associated with the road segment, and (v) a degree of undulation of the road segment.

49. The method of claim 42, comprising calculating a location of the physical event.

50. The method of claim 42, comprising calculating the location of the physical event based on locations of different vehicle components associated with the physical event at points in time corresponding to measurements of the first set of parameters.

51. The method of claim 42, comprising: calculating a difference between (a) a reference map of the plurality of road segments and (b) the physical event information, the reference map including reference information on previously detected physical events related to the plurality of road segments; and wherein at least some of the differences are transmitted.

52. The method of claim 42, comprising receiving or calculating a reference map for the plurality of road segments, the reference map comprising (a) reference information about previously detected physical events related to the plurality of road segments, and (b) reference road segment attributes related to the plurality of road segments.

53. The method of claim 52, comprising determining the location of the vehicle based on the reference map and the sequence of detected physical events.

54. The method of claim 52, comprising determining the location of the vehicle by searching within the reference map for a reference sequence of physical events that coincides with the detected sequence of physical events.

55. The method of claim 52, comprising determining the location of the vehicle by searching within the reference map for a reference sequence of mandatory physical events that coincides with a sequence of mandatory detected physical events.

56. The method of claim 52, wherein the reference map comprises a base layer that stores information about locations of the plurality of road segments and spatial relationships between the plurality of road segments.

57. The method of claim 56, wherein the reference map comprises a layer storing the reference information regarding the previously detected physical events related to the plurality of road segments.

58. The method of claim 57, comprising determining the location of the vehicle by searching within the layer for a reference sequence of physical events that coincides with the detected sequence of physical events.

59. The method of claim 58, wherein the searching comprises scanning a road segment represented by the base layer and retrieving reference information about previously detected physical events related to the scanned road segment.

60. The method of claim 59, wherein the retrieving comprises applying a hash function to find the reference information about previously detected physical events.

61. The method of claim 52, wherein the reference map comprises: (a) a base layer storing information on positions of the plurality of road segments and spatial relationships between the plurality of road segments; and (b) one or more sparse layers comprising additional information about only some of the plurality of road segments; wherein the one or more sparse layers are linked to the base layer.

62. The method of claim 61, comprising generating travel instructions based on the one or more sparse layers and the location of the vehicle.

63. The method of claim 52, wherein the reference map includes a fixed-field-size sparse layer and a variable-size sparse layer; wherein the variable-size sparse layer includes the reference physical event information.

64. The method of claim 52, comprising receiving a reference map update for updating a portion of the reference map, and updating the portion of the reference map without updating an un-updated portion of the reference map.

65. The method of claim 52, wherein the reference map includes a private field storing information about a mode of travel associated with the vehicle or with a driver of the vehicle, and includes a public field.

66. The method of claim 42, further comprising generating virtual sensor information based at least on the first set of parameters.

67. The method of claim 42, further comprising determining a lateral position of the vehicle by using an image sensor.

68. The method of claim 42, wherein the physical event information comprises a normalized amplitude of the detected physical event.

69. A non-transitory computer program product for measuring physical events related to a plurality of road segments, wherein the non-transitory computer program product stores instructions for: measuring a first set of parameters by a first vehicle sensor; wherein the measuring occurs while the vehicle is traveling on the plurality of road segments; wherein the first set of parameters includes a wheel motion parameter and a vehicle acceleration parameter; wherein the first vehicle sensor is different from a road image sensor; detecting, by a vehicle computer, a detected physical event related to travel over the plurality of road segments, wherein the detecting is based on the first set of parameters; generating physical event information regarding the detected physical event; and storing or transmitting at least a portion of the physical event information.

70. The non-transitory computer program product of claim 69, wherein the detected physical event is selected from the group consisting of: collision, slip, sideslip, spin, latitude spin, and longitude spin.

71. The non-transitory computer program product of claim 69, wherein the detected physical event comprises a collision, a slip, a sideslip, a rotation, a latitude rotation, and a longitude rotation.

72. The non-transitory computer program product of claim 69, wherein the first vehicle sensor comprises an accelerometer and a plurality of wheel motion sensors.

73. The non-transitory computer program product of claim 69, the stored instructions to calculate a road segment attribute.

74. The non-transitory computer program product of claim 73, wherein the road segment attributes comprise at least one road segment attribute of: (i) a curvature of a set of road segments including the road segment; (ii) a longitudinal slope of the road segment, (iii) a lateral slope of the road segment, (iv) a level of grip associated with the road segment, and (v) a degree of undulation of the road segment.

75. The non-transitory computer program product of claim 73, wherein the road segment attributes include at least three road segment attributes from among: (i) a curvature of a set of road segments including the road segment; (ii) a longitudinal slope of the road segment, (iii) a lateral slope of the road segment, (iv) a level of grip associated with the road segment, and (v) a degree of undulation of the road segment.

76. The non-transitory computer program product of claim 69, the stored instructions to calculate a location of the physical event.

77. The non-transitory computer program product of claim 69, storing instructions for calculating a location of the physical event based on locations of different vehicle components associated with the physical event at points in time corresponding to measurements of the first set of parameters.

78. The non-transitory computer program product of claim 69, storing instructions for: calculating a difference between (a) a reference map of the plurality of road segments and (b) the physical event information, the reference map including reference information on previously detected physical events related to the plurality of road segments; and wherein at least some of the differences are transmitted.

79. The non-transitory computer program product of claim 69, storing instructions for receiving or calculating a reference map for the plurality of segments, the reference map comprising (a) reference information regarding previously detected physical events related to the plurality of segments, and (b) reference segment attributes related to the plurality of segments.

80. The non-transitory computer program product of claim 79 storing instructions for determining a location of the vehicle based on the reference map and a sequence of detected physical events.

81. The non-transitory computer program product of claim 79 storing instructions for determining a location of the vehicle by searching within the reference map for a reference sequence of physical events that coincide with a sequence of detected physical events.

82. The non-transitory computer program product of claim 79 storing instructions for determining a location of the vehicle by searching within the reference map for a reference sequence of mandatory physical events that coincide with a sequence of mandatory detected physical events.

83. The non-transitory computer program product of claim 79, wherein the reference map comprises a base layer that stores information about locations of the plurality of road segments and spatial relationships between the plurality of road segments.

84. The non-transitory computer program product of claim 83, wherein the reference map includes a layer storing the reference information regarding the previously detected physical events related to the plurality of road segments.

85. The non-transitory computer program product of claim 84 storing instructions for determining a location of the vehicle by searching within the layer for a reference sequence of physical events that coincides with a sequence of detected physical events.

86. The non-transitory computer program product of claim 85, wherein the searching comprises scanning a road segment represented by the base layer and retrieving reference information about previously detected physical events related to the scanned road segment.

87. The non-transitory computer program product of claim 85, wherein the retrieving comprises applying a hash function to find the reference information about previously detected physical events.

88. The non-transitory computer program product of claim 79, wherein the reference map comprises (a) a base layer storing information about locations of and spatial relationships between the plurality of road segments, and (b) one or more sparse layers comprising additional information about only some of the plurality of road segments; wherein the one or more sparse layers are linked to the base layer.

89. The non-transitory computer program product of claim 88, storing instructions for generating travel instructions based on the one or more sparse layers and a location of the vehicle.

90. The non-transitory computer program product of claim 79, wherein the reference map comprises a fixed-field-size sparse layer and a variable-size sparse layer; wherein the variable-size sparse layer includes the reference physical event information.

91. The non-transitory computer program product of claim 79, storing instructions for receiving a reference map update for updating a portion of the reference map and updating the portion of the reference map without updating an un-updated portion of the reference map.

92. The non-transitory computer program product of claim 79, wherein the reference map includes a private field storing information about a mode of travel associated with the vehicle or with a driver of the vehicle, and includes a public field.

93. The non-transitory computer program product of claim 69 storing instructions for generating virtual sensor information based at least on the first set of parameters.

94. The non-transitory computer program product of claim 69 storing instructions for determining a lateral position of the vehicle using an image sensor.

95. The non-transitory computer program product of claim 69, wherein the physical event information includes a normalized amplitude of the detected physical event.

96. A system for measuring physical events associated with a plurality of road segments, the system comprising: a vehicle computer configured to: (i) receiving a first set of parameters from a first vehicle sensor; wherein the measuring occurs while the vehicle is traveling on the plurality of road segments; wherein the first set of parameters includes a wheel motion parameter and a vehicle acceleration parameter; wherein the first vehicle sensor is different from a road image sensor; (ii) detecting a detected physical event related to travel over the plurality of road segments, wherein the detecting is based on the first set of parameters; generating physical event information regarding the detected physical event; and storing or facilitating transmission of at least a portion of the physical event information.

97. A method for generating a reference map of an area, the method comprising: receiving, from a plurality of vehicles through a communication interface, (a) physical event information about detected physical events detected by the plurality of vehicles while traveling on road segments belonging to the area, and (b) road segment attributes calculated by the plurality of vehicles, the road segment attributes relating to road segments belonging to the area; wherein the physical event information of a vehicle of the plurality of vehicles is based on a first set of parameters sensed by a first vehicle sensor of the vehicle; wherein the first set of parameters includes a wheel motion parameter and a vehicle acceleration parameter; wherein the first vehicle sensor is different from a road image sensor; and calculating, by a computerized system, the reference map based on the physical event information regarding the detected physical events detected by the plurality of vehicles and the road segment attributes calculated by the plurality of vehicles.

98. The method of claim 97, wherein the detected physical event is selected from the group consisting of: collision, slip, sideslip, spin, latitude spin, and longitude spin.

99. The method of claim 97, wherein the detected physical event comprises a collision, a slip, a sideslip, a rotation, a latitude rotation, and a longitude rotation.

100. The method of claim 97, wherein the first vehicle sensor comprises an accelerometer and a plurality of wheel motion sensors.

101. The method of claim 97, wherein the road segment attributes comprise at least one of: (i) a curvature of a set of road segments including the road segment; (ii) a longitudinal slope of the road segment, (iii) a lateral slope of the road segment, (iv) a level of grip associated with the road segment, and (v) a degree of undulation of the road segment.

102. The method of claim 97, wherein the road segment attributes comprise at least three road segment attributes from among: (i) a curvature of a set of road segments including the road segment; (ii) a longitudinal slope of the road segment, (iii) a lateral slope of the road segment, (iv) a level of grip associated with the road segment, and (v) a degree of undulation of the road segment.

103. The method of claim 97, wherein the reference map includes (a) reference information regarding previously detected physical events related to the plurality of road segments, and (b) reference road segment attributes related to the plurality of road segments.

104. The method of claim 97, wherein the reference map comprises a base layer that stores information about locations of the plurality of road segments and spatial relationships between the plurality of road segments.

105. The method of claim 104, wherein the reference map includes a layer storing the reference information for the previously detected physical events related to the plurality of road segments.

106. The method of claim 97, wherein the reference map comprises (a) a base layer storing information about locations of and spatial relationships between the plurality of road segments, and (b) one or more sparse layers comprising additional information about only some of the plurality of road segments; wherein the one or more sparse layers are linked to the base layer.

107. The method of claim 97, wherein the reference map includes a fixed-field-size sparse layer and a variable-size sparse layer; wherein the variable-size sparse layer includes the reference physical event information.

108. The method of claim 97, wherein the reference map includes a private field storing information about a mode of travel associated with the vehicle or with a driver of the vehicle, and includes a public field.

109. The method of claim 97, wherein the physical event information comprises a normalized amplitude of the detected physical event.

110. A non-transitory computer program product for generating a reference map of an area, the non-transitory computer program product storing instructions for:

receiving, from a plurality of vehicles through a communication interface, (a) physical event information about detected physical events detected by the plurality of vehicles while traveling on road segments belonging to the area, and (b) road segment attributes calculated by the plurality of vehicles, the road segment attributes relating to road segments belonging to the area; wherein the physical event information of a vehicle of the plurality of vehicles is based on a first set of parameters sensed by a first vehicle sensor of the vehicle; wherein the first set of parameters includes a wheel motion parameter and a vehicle acceleration parameter; wherein the first vehicle sensor is different from a road image sensor; and

calculating, by a computerized system, the reference map based on the physical event information regarding detected physical events detected by the plurality of vehicles and the road segment attributes calculated by the plurality of vehicles.

111. The non-transitory computer program product of claim 110, wherein the detected physical event is selected from the group consisting of: collision, slip, sideslip, spin, latitude spin, and longitude spin.

112. The non-transitory computer program product of claim 110, wherein the detected physical event comprises a collision, a slip, a sideslip, a rotation, a latitude rotation, and a longitude rotation.

113. The non-transitory computer program product of claim 110, wherein the first vehicle sensor comprises an accelerometer and a plurality of wheel motion sensors.

114. The non-transitory computer program product of claim 110, wherein the road segment attributes include at least one road segment attribute of: (i) a curvature of a set of road segments including the road segment; (ii) a longitudinal slope of the road segment, (iii) a lateral slope of the road segment, (iv) a level of grip associated with the road segment, and (v) a degree of undulation of the road segment.

115. The non-transitory computer program product of claim 110, wherein the road segment attributes include at least three road segment attributes from among: (i) a curvature of a set of road segments including the road segment; (ii) a longitudinal slope of the road segment, (iii) a lateral slope of the road segment, (iv) a level of grip associated with the road segment, and (v) a degree of undulation of the road segment.

116. The non-transitory computer program product of claim 110, wherein the reference map comprises: (a) reference information regarding previously detected physical events associated with the plurality of road segments, and (b) reference road segment attributes associated with the plurality of road segments.

117. The non-transitory computer program product of claim 110, wherein the reference map includes a base layer that stores information about locations of the plurality of road segments and spatial relationships between the plurality of road segments.

118. The non-transitory computer program product of claim 117, wherein the reference map includes a layer storing the reference information regarding the previously detected physical events related to the plurality of road segments.

119. The non-transitory computer program product of claim 110, wherein the reference map comprises (a) a base layer storing information about locations of and spatial relationships between the plurality of road segments, and (b) one or more sparse layers comprising additional information about only some of the plurality of road segments; wherein the one or more sparse layers are linked to the base layer.

120. The non-transitory computer program product of claim 110, wherein the reference map comprises a fixed-field-size sparse layer and a variable-size sparse layer; wherein the variable-size sparse layer includes the reference physical event information.

121. The non-transitory computer program product of claim 110, wherein the reference map includes a private field storing information about a mode of travel associated with the vehicle or with a driver of the vehicle, and includes a public field.

122. The non-transitory computer program product of claim 110, wherein the physical event information includes a normalized amplitude of the detected physical event.

123. A system for generating a reference map of an area, the system comprising: a communication interface configured to: receiving, from a plurality of vehicles, (a) physical event information about detected physical events detected by the plurality of vehicles while traveling on a road segment belonging to the area, and (b) road segment attributes calculated by the plurality of vehicles, the road segment attributes relating to road segments belonging to the area; wherein the physical event information of a vehicle of the plurality of vehicles is based on a first set of parameters sensed by a first vehicle sensor of the vehicle; wherein the first set of parameters includes a wheel motion parameter and a vehicle acceleration parameter; wherein the first vehicle sensor is different from a road image sensor; and a processor configured to calculate the reference map based on the physical event information on the detected physical events detected by the plurality of vehicles and the section attributes calculated by the plurality of vehicles.

124. A method for generating a vehicle profile, the method comprising: collecting vehicle profile information candidates, wherein the vehicle profile information candidates include fuel consumption information related to different road paths and vehicle parameters; wherein at least some of the road path and the vehicle parameters are sensed by a first vehicle sensor different from a road image sensor; and generating the vehicle profile based at least on the vehicle profile information candidate; wherein the vehicle profile consists essentially of:

(i) a cruise data structure comprising cruise information on values of a cruise fuel consumption parameter associated with constant speed movement of the vehicle for a first set of road paths and different values of vehicle parameters,

(ii) an idle deceleration data structure comprising idle deceleration information regarding values of idle deceleration distance values associated with idle deceleration of the vehicle for a second set of road paths and different values of vehicle parameters,

(iii) an acceleration data structure comprising acceleration information for values of an acceleration fuel consumption parameter associated with a constant acceleration of the vehicle for a third set of road paths and different values of vehicle parameters.

125. The method as claimed in claim 124, wherein said cruise data structure consists essentially of values of said cruise fuel consumption parameter.

126. The method of claim 125, wherein the first set of road path and vehicle parameters consists essentially of vehicle speed, road grade, vehicle weight, and one or more driveline parameters.

127. The method of claim 126, wherein the driveline parameters include gear and throttle position.

128. The method of claim 124, wherein the idle deceleration structure consists essentially of a value of the idle deceleration distance.

129. The method of claim 128, wherein the second set of road paths and vehicle parameters consists essentially of a starting vehicle speed, a road segment grade, and a vehicle weight.

130. The method of claim 128, wherein the second set of road paths and vehicle parameters consists essentially of a starting vehicle speed, a road segment grade, a vehicle weight, and one or more driveline parameters.

131. The method of claim 130, wherein the drive train parameter comprises gear.

132. The method according to claim 124, wherein said cruise data structure consists essentially of values of said acceleration fuel consumption parameter.

133. The method of claim 132, wherein the third set of road paths and vehicle parameters consists essentially of a starting vehicle speed, a road segment grade, a vehicle weight, an acceleration distance, and one or more driveline parameters.

134. The method of claim 133, wherein the driveline parameters include gear and throttle position.

135. The method of claim 124, comprising excluding vehicle profile information candidates based on a comparison between a grade of a path segment and: a ratio between (i) a height difference between two ends of the path segment and (ii) a length of a horizontal projection of the path segment.

136. The method of claim 124, further comprising dynamically clustering vehicles based on the vehicle profile.

137. The method of claim 136, further comprising computing a cluster profile for each cluster.

138. The method of claim 137, further comprising updating at least one of the cruise data structure, the idle deceleration data structure, and the acceleration data structure based at least on a cluster profile that includes a cluster of the vehicle.

139. The method of claim 124, further comprising compressing the vehicle profile to generate a compressed vehicle profile.

140. The method of claim 139, wherein said compressing includes calculating a mathematical relationship between a relevant road path and vehicle parameters, and removing information about at least one of the relevant road path and vehicle parameters from at least one of the cruise data structure, the idle deceleration data structure, and the acceleration data structure.

141. The method of claim 139, wherein said compressing includes removing road paths and vehicle parameters associated with a subset of vehicle speeds.

142. The method of claim 139, wherein said compressing includes using one or more road paths and vehicle parameters as keywords without storing said one or more road paths and vehicle parameters in any of said vehicle profiles.

143. The method of claim 124, wherein the generating of the vehicle profile includes estimating a value of the cruise fuel consumption parameter for a particular value of a first set of road paths and vehicle parameters, wherein the estimating is responsive to the value of the cruise fuel consumption parameter for a particular other measurement of the first set of road paths and vehicle parameters.

144. The method of claim 124, further comprising calculating suggested travel parameters for a path ahead of the vehicle, wherein the calculating is based at least in part on the vehicle profile, path portion grade, and extrinsic limits.

145. The method of claim 144, wherein the calculating comprises virtually dividing the path into a plurality of portions, each portion comprising one or more path segments having substantially the same grade and substantially the same extrinsic limit.

146. The method of claim 145, comprising finding an optimal speed for each segment based on a grade and a maximum speed limit associated with the segment.

147. The method of claim 124, wherein the vehicle profile includes the cruise data structure, the idle deceleration data structure, and the acceleration data structure.

148. A non-transitory computer program product for generating a vehicle profile, wherein the non-transitory computer program product stores instructions for:

collecting vehicle profile information candidates, wherein the vehicle profile information candidates include fuel consumption information related to different road paths and vehicle parameters; wherein at least some of the road path and the vehicle parameters are sensed by a first vehicle sensor different from a road image sensor; and

generating the vehicle profile based at least on the vehicle profile information candidate; wherein the vehicle profile consists essentially of:

(i) a cruise data structure comprising cruise information on values of a cruise fuel consumption parameter associated with constant speed movement of the vehicle for a first set of road paths and different values of vehicle parameters,

(ii) an idle deceleration data structure comprising idle deceleration information regarding values of idle deceleration distance values associated with idle deceleration of the vehicle for a second set of road paths and different values of vehicle parameters,

(iii) an acceleration data structure comprising acceleration information for values of an acceleration fuel consumption parameter associated with a constant acceleration of the vehicle for a third set of road paths and different values of vehicle parameters.

149. A computerized system for generating a vehicle profile, the computerized system comprising:

a collection module to collect vehicle profile information candidates, wherein the vehicle profile information candidates include fuel consumption information related to different road paths and vehicle parameters; wherein at least some of the road path and the vehicle parameters are sensed by a first vehicle sensor different from a road image sensor; and

a computer to generate the vehicle profile based at least on the vehicle profile information candidate; wherein the vehicle profile consists essentially of:

a cruise data structure comprising cruise information on values of a cruise fuel consumption parameter associated with constant speed movement of the vehicle for a first set of road paths and different values of vehicle parameters,

an idle deceleration data structure comprising idle deceleration information regarding values of idle deceleration distance values associated with idle deceleration of the vehicle for a second set of road paths and different values of vehicle parameters,

an acceleration data structure comprising acceleration information for values of an acceleration fuel consumption parameter associated with a constant acceleration of the vehicle for a third set of road paths and different values of vehicle parameters; and

a memory for storing the cruise data structure, the idle deceleration data structure, and the acceleration data structure.

150. A method for determining a travel period, the method comprising:

receiving or generating, by the vehicle computer, a vehicle profile and a grade of a portion of the path ahead of the vehicle; wherein the vehicle profile is generated based on at least a road path and a vehicle parameter; wherein at least some of the road path and the vehicle parameters are sensed by a vehicle sensor different from a road image sensor; and

determining, by the vehicle computer, a suggested travel parameter for a path ahead of the vehicle, wherein the calculating is based at least in part on the vehicle profile, a path portion grade, and an extrinsic limit.

151. The method of claim 150, wherein the calculating comprises virtually dividing the path into a plurality of portions, each portion comprising one or more path segments having substantially the same grade and substantially the same extrinsic limit.

152. The method of claim 150, comprising finding an optimal speed for each segment based on the grade and a maximum speed limit associated with that segment.

153. The method of claim 150, wherein the vehicle profile consists essentially of a cruise data structure, an idle deceleration data structure, and an acceleration data structure.

154. The method of claim 150, wherein the vehicle profile includes a cruise data structure, an idle deceleration data structure, and an acceleration data structure.

155. A non-transitory computer program product for determining a travel period, wherein the non-transitory computer program product stores instructions for:

receiving or generating, by the vehicle computer, a vehicle profile and a grade of a portion of the path ahead of the vehicle; wherein the vehicle profile is generated based on at least a road path and a vehicle parameter; wherein at least some of the road path and the vehicle parameters are sensed by a vehicle sensor different from a road image sensor; and determining, by the vehicle computer, suggested driving parameters for the path ahead of the vehicle, wherein the calculating is based at least in part on the vehicle profile, path portion grade, and extrinsic limits.

156. A method for estimating the weight of a vehicle, the method comprising:

obtaining vehicle sensor measurements regarding a travel period of the vehicle during a learning cycle and by a vehicle sensor, wherein the vehicle sensor measurements comprise: (a) a height measurement of a route associated with the travel period, (b) a fuel consumption measurement associated with the travel period, (c) a length measurement of a road segment associated with the travel period; and (d) a speed measurement associated with the travel period; and

calculating an estimated weight of the vehicle based on the vehicle sensor measurements; wherein the calculation is based on a value of an energy coefficient indicative of energy wasted by the vehicle.

157. The method of claim 156, wherein the calculating of the estimated weight further comprises finding a motor efficiency function and a fuel consumption error correction function.

158. The method of claim 156, wherein the calculating comprises searching for values of the energy coefficient that provide at least one distribution related to a weight estimate of the vehicle, the at least one distribution satisfying at least one predefined statistical significance criterion.

159. The method of claim 156, wherein the determining of the estimated weight comprises determining a weight estimate for each of the plurality of path segments according to the following equation:

wherein the energy coefficient group comprises k₁、k₂、k₃And k₄；

Where ame is the value of the estimated motor efficiency function;

wherein v is₂Is the speed of the vehicle at the end of the path segment;

v₁is the speed of the vehicle at the beginning of the path segment;

v represents at least one value of the speed of the vehicle when travelling on the path segment;

x is the length of the path segment;

Δ h is the height difference between the end point and the start point of the path segment; and

fuel is the error corrected fuel consumption associated with the path segment.

160. The method of claim 159, wherein the calculating comprises searching for values of the energy coefficient that provide at least one distribution related to a weight estimate of the vehicle, the at least one distribution satisfying at least one predefined statistical significance criterion.

161. The method of claim 160, wherein the predefined statistical significance criteria is a maximum statistical significance.

162. The method of claim 160, wherein the predefined statistical significance criterion is a minimum standard deviation of at least one of the weight estimation distributions.

163. The method of claim 160, wherein the determining of the estimated weight comprises determining a weight estimate for each of the plurality of path segments and for a different value of the energy coefficient.

164. The method of claim 160, wherein the determining of the estimated weight comprises determining a weight estimate for each of the plurality of path segments, for different values of the energy coefficient, and for different motor efficiency function values.

165. The method of claim 160, wherein the determining of the estimated weight comprises determining a weight estimate for each of the plurality of path segments, for different values of the energy coefficient, and for different fuel consumption error correction function values.

166. The method of claim 160, wherein the determining of the estimated weight comprises determining a weight estimate for each of the plurality of path segments, for a different value of the energy coefficient, for a different motor efficiency function value, and for a different fuel consumption error correction function value.

167. The method of claim 160, wherein determining the estimated weight comprises associating a mass attribute with each weight estimate.

168. The method of claim 160, wherein the determining of the estimated weight includes associating a mass attribute with each weight estimate, wherein the at least one distribution relating to weight estimates of the vehicle is responsive to the mass attribute assigned to each weight estimate.

169. The method of claim 160, wherein the determining of the estimated weight comprises associating a mass attribute with each weight estimate, wherein the at least one distribution related to the weight estimate of the vehicle is a histogram, wherein the histogram includes a bar region, wherein each bar region is associated with a weight estimate range and has a value representing the mass attribute of the weight estimate belonging to the bar region.

170. The method of claim 160, wherein the determining of the estimated weight comprises associating a mass attribute with each weight estimate, wherein the at least one distribution related to the weight estimate of the vehicle is a histogram, wherein the histogram includes a bar region, wherein each bar region is associated with a weight estimate range and has a value representing a sum of mass attributes of weight estimates belonging to the bar region.

171. The method of claim 160, comprising assigning a quality attribute to at least some of the vehicle sensor measurements.

172. The method of claim 160, comprising assigning a quality attribute to a vehicle sensor measurement associated with a particular path segment based on a difference related to the speed of the vehicle at a start and an end of the particular path segment.

173. The method of claim 160, comprising assigning a quality attribute to a vehicle sensor measurement associated with a particular path segment based on a maximum speed of the vehicle during a particular travel period.

174. The method of claim 160, comprising disregarding vehicle sensor measurements obtained at a path segment where the vehicle is descending.

175. The method of claim 156, wherein the computing comprises applying machine learning.

176. A non-transitory computer-readable medium for estimating a weight of a vehicle, the non-transitory computer-readable medium storing instructions for:

obtaining vehicle sensor measurements regarding a travel period of the vehicle during a learning cycle, wherein the vehicle sensor measurements include: (a) a height measurement of a route associated with the travel period, (b) a fuel consumption measurement associated with the travel period, (c) a length measurement of a road segment associated with the travel period; and (d) a speed measurement associated with the travel period; and

calculating an estimated weight of the vehicle based on the vehicle sensor measurements; wherein the calculation is based on a value of an energy coefficient indicative of energy wasted by the vehicle.

177. The non-transitory computer readable medium of claim 176, wherein calculating the estimated weight further comprises finding a motor efficiency function and a fuel consumption error correction function.

178. The non-transitory computer-readable medium of claim 176, wherein the calculating comprises searching for values that provide energy coefficients for at least one distribution related to a weight estimate of the vehicle, the at least one distribution satisfying at least one predefined statistical significance criterion.

179. The non-transitory computer readable medium of claim 176, wherein the determining of the estimated weight comprises determining a weight estimate for each of the plurality of path segments according to the following equation:

wherein the energy coefficient group comprises k₁、k₂、k₃And k₄；

Where ame is the value of the estimated motor efficiency function;

wherein v is₂Is the speed of the vehicle at the end of the path segment;

v₁is the speed of the vehicle at the beginning of the path segment;

v represents at least one value of the speed of the vehicle when travelling on the path segment;

x is the length of the path segment;

Δ h is the height difference between the end point and the start point of the path segment; and

fuel is the error corrected fuel consumption associated with the path segment.

180. The non-transitory computer-readable medium of claim 179, wherein the calculating comprises searching for values of energy coefficients that provide at least one distribution related to a weight estimate of the vehicle, the at least one distribution satisfying at least one predefined statistical significance criterion.

181. The non-transitory computer-readable medium of claim 180, wherein the predefined statistical significance criterion is a maximum statistical significance.

182. The non-transitory computer-readable medium of claim 180, wherein the predefined statistical significance criterion is a minimum standard deviation of at least one of the weight estimation distributions.

183. The non-transitory computer-readable medium of claim 180, wherein the determination of the estimated weight includes determining a weight estimate for each of the plurality of path segments and for different values of the energy coefficient.

184. The non-transitory computer readable medium of claim 180, wherein the determining of the estimated weight includes determining a weight estimate for each of the plurality of path segments, for different values of the energy coefficient, and for different motor efficiency function values.

185. The non-transitory computer readable medium of claim 180, wherein the determination of the estimated weight comprises determining a weight estimate for each of the plurality of path segments, for a different value of the energy coefficient, and for a different fuel consumption error correction function value.

186. The non-transitory computer readable medium of claim 180, wherein the determination of the estimated weight comprises determining a weight estimate for each of the plurality of path segments, for a different value of the energy coefficient, for a different motor efficiency function value, and for a different fuel consumption error correction function value.

187. The non-transitory computer-readable medium of claim 180, wherein the determination of the estimated weight comprises associating a mass attribute with each weight estimate.

188. The non-transitory computer-readable medium of claim 180, wherein the determination of the estimated weight includes associating a mass attribute with each weight estimate, wherein the at least one distribution related to weight estimates for the vehicle is responsive to the mass attribute assigned to each weight estimate.

189. The non-transitory computer-readable medium of claim 180, wherein the determination of the estimated weight includes associating a mass attribute with each weight estimate, wherein the at least one distribution related to the weight estimate of the vehicle is a histogram, wherein the histogram includes a bar region, wherein each bar region is associated with a weight estimate range and has a value representing the mass attribute of the weight estimate belonging to the bar region.

190. The non-transitory computer-readable medium of claim 180, wherein the determination of the estimated weight includes associating a mass attribute with each weight estimate, wherein the at least one distribution related to the weight estimate of the vehicle is a histogram, wherein the histogram includes vertical bar regions, wherein each vertical bar region is associated with a weight estimate range and has a value representing a sum of mass attributes of weight estimates belonging to the vertical bar region.

191. The non-transitory computer-readable medium of claim 180 storing instructions for assigning a quality attribute to at least some of the vehicle sensor measurements.

192. The non-transitory computer-readable medium of claim 180, storing instructions for assigning a quality attribute to a vehicle sensor measurement related to a particular path segment based on a difference related to the speed of the vehicle at a start and an end of the particular path segment.

193. The non-transitory computer-readable medium of claim 180, storing instructions for assigning a quality attribute to a vehicle sensor measurement associated with a particular path segment based on a maximum speed of the vehicle during a particular travel period.

194. The non-transitory computer-readable medium of claim 180 storing instructions for ignoring vehicle sensor measurements obtained at a path segment where the vehicle is descending.

195. The non-transitory computer-readable medium of claim 176, wherein the computing comprises applying machine learning.

196. A method for estimating the weight of a vehicle, the method comprising: receiving a value indicative of an energy coefficient of energy wasted by the vehicle; wherein the value of the energy coefficient is calculated based at least in part on vehicle sensor measurements obtained by vehicle sensors of the vehicle, the vehicle sensor measurements being obtained during a travel period of the vehicle; wherein the vehicle sensor measurements comprise: (a) a height measurement of a route associated with the travel period, (b) a fuel consumption measurement associated with the travel period, (c) a length measurement of the road segment associated with the travel period; and (d) a speed measurement associated with the travel period; obtaining, during a new travel period and by the vehicle sensor, a new vehicle sensor measurement related to the new travel period; and calculating, by a vehicle computer, a weight of the vehicle based on the value of the energy coefficient and the new vehicle sensor measurement.

197. The method of claim 196, further comprising receiving information about a motor efficiency function of the vehicle, and wherein the calculating the weight of the vehicle is further responsive to the motor efficiency function of the vehicle.

198. The method of claim 197 wherein the information about the motor efficiency function includes motor efficiency function coefficients.

199. The method of claim 198, wherein the number of motor efficiency function coefficients may not exceed fifty.

200. The method of claim 196, further comprising receiving information about a fuel consumption error correction function for the vehicle, and wherein the calculating of the weight of the vehicle is further responsive to the fuel consumption error correction function.

201. The method of claim 200, wherein the information about a fuel consumption error correction function comprises fuel consumption error correction function coefficients.

202. The method of claim 201, wherein the number of fuel consumption error correction function coefficients does not exceed ten.

203. The method of claim 196, further comprising receiving information about a motor efficiency function of the vehicle and a fuel consumption error correction function of the vehicle, and wherein the calculating of the weight of the vehicle is further responsive to the motor efficiency function of the vehicle and to the fuel consumption error correction of the vehicle.

204. The method of claim 196, wherein the calculating of the weight of the vehicle is performed in real-time.

205. The method of claim 196, further comprising transmitting the new vehicle sensor measurements related to the new travel period.

206. The method of claim 196, further comprising receiving an updated value of an energy coefficient, and wherein the calculating of the weight is responsive to the updated value of an energy coefficient.

207. The method of claim 196, wherein the calculating of the weight comprises calculating the following equation for a new path segment for the new time period:

wherein the energy coefficient group comprises k₁、k₂、k₃And k₄；

Where ame is the value of the estimated motor efficiency function;

wherein v is₂Is the speed of the vehicle at the end of the new path segment;

v₁is the speed of the vehicle at the start of the new path segment;

v represents at least one value of the speed of the vehicle when travelling on the new path segment;

x is the length of the new path segment;

Δ h is the height difference between the start and end points of the new path segment; and

fuel is the error corrected fuel consumption associated with the new path segment.

208. A non-transitory computer-readable medium for estimating a weight of a vehicle, the non-transitory computer-readable medium storing instructions for: receiving a value indicative of an energy coefficient of energy wasted by the vehicle; wherein the value of the energy coefficient is calculated based at least in part on vehicle sensor measurements obtained by vehicle sensors of the vehicle, the vehicle sensor measurements being obtained during a travel period of the vehicle; wherein the vehicle sensor measurements comprise: (a) a height measurement of a route associated with the travel period, (b) a fuel consumption measurement associated with the travel period, (c) a length measurement of the road segment associated with the travel period; and (d) a speed measurement associated with the travel period; obtaining, during a new travel period and by the vehicle sensor, a new vehicle sensor measurement related to the new travel period; and calculating, by a vehicle computer, a weight of the vehicle based on the value of the energy coefficient and the new vehicle sensor measurement.

209. The non-transitory computer readable medium of claim 208 storing instructions for receiving information about a motor efficiency function of the vehicle, and wherein the calculating of the weight of the vehicle is further responsive to the motor efficiency function of the vehicle.

210. The non-transitory computer-readable medium of claim 209, wherein the information about the motor efficiency function includes motor efficiency function coefficients.

211. The non-transitory computer readable medium of claim 210, wherein the number of motor efficiency function coefficients does not exceed fifty.

212. The non-transitory computer readable medium of claim 208 storing instructions for receiving information about a fuel consumption error correction function for the vehicle, and wherein the calculation of the weight of the vehicle is further responsive to the fuel consumption error correction function.

213. The non-transitory computer readable medium of claim 212, wherein the information about a fuel consumption error correction function includes fuel consumption error correction function coefficients.

214. The non-transitory computer readable medium of claim 213, wherein a number of fuel consumption error correction function coefficients does not exceed ten.

215. The non-transitory computer readable medium of claim 208 storing instructions for receiving information about a motor efficiency function of the vehicle and a fuel consumption error correction function of the vehicle, and wherein the calculating of the weight of the vehicle is further responsive to the motor efficiency function of the vehicle and to the fuel consumption error correction of the vehicle.

216. The non-transitory computer-readable medium of claim 208, wherein the calculating of the weight of the vehicle is performed in real-time.

217. The non-transitory computer-readable medium of claim 208 storing instructions for transmitting the new vehicle sensor measurements related to the new travel period.

218. The non-transitory computer readable medium of claim 208 storing instructions for receiving an updated value of an energy coefficient, and wherein the calculating of the weight is responsive to the updated value of an energy coefficient.

219. The non-transitory computer-readable medium of claim 208, wherein the calculating of the weight comprises calculating, for a new path segment of the new time period, the following equation:

wherein the energy coefficient group comprises k₁、k₂、k₃And k₄；

Where ame is the value of the estimated motor efficiency function;

wherein v is₂Is the speed of the vehicle at the end of the new path segment;

v₁is the speed of the vehicle at the start of the new path segment;

v represents at least one value of the speed of the vehicle when travelling on the new path segment;

x is the length of the new path segment;

Δ h is the height difference between the start and end points of the new path segment; and

fuel is the error corrected fuel consumption associated with the new path segment.

220. A method for generating path-segment-related and vehicle-related normalized path-segment grip information, the method comprising: generating wheel speed information relating to speeds of a plurality of wheels of the vehicle using a sensor; detecting, by a vehicle computer and based on the wheel speed information, a grip event; determining the normalized path segment grip information based on vehicle parameters obtained during at least a portion of the grip event; and performing at least one of the following operations: (i) transmit the normalized path segment grip information and (ii) store the normalized path segment grip information.

221. The method of claim 220, comprising receiving from a computerized system normalized path segment grip information generated by the computerized system, and de-normalizing the normalized path segment grip information generated by the computerized system to provide actual path segment grip information.

222. The method of claim 221, comprising calculating a marginal grip of the vehicle as it traverses the path segment based on the actual path segment grip information.

223. The method of claim 221, wherein the de-normalization is based on at least some of speed, climate bias, wheel active patch size, tire health, weight of the vehicle, and excitation.

224. The method of claim 220, wherein the grip event is selected from a braking event, a turning event, and a high speed event.

225. The method of claim 220, wherein the determination of the normalized path segment grip information includes calculating an excitation, calculating a slip ratio, and calculating a normalized slip ratio and a normalized excitation.

226. The method of claim 225, comprising determining a normalized slip curve based on the normalized slip ratio and the normalized stimulus.

227. The method of claim 226, wherein the calculation of the incentive includes selecting some vehicle speed readings and ignoring other vehicle speed readings obtained during the traction event.

228. The method of claim 226, wherein the calculation of the normalized slip ratio and normalized excitation is based on at least one of speed, climate bias, wheel active patch size, tire health, weight of the vehicle, and excitation.

229. The method of claim 220, wherein the generating of the wheel speed information includes low pass filtering the wheel speed information, wherein the low pass filtering is responsive to an expected wheel speed.

230. The method of claim 220, wherein the generating of the wheel speed information includes ignoring short term variations.

231. The method of claim 220, wherein the traction event is a response of the vehicle to negotiating a small obstacle, wherein the small obstacle has a length less than a circumference of each of the plurality of wheels of the vehicle.

232. A non-transitory computer program product for generating path segment-related and vehicle-related normalized path segment grip information, wherein the non-transitory computer program product stores instructions for: generating wheel speed information relating to speeds of a plurality of wheels of the vehicle using a sensor; detecting, by a vehicle computer and based on the wheel speed information, a grip event; determining the normalized path segment grip information based on vehicle parameters obtained during at least a portion of the grip event; and performing at least one of the following operations: (i) transmit the normalized path segment grip information and (ii) store the normalized path segment grip information.

233. The non-transitory computer program product of claim 232, storing instructions for receiving from a computerized system normalized path segment grip information generated by the computerized system and de-normalizing the normalized path segment grip information generated by the computerized system to provide actual path segment grip information.

234. The non-transitory computer program product of claim 233 storing instructions for calculating a marginal grip of the vehicle as it traverses the path segment based on the actual path segment grip information.

235. The non-transitory computer program product of claim 233, wherein the de-normalization is based on at least some of speed, climate bias, wheel active patch size, tire health, weight of the vehicle, and excitation.

236. The non-transitory computer program product of claim 232, wherein the grip event is selected from a braking event, a turning event, and a high speed event.

237. The non-transitory computer program product of claim 232, wherein the determination of the normalized path segment grip information includes calculating an incentive, calculating a slip ratio, and calculating a normalized slip ratio and a normalized incentive.

238. The non-transitory computer program product of claim 237, storing instructions for determining a normalized slip curve based on the normalized slip ratio and the normalized stimulus.

239. The non-transitory computer program product of claim 237, wherein the calculation of the incentive includes selecting some vehicle speed readings and ignoring other vehicle speed readings obtained during the traction event.

240. The non-transitory computer program product of claim 237, wherein the calculation of the normalized slip ratio and normalized incentive is based on at least one of speed, climate bias, wheel active patch size, tire health, weight of the vehicle, and incentive.

241. The non-transitory computer program product of claim 232, wherein the generation of the wheel speed information includes low pass filtering wheel speed information, wherein the low pass filtering is responsive to an expected wheel speed.

242. The non-transitory computer program product of claim 232, wherein the generation of the wheel speed information includes ignoring short term variations.

243. The non-transitory computer program product of claim 232, wherein the traction event is a response of a vehicle to passing a small obstacle, wherein the small obstacle has a length that is less than a circumference of each of a plurality of wheels of the vehicle.

244. A vehicle system for generating a vehicle profile, the vehicle system comprising: a sensor configured to generate wheel speed information related to speeds of a plurality of wheels of the vehicle; a computer vehicle configured to: (i) detecting a grip event based on the wheel speed information; and (ii) determining the normalized path segment grip information based on vehicle parameters obtained during at least a portion of the grip event; and (a) at least one of a communication module configured to transmit the normalized path segment grip information and a memory module configured to store the normalized path segment grip information.

245. A method for generating path-segment-related and vehicle-related normalized path-segment grip information, the method comprising: generating wheel speed information relating to speeds of a plurality of wheels of the vehicle using a sensor; detecting, by a vehicle computer and based on the wheel speed information, a response of the vehicle to passing a small obstacle; wherein the small obstacle has a length that is less than a circumference of each of the plurality of wheels of the vehicle; determining the normalized path segment grip information based on vehicle parameters obtained during at least a portion of the vehicle's response to passing the small obstacle; and performing at least one of the following operations: (i) transmitting the normalized path segment grip information and (ii) storing the normalized path segment grip information.

246. The method of claim 245, comprising receiving from a computerized system normalized path segment grip information generated by said computerized system, and de-normalizing said normalized path segment grip information generated by said computerized system to provide actual path segment grip information.

247. The method of claim 246, comprising calculating a marginal grip of the vehicle as it traverses the path segment based on the actual path segment grip information.

248. The method of claim 246, wherein the de-normalization is based on at least some of speed, climate bias, wheel active patch size, tire health, weight of the vehicle, and excitation.

249. The method of claim 245, wherein the determination of the normalized path segment grip information includes calculating an excitation, calculating a slip ratio, and calculating a normalized slip ratio and a normalized excitation.

250. The method of claim 249, comprising determining a normalized slip curve based on the normalized slip ratio and the normalized stimulus.

251. The method of claim 249, wherein the calculation of the incentive includes selecting some vehicle speed readings and ignoring other vehicle speed readings obtained during the vehicle's response to passing the small obstacle.

252. The method of claim 249, wherein the calculation of the normalized slip ratio and normalized excitation is based on at least one of speed, climate bias, wheel active patch size, tire health, weight of the vehicle, and excitation.

253. The method of claim 245, wherein the generating of the wheel speed information comprises low pass filtering the wheel speed information, wherein the low pass filtering is responsive to an expected wheel speed.

254. The method of claim 245, wherein the generating of the wheel speed information comprises ignoring short term variations.

255. A non-transitory computer program product for generating path segment-related and vehicle-related normalized path segment grip information, wherein the non-transitory computer program product stores instructions for: generating wheel speed information relating to speeds of a plurality of wheels of the vehicle using a sensor; detecting, by a vehicle computer and based on the wheel speed information, a response of the vehicle to passing a small obstacle; wherein the small obstacle has a length less than a circumference of each of a plurality of wheels of the vehicle; determining the normalized path segment grip information based on vehicle parameters obtained during at least a portion of the vehicle's response to passing the small obstacle; and performing at least one of the following operations: (i) transmitting the normalized path segment grip information and (ii) storing the normalized path segment grip information.

256. The non-transitory computer program product of claim 255, storing instructions for receiving from a computerized system normalized path segment grip information generated by the computerized system and de-normalizing the normalized path segment grip information generated by the computerized system to provide actual path segment grip information.

257. The non-transitory computer program product of claim 256 storing instructions for calculating a marginal grip of the vehicle as it traverses the path segment based on the actual path segment grip information.

258. The non-transitory computer program product of claim 256, wherein the de-normalization is based on at least some of speed, climate bias, wheel active patch size, tire health, weight of the vehicle, and excitation.

259. The non-transitory computer program product of claim 255, wherein the determination of the normalized path segment grip information includes calculating an incentive, calculating a slip ratio, and calculating a normalized slip ratio and a normalized incentive.

260. The non-transitory computer program product of claim 259, storing instructions for determining a normalized slip curve based on the normalized slip ratio and the normalized stimulus.

261. The non-transitory computer program product of claim 259, wherein the calculation of the incentive includes selecting some vehicle speed readings and ignoring other vehicle speed readings obtained during the vehicle's response to passing the small obstacle.

262. The non-transitory computer program product of claim 259, wherein the calculation of the normalized slip ratio and normalized incentive is based on at least one of speed, climate bias, wheel active patch size, tire health, weight of vehicle, and incentive.

263. The non-transitory computer program product of claim 255, wherein the generation of the wheel speed information includes low pass filtering wheel speed information, wherein the low pass filtering is responsive to an expected wheel speed.

264. The non-transitory computer program product of claim 255, wherein the generation of the wheel speed information includes ignoring short-term variations.

265. A vehicle system for generating a vehicle profile, the vehicle system comprising: a sensor configured to generate wheel speed information related to speeds of a plurality of wheels of the vehicle; a computer vehicle configured to: (i) detecting a response of the vehicle to passing a small obstacle based on the wheel speed information; and (ii) determining the normalized path segment grip information based on vehicle parameters obtained during at least a portion of the vehicle's response to passing the small obstacle; and (a) at least one of a communication module configured to transmit the normalized path segment grip information and a memory module configured to store the normalized path segment grip information.

266. A method for driving a vehicle, the method comprising:

receiving or generating rain information about rain associated with a plurality of road segments;

estimating a reduction in grip level associated with each of the plurality of road segments, wherein the estimation of the reduction in grip level is based on the rain information, on at least one rain-related parameter of the vehicle, and on a mapping between the rain information and the reduction in grip level associated with each of the road segments; and

performing a travel-related operation based on the grip level reduction.

267. The method of claim 266, wherein the rain-related parameter of the vehicle comprises a health of at least one tire of the vehicle.

268. The method of claim 266, wherein estimating the reduction in grip level comprises estimating an occurrence of one or more slip events in the plurality of road segments.

269. The method of claim 268, wherein estimating the reduction in grip level comprises estimating the reduction in grip level associated with the occurrence of one or more slip events in the plurality of road segments.

270. The method of claim 268, comprising verifying occurrence of the one or more slip events of the vehicle.

271. The method of claim 270, wherein the verifying includes sensing, by a vehicle sensor, behavior of the vehicle as it travels over the plurality of road segments to provide a sensed result; and searching for one or more slip signatures in the sensing results by the vehicle.

272. The method of claim 266, comprising accumulating rain perception rate information obtained during a precipitation time window to generate the rain information.

273. The method of claim 266, wherein the performance of the travel-related operation includes selectively activating an autonomous driving module for autonomously driving the vehicle.

274. The method of claim 266, wherein the performance of the travel-related operation includes selectively deactivating an autonomous driving module configured to autonomously drive the vehicle when activated.

275. The method of claim 266, wherein the performance of the travel-related operation includes setting a speed of the vehicle in each of the plurality of road segments.

276. The method of claim 266, comprising estimating a rain perception rate via at least one vehicle sensor.

277. The method of claim 276, wherein the at least one vehicle sensor belongs to a wiper control unit.

278. The method of claim 266, wherein the performance of the travel-related operation includes alerting a human driver of the vehicle.

279. A non-transitory computer program product for driving a vehicle, wherein the non-transitory computer program product stores instructions for: receiving or generating rain information about rain associated with a plurality of road segments; estimating a reduction in grip level associated with each of the plurality of road segments, wherein the estimation of the reduction in grip level is based on the rain information, on at least one rain-related parameter of the vehicle, and on a mapping between the rain information and the reduction in grip level associated with each of the road segments; and performing a travel-related operation based on the grip level reduction.

280. The non-transitory computer-readable medium of claim 279, wherein the rain-related parameter of the vehicle comprises a health condition of at least one tire of the vehicle.

281. The non-transitory computer-readable medium of claim 279, wherein the estimation of the decrease in grip level comprises estimating an occurrence of one or more slip events in the plurality of road segments.

282. The non-transitory computer-readable medium of claim 281, wherein the estimation of the reduction in the grip level comprises estimating the reduction in grip level associated with an occurrence of one or more slip events in the plurality of road segments.

283. The non-transitory computer-readable medium of claim 281, comprising verifying occurrence of the one or more slip events of the vehicle.

284. The non-transitory computer-readable medium of claim 282, wherein the verifying includes sensing, by a vehicle sensor, behavior of the vehicle while traveling over the plurality of road segments to provide a sensed result; and searching for one or more slip signatures in the sensing results by the vehicle computer.

285. The non-transitory computer-readable medium of claim 279, storing instructions for accumulating rain perception rate information obtained during a precipitation time window to generate the rain information.

286. The non-transitory computer-readable medium of claim 279, wherein the performance of the travel-related operation comprises selectively activating an autonomous driving module for autonomously driving the vehicle.

287. The non-transitory computer-readable medium of claim 279, wherein the performance of the travel-related operation comprises selectively deactivating an autonomous driving module configured to autonomously drive the vehicle when activated.

288. The non-transitory computer-readable medium of claim 279, wherein the performance of the travel-related operation comprises setting a speed of the vehicle in each of the plurality of road segments.

289. The non-transitory computer-readable medium of claim 279, storing instructions for estimating a rain perception rate by at least one vehicle sensor.

290. The non-transitory computer readable medium of claim 283, wherein the at least one vehicle sensor belongs to a wiper control unit.

291. The non-transitory computer-readable medium of claim 279, wherein the performance of the travel-related operation comprises alerting a human driver of the vehicle.

292. A vehicle system for driving a vehicle, the vehicle system comprising: a sensor configured to perform at least one of the following operations: (a) sensing a behavior of the vehicle, and (b) sensing a rain parameter; and a computer vehicle configured to receive or generate rain information about rain associated with a plurality of road segments; estimating a grip level reduction associated with each of the plurality of road segments, wherein the estimation of the grip level reduction is based on the rain information, on at least one rain related parameter of the vehicle, and on a mapping between the rain information and grip level reduction associated with each of the road segments; and assisting in performing a travel-related operation based on the reduced grip level.

293. A method for estimating the occurrence of one or more slip events, the method comprising:

receiving or generating rain information about rain associated with a plurality of road segments; and

estimating, by a vehicle computer, an occurrence of the one or more slip events in the plurality of road segments, wherein the estimation of the occurrence of one or more slip events is based on the rain information, on at least one rain-related parameter of the vehicle, and on a mapping between the rain information and the occurrence of one or more slip events associated with each of the road segments.

294. The method of claim 293, comprising performing a driving-related operation based on the estimation of the occurrence of the one or more slip events.

295. The method of claim 293, comprising verifying the occurrence of the one or more slip events of the vehicle.

296. The method of claim 295, wherein the verifying includes sensing, by a vehicle sensor, behavior of the vehicle while traveling over the plurality of road segments to provide a sensed result; and searching for one or more slip signatures in the sensing results by the vehicle.

297. The method of claim 293, comprising accumulating rain perception rate information obtained during a precipitation time window to generate the rain information.

298. The method of claim 293, wherein the performance of the travel-related operation comprises selectively activating an autonomous driving module for autonomously driving the vehicle.

299. The method of claim 293, wherein the performance of the travel-related operation comprises selectively deactivating an autonomous driving module configured to autonomously drive the vehicle when activated.

300. The method of claim 293, wherein the performing of the travel-related operation comprises setting the speed of the measurement in each of the plurality of road segments.

301. The method of claim 293, comprising estimating a rain perception rate by at least one vehicle sensor.

302. The method of claim 301, wherein the at least one vehicle sensor belongs to a wiper control unit.

303. The method of claim 293, wherein the performance of the travel-related operation comprises alerting a human driver of the vehicle.

304. A non-transitory computer program product for estimating the occurrence of one or more slip events, wherein the non-transitory computer program product stores instructions for:

receiving or generating rain information about rain associated with a plurality of road segments; and

estimating, by a vehicle computer, an occurrence of the one or more slip events in the plurality of road segments, wherein the estimation of the occurrence of one or more slip events is based on the rain information, on at least one rain-related parameter of the vehicle, and on a mapping between the rain information and the occurrence of one or more slip events associated with each of the road segments.

305. The non-transitory computer-readable medium of claim 304, comprising performing a driving-related operation based on the estimation of the occurrence of the one or more slip events.

306. The non-transitory computer-readable medium of claim 304, comprising verifying the occurrence of the one or more slip events of the vehicle.

307. The non-transitory computer-readable medium of claim 306, wherein the verifying includes sensing, by a vehicle sensor, behavior of the vehicle as it travels over the plurality of road segments to provide a sensed result; and searching for one or more slip signatures in the sensing results by the vehicle.

308. The non-transitory computer-readable medium of claim 304 storing instructions for accumulating rain perception rate information obtained during a precipitation time window to generate the rain information.

309. The non-transitory computer-readable medium of claim 304, wherein the performance of the travel-related operation includes selectively activating an autonomous driving module for autonomously driving the vehicle.

310. The non-transitory computer-readable medium of claim 304, wherein the performance of the travel-related operation includes selectively deactivating an autonomous driving module configured to autonomously drive the vehicle when activated.

311. The non-transitory computer-readable medium of claim 304, wherein the performance of the travel-related operation includes setting a speed of the vehicle in each of the plurality of road segments.

312. The non-transitory computer-readable medium of claim 304 storing instructions for estimating a rain perception rate through at least one vehicle sensor.

313. The non-transitory computer readable medium of claim 312, wherein the at least one vehicle sensor belongs to a wiper control unit.

314. The non-transitory computer-readable medium of claim 304, wherein the performance of the travel-related operation includes alerting a human driver of the vehicle.

315. A vehicle system for driving a vehicle, the vehicle system comprising: a sensor configured to perform at least one of the following operations: (a) sensing a behavior of the vehicle, and (b) sensing a rain parameter; and a computer vehicle configured to receive or generate rain information about rain associated with a plurality of road segments; and estimating the occurrence of the one or more slip events in the plurality of road segments, wherein the estimation of the occurrence of one or more slip events is based on the rain information, on at least one rain related parameter of the vehicle, and on a mapping between the rain information and the occurrence of one or more slip events associated with each of the road segments.

316. The vehicle monitor of claim 315, wherein the vehicle computer is configured to assist in performing driving-related operations based on the estimation of the occurrence of the one or more slip events.

317. A method for measuring physical events associated with a plurality of road segments, the method comprising: measuring a first set of parameters by a first vehicle sensor; wherein the measuring occurs while the vehicle is traveling on the plurality of road segments; wherein the first set of parameters includes a wheel motion parameter and a vehicle acceleration parameter; wherein the first vehicle sensor is different from a road image sensor; detecting, by a vehicle computer, a detected physical event related to travel over the plurality of road segments, wherein the detecting is based on the first set of parameters; generating physical event information regarding the detected physical event; and storing or transmitting at least a portion of the physical event information; wherein the physical event comprises an occurrence of a slip event.

318. A non-transitory computer program product for measuring physical events related to a plurality of road segments, wherein the non-transitory computer program product stores instructions for: measuring a first set of parameters by a first vehicle sensor; wherein the measuring occurs while the vehicle is traveling on the plurality of road segments; wherein the first set of parameters includes a wheel motion parameter and a vehicle acceleration parameter; wherein the first vehicle sensor is different from a road image sensor; detecting, by a vehicle computer, a detected physical event related to travel over the plurality of road segments, wherein the detecting is based on the first set of parameters; generating physical event information regarding the detected physical event; and storing or transmitting at least a portion of the physical event information; wherein the physical event comprises an occurrence of a slip event.

319. A system for measuring physical events related to a plurality of road segments, the system comprising a vehicle computer configured to (i) receive a first set of parameters from a first vehicle sensor; wherein the measuring occurs while the vehicle is traveling on the plurality of road segments; wherein the first set of parameters includes a wheel motion parameter and a vehicle acceleration parameter; wherein the first vehicle sensor is different from a road image sensor; (ii) detecting a detected physical event related to the driving over the plurality of road segments, wherein the detecting is based on the first set of parameters; generating physical event information regarding the detected physical event; and storing or facilitating transmission of at least a portion of the physical event information; wherein the physical event comprises an occurrence of a slip event.

320. A method for generating a reference map of an area, the method comprising: receiving, from a plurality of vehicles through a communication interface, (a) physical event information about detected physical events detected by the plurality of vehicles while traveling on road segments belonging to the area, and (b) road segment attributes calculated by the plurality of vehicles, the road segment attributes relating to road segments belonging to the area; wherein the physical event information of a vehicle of the plurality of vehicles is based on a first set of parameters sensed by a first vehicle sensor of the vehicle; wherein the first set of parameters includes a wheel motion parameter and a vehicle acceleration parameter; wherein the first vehicle sensor is different from a road image sensor; and calculating, by a computerized system, the reference map based on the physical event information regarding detected physical events detected by the plurality of vehicles and the road segment attributes calculated by the plurality of vehicles; wherein the detected physical event comprises an occurrence of a slip event.

321. A non-transitory computer program product for generating a reference map of an area, the non-transitory computer program product storing instructions for: receiving, from a plurality of vehicles through a communication interface, (a) physical event information about detected physical events detected by the plurality of vehicles while traveling on road segments belonging to the area, and (b) road segment attributes calculated by the plurality of vehicles, the road segment attributes relating to road segments belonging to the area; wherein the physical event information of a vehicle of the plurality of vehicles is based on a first set of parameters sensed by a first vehicle sensor of the vehicle; wherein the first set of parameters includes a wheel motion parameter and a vehicle acceleration parameter; wherein the first vehicle sensor is different from a road image sensor; and calculating, by a computerized system, the reference map based on the physical event information regarding detected physical events detected by the plurality of vehicles and the road segment attributes calculated by the plurality of vehicles; wherein the detected physical event comprises an occurrence of a slip event.

322. A method for determining a travel period, the method comprising: receiving or generating, by the vehicle computer, a vehicle profile and a grade of a portion of the path ahead of the vehicle; wherein the vehicle profile is generated based on at least a road path and a vehicle parameter; wherein at least some of the road path and the vehicle parameters are sensed by a vehicle sensor different from a road image sensor; and determining, by the vehicle computer, suggested driving parameters for a path ahead of the vehicle, wherein the calculating is based at least in part on the vehicle profile, a path segment grade, an extrinsic limit, and information related to one or more slip events.

323. A non-transitory computer program product for determining a travel period, wherein the non-transitory computer program product stores instructions for: receiving or generating, by the vehicle computer, a vehicle profile and a grade of a portion of the path ahead of the vehicle; wherein the vehicle profile is generated based on at least a road path and a vehicle parameter; wherein at least some of the road path and the vehicle parameters are sensed by a vehicle sensor different from a road image sensor; and determining, by the vehicle computer, suggested driving parameters for a path ahead of the vehicle, wherein the calculating is based at least in part on the vehicle profile, a path segment grade, an extrinsic limit, and information related to one or more slip events.