阅读说明：本技术 全息交叉口信号控制自主优化方法 (Holographic intersection signal control autonomous optimization method ) 是由 张晖 杨雯博 慕佳作 刘益欣 陈博通 王宣 于 2021-07-21 设计创作，主要内容包括：本发明公开了全息交叉口信号控制自主优化方法,包括以下步骤：S1、通过搭建仿真模型以及布置的全息感知设备获取路网信息,路网信息包括交叉口类型及车道数量；S2、搭建VISSIM仿真场景,构建VISSIMCOM二次开发平台,根据所述路网信息输出车辆轨迹图和相关交通数据；S3、根据所述车辆轨迹图和相关交通数据,利用交通波理论对相位配时进行优化；S4、将相位配时优化前后的延误时长进行对比,得到延误时长优化值。本发明减少了交叉口的行车延误和交通事故。(The invention discloses an autonomous optimization method for holographic intersection signal control, which comprises the following steps: s1, obtaining road network information by building a simulation model and arranging holographic sensing equipment, wherein the road network information comprises intersection types and lane number; s2, building a VISSIM simulation scene, building a VISSICOM secondary development platform, and outputting a vehicle trajectory graph and related traffic data according to the road network information; s3, optimizing phase timing by using a traffic wave theory according to the vehicle trajectory diagram and the related traffic data; and S4, comparing the delay time before and after the phase timing optimization to obtain an optimized value of the delay time. The invention reduces the traffic delay and traffic accidents at the intersection.)

1. The holographic intersection signal control autonomous optimization method is characterized by comprising the following steps: the method comprises the following steps:

s1, obtaining road network information by building a simulation model and arranging holographic sensing equipment, wherein the road network information comprises intersection types and lane number;

s2, building a VISSIM simulation scene, building a VISSICOM secondary development platform, and outputting a vehicle trajectory graph and related traffic data according to the road network information;

s3, optimizing phase timing by using a traffic wave theory according to the vehicle trajectory diagram and the related traffic data;

and S4, comparing the delay time before and after the phase timing optimization to obtain an optimized value of the delay time.

2. The holographic intersection signal control autonomous optimization method of claim 1, characterized in that: s2 the VISSIMCOM secondary development platform is constructed by COM interface and Java programming.

3. The holographic intersection signal control autonomous optimization method of claim 1, characterized in that: s2, the related traffic data comprises vehicle speed, position, number, vehicle queue length on each lane, traffic jam density of each lane, saturated headway and average acceleration of vehicles passing through the intersection.

4. The holographic intersection signal control autonomous optimization method of claim 1, characterized in that: s3, the optimizing the phase timing of the traffic signal specifically includes: and distributing green time to the traffic signal phase of the intersection in real time by using a traffic wave theory according to the related traffic data.

5. The holographic intersection signal control autonomous optimization method of claim 1 or 4, characterized in that: the starting wave in the traffic wave theory is as follows: when the phase at the intersection obtains the right of way, the density of the phase traffic is changed, so that a starting wave is generated, and the propagation speed formula is as follows:

in the formula u_wThe negative value of the unit m/s represents that the propagation direction is from the intersection to the upstream intersection for starting the wave speed; h is the saturated headway time, unit s/veh, and is obtained by track data statistics; k is a radical of_jThe density of traffic jams is given in units of veh/km, u being the maximum speed of the vehicle passing through the intersection.

6. The holographic intersection signal control autonomous optimization method of claim 1, characterized in that: the phase timing optimization specifically comprises:

in order to ensure that all vehicles waiting in line pass through the intersection, the calculation formula of the phase green light is as follows:

in the formula, T_jIs the j phase green time; t is_vThe time it takes for the vehicle at the end of the queue to pass the stop line from start-up; t is_mFor phase duration correction parameters, take T_m＝5s；

Wherein T is_vThe calculation is shown in the following formula:

wherein a is the acceleration, l_m＝u²A/2 a, representing the distance travelled by the vehicle for uniform acceleration to maximum speed;

in order to prevent the situation where the green time is too long or too short, the green phase is given a limit on the minimum green time and the maximum green time.

7. A computer device, characterized by: comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor when executing the computer program implementing the steps of the holographic intersection signalization autonomous optimization method according to any of claims 1 to 6.

8. A computer-readable storage medium characterized by: stored thereon a computer program which, when being executed by a processor, carries out the steps of the holographic intersection signalization autonomous optimization method according to any one of claims 1 to 6.

9. The holographic intersection signal control autonomous optimization system for realizing the holographic intersection signal control autonomous optimization method of claims 1-4 is characterized in that: the system comprises:

the data acquisition module comprises holographic sensing equipment and is used for building a simulation model and acquiring road network information according to the holographic sensing equipment, wherein the road network information comprises intersection types and lane number;

the secondary development platform simulation module is used for building a VISSIM simulation scene, building a VISSICOM secondary development platform and outputting a vehicle trajectory graph and related traffic data according to the road network information;

the phase timing optimization module is used for optimizing phase timing by utilizing a traffic wave theory according to the vehicle trajectory diagram and the related traffic data;

and the delay judgment module is used for comparing the delay time before and after the phase timing optimization to obtain an optimized value of the delay time.

Technical Field

The invention relates to the field of intelligent traffic intersection signal control, in particular to a holographic intersection signal control autonomous optimization method.

Background

The intersections are the most important nodes in the urban road network, are the places where traffic flows converge, turn and shunt, and are the key points of the flexibility of the road network. The intersection signal control is an effective means for solving the problems of serious urban intersection congestion, multiple traffic accidents, unreasonable distribution of space-time resources for passing, disordered traffic order, serious pedestrian and vehicle mixing and the like. Because the traditional traffic signal control at present has the problems of incomplete traffic information acquisition, untimely traffic state perception, unintelligent control strategy selection, non-interactive traffic control signals and the like, although researchers at home and abroad are dedicated to reasonably improving the intersection signal control algorithm for a long time, the improved algorithm is limited by the complexity and randomness of a traffic system, is often lack of instantaneity and accuracy and cannot be practically verified and popularized.

Disclosure of Invention

The invention aims to provide an autonomous optimization method for signal control of a holographic intersection so as to solve traffic jam at the intersection.

In order to solve the technical problem, the invention provides a technical scheme that: the holographic intersection signal control autonomous optimization method comprises the following steps:

s1, obtaining road network information by building a simulation model and arranging holographic sensing equipment, wherein the road network information comprises intersection types and lane number;

s2, building a VISSIM simulation scene, building a VISSICOM secondary development platform, and outputting a vehicle trajectory graph and related traffic data according to the road network information;

s3, optimizing phase timing by using a traffic wave theory according to the vehicle trajectory diagram and the related traffic data;

and S4, comparing the delay time before and after the phase timing optimization to obtain an optimized value of the delay time.

According to the scheme, the VISSIMCOM secondary development platform is constructed through a COM interface and Java programming at S2.

According to the scheme, the related traffic data of S2 comprises vehicle speed, position, number, vehicle queue length on each lane, traffic jam density of each lane, saturated headway and average acceleration of vehicles passing through the intersection.

According to the above scheme, the optimizing the phase timing of the traffic signal in S3 specifically includes: and distributing green time to the traffic signal phase of the intersection in real time by using a traffic wave theory according to the related traffic data.

According to the scheme, the starting wave in the traffic wave theory is as follows: when the phase at the intersection obtains the right of way, the density of the phase traffic is changed, so that a starting wave is generated, and the propagation speed formula is as follows:

in the formula u_wThe negative value of the unit m/s represents that the propagation direction is from the intersection to the upstream intersection for starting the wave speed; h is the saturated headway time, unit s/veh, and is obtained by track data statistics; k is a radical of_jThe density of traffic jams is given in units of veh/km, u being the maximum speed of the vehicle passing through the intersection.

According to the scheme, the phase timing optimization specifically comprises the following steps:

in order to ensure that all vehicles waiting in line pass through the intersection, the calculation formula of the phase green light is as follows:

in the formula, T_jIs the j phase green time; t is_vThe time it takes for the vehicle at the end of the queue to pass the stop line from start-up; t is_mFor phase duration correction parameters, take T_m＝5s；

Wherein T is_vThe calculation is shown in the following formula:

wherein a is the acceleration, l_m＝u²A/2 a, representing the distance travelled by the vehicle for uniform acceleration to maximum speed;

in order to prevent the situation where the green time is too long or too short, the green phase is given a limit on the minimum green time and the maximum green time.

A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor when executing the computer program implementing the steps of the holographic intersection signalization autonomous optimization method according to any of the preceding claims.

A computer-readable storage medium characterized by: stored thereon, a computer program which, when executed by a processor, carries out the steps of the holographic intersection signalization autonomous optimization method according to any one of the preceding claims.

The holographic intersection signal control autonomous optimization system for implementing the holographic intersection signal control autonomous optimization method comprises the following steps:

the data acquisition module comprises holographic sensing equipment and is used for building a simulation model and acquiring road network information according to the holographic sensing equipment, wherein the road network information comprises intersection types and lane number;

the secondary development platform simulation module is used for building a VISSIM simulation scene, building a VISSICOM secondary development platform and outputting a vehicle trajectory graph and related traffic data according to the road network information;

the phase timing optimization module is used for optimizing phase timing by utilizing a traffic wave theory according to the vehicle trajectory diagram and the related traffic data;

and the delay judgment module is used for comparing the delay time before and after the phase timing optimization to obtain an optimized value of the delay time.

The invention has the beneficial effects that: road network information is acquired by building a simulation model and arranging holographic sensing equipment, a VISSCOM secondary development platform is built, a vehicle track map and related traffic data are output according to the road network information, and phase timing is optimized, so that driving delay and traffic accidents at the intersection are reduced.

Drawings

FIG. 1 is a flow chart of a method implementation of one embodiment of the present invention;

FIG. 2 is a schematic diagram of intersection simulation modeling in accordance with an embodiment of the present invention;

FIG. 3 is a schematic structural diagram of a VISSIMICM secondary development platform according to an embodiment of the present invention;

fig. 4 is a flowchart of an intersection signal control autonomous optimization method according to an embodiment of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present disclosure more apparent, the technical solutions of the embodiments of the present disclosure will be described clearly and completely with reference to the drawings of the embodiments of the present disclosure. It is to be understood that the described embodiments are only a few embodiments of the present disclosure, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the described embodiments of the disclosure without any inventive step, are within the scope of protection of the disclosure.

In the embodiment, intersections between south roads and military roads in Wuhan city are selected as optimization objects.

Referring to fig. 1, the holographic intersection signal control autonomous optimization method includes the following steps:

s1, obtaining road network information by building a simulation model and arranging holographic sensing equipment, wherein the road network information comprises intersection types and lane number;

s2, referring to FIG. 2, building a VISSIM simulation scene, building a VISSIM COM secondary development platform, and outputting a vehicle trajectory graph and related traffic data according to the road network information;

s3, referring to fig. 3, optimizing phase timing by using a traffic wave theory according to the vehicle trajectory diagram and the related traffic data;

and S4, comparing the delay time before and after the phase timing optimization to obtain an optimized value of the delay time.

Further, referring to fig. 3, the VISSIMCOM secondary development platform described in S2 is constructed by COM interface and Java programming.

Further, the relevant traffic data of S2 includes vehicle speed, position, number, vehicle queue length on each lane, traffic jam density of each lane, saturated headway, and average acceleration of the vehicle passing through the intersection.

Further, referring to fig. 4, the optimizing the phase timing of the traffic signal in S3 specifically includes: according to the related traffic data, the traffic wave theory is utilized to distribute green time to the traffic signal phase of the intersection in real time; the traffic wave theory is based on the basic principle of fluid mechanics, establishes a continuous equation of traffic flow by simulating the continuity of fluid, and simulates the density change of the traffic flow into the fluctuation of water waves so as to abstract the fluctuation into the traffic waves, and the traffic waves are as follows:

when the phase at the intersection obtains the right of way, the density of the phase traffic is changed, and therefore the starting wave is generated. According to the traffic wave theory, the length of the queue of the intersection is divided into two steps to pass through the intersection: when the green light phase is started, the starting wave propagates upstream at a certain speed; and secondly, accelerating the vehicle receiving the starting wave to pass through the intersection. In traffic wave theory, the propagation velocity formula of the launch wave is shown as follows:

in the formula u_wThe negative value of the unit m/s represents that the propagation direction is from the intersection to the upstream intersection for starting the wave speed; h is the saturated headway time, unit s/veh, and is obtained by track data statistics; k is a radical of_jThe density of traffic flow blockage is shown in a unit of veh/km, and u is the maximum speed of a vehicle passing through the intersection;

in order to ensure that all vehicles waiting in line pass through the intersection, the calculation formula of the phase green light is as follows:

in the formula, T_jIs the j phase green time; t is_vThe time it takes for the vehicle at the end of the queue to pass the stop line from start-up; t is_mFor phase duration correction parameters, take T_m＝5s；

Wherein T is_vThe calculation is shown in the following formula:

wherein a is the acceleration, l_m＝u²A/2 a, representing the distance travelled by the vehicle for uniform acceleration to maximum speed;

in order to prevent the situation where the green time is too long or too short, the green phase is given a limit on the minimum green time and the maximum green time.

The holographic intersection signal control autonomous optimization system for implementing the holographic intersection signal control autonomous optimization method comprises the following steps:

the data acquisition module comprises holographic sensing equipment and is used for building a simulation model and acquiring road network information according to the holographic sensing equipment, wherein the road network information comprises intersection types and lane number;

the secondary development platform simulation module is used for building a VISSIM simulation scene, building a VISSICOM secondary development platform and outputting a vehicle trajectory graph and related traffic data according to the road network information;

the phase timing optimization module is used for optimizing phase timing by utilizing a traffic wave theory according to the vehicle trajectory diagram and the related traffic data;

and the delay judgment module is used for comparing the delay time before and after the phase timing optimization to obtain an optimized value of the delay time.

The above description is only an embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.