阅读说明：本技术 不确定环境中的安全轨迹跟踪 (Secure trajectory tracking in uncertain environments ) 是由 伊沃·巴特科维奇 穆罕默德·阿利 马利奥·扎农 保罗·法尔科内 于 2020-09-14 设计创作，主要内容包括：本申请公开了不确定环境中的安全轨迹跟踪。本发明涉及一种用于车辆的轨迹规划的方法,包括：获得有限时间范围内的参考轨迹,参考轨迹包括有限时间范围内的随着时间的速度参考；确定有限时间范围内的备用停止轨迹,备用停止轨迹具有起始状态并在最终状态下终止,最终状态被限定为安全状态；基于至少一个预定约束形成有限时间范围内的结尾状态集,结尾状态集包括与备用停止轨迹的起始状态相对应的结尾状态；基于约束控制技术生成有限时间范围的至少一部分内的标称轨迹,标称轨迹取决于获得的参考轨迹和结尾约束,结尾约束限定标称轨迹包括结尾状态。约束控制技术包括成本最小化控制策略,并且从起始状态到最终状态的备用停止轨迹与零成本相关联。(The application discloses secure trajectory tracking in an uncertain environment. The invention relates to a method for trajectory planning of a vehicle, comprising: obtaining a reference trajectory over a limited time range, the reference trajectory comprising a speed reference over time over the limited time range; determining a backup stopping trajectory within a limited time range, the backup stopping trajectory having an initial state and terminating in a final state, the final state being defined as a safe state; forming an ending state set within a limited time range based on at least one predetermined constraint, the ending state set comprising ending states corresponding to starting states of the alternate stopping track; generating a nominal trajectory within at least a portion of the limited time range based on a constraint control technique, the nominal trajectory being dependent on the obtained reference trajectory and an ending constraint defining the nominal trajectory to include an ending state. The constraint control technique includes a cost minimization control strategy, and the alternate stop trajectory from the start state to the final state is associated with a zero cost.)

1. A method for trajectory planning for a vehicle, the method comprising:

obtaining a reference trajectory over a limited time range, the reference trajectory comprising a speed reference over time over the limited time range;

determining a backup stopping trajectory within the limited time range, the backup stopping trajectory having a starting state and terminating in a final state, the final state being defined as a safe state;

forming an ending state set within the limited time range based on at least one predetermined constraint, wherein the ending state set comprises ending states corresponding to the starting states of the alternate stopping tracks;

generating a nominal trajectory within at least a portion of the limited time range based on a constraint control technique, the nominal trajectory being dependent on the obtained reference trajectory and an ending constraint, wherein the ending constraint defines that the nominal trajectory includes the ending state; and is

Wherein the constraint control technique comprises a cost minimization control strategy, and wherein the alternate stopping trajectory from the starting state to the final state is associated with a zero cost.

2. The method of claim 1, wherein the alternate stopping track is associated with a zero cost of the generated nominal track as long as the corresponding ending state of the ending state set is included in the nominal track.

3. The method of claim 1, wherein the nominal trace ends with an ending state from the set of ending states.

4. The method of claim 1, wherein the constraint control technique controls the MPC framework based on model prediction.

5. The method of claim 1, wherein the limited time range includes a nominal time range defined as a first portion of the limited time range and a standby stop time range defined as a second portion of the limited time range, the first portion preceding the second portion; and is

Wherein the nominal track is included in the nominal time range and the alternate stop track is included in the alternate stop time range.

6. The method of claim 5, wherein the first portion is a first predetermined time period of the limited time range, and wherein the second portion is a second predetermined time period of the limited time range, the first and second predetermined time periods being equal to a total time of the limited time range.

7. The method of claim 1, wherein the final state is a state where a speed of the vehicle is zero.

8. The method of claim 1, wherein the at least one predetermined constraint comprises at least one of a road geometry of a surrounding of the vehicle, a maximum deceleration capacity of the vehicle, and weather data.

9. The method of claim 1, further comprising:

for a first time sample, sending a signal to control a speed of the vehicle based on the generated nominal trajectory; and

shifting the limited time range forward in time by one time sample; and

repeating the method according to any of the preceding claims, wherein the limited time range is replaced by the shifted limited time range.

10. The method of claim 1, further comprising:

obtaining a predicted trajectory of at least one dynamic object located in a surrounding environment of the vehicle, wherein the predicted trajectory is based on sensor data obtained by at least one sensor and a predetermined model; and is

Wherein the ending state set is formed further based on each predicted trajectory.

11. A computer readable storage medium storing one or more programs configured for execution by one or more processors of a vehicle control system, the one or more programs including instructions for performing a method for trajectory planning for a vehicle, the method comprising:

obtaining a reference trajectory over a limited time range, the reference trajectory comprising a speed reference over time over the limited time range;

determining a backup stopping trajectory within the limited time range, the backup stopping trajectory having a starting state and terminating in a final state, the final state being defined as a safe state;

forming an ending state set within the limited time range based on at least one predetermined constraint, wherein the ending state set comprises ending states corresponding to the starting states of the alternate stopping tracks;

generating a nominal trajectory within at least a portion of the limited time range based on a constraint control technique, the nominal trajectory being dependent on the obtained reference trajectory and an ending constraint, wherein the ending constraint defines that the nominal trajectory includes the ending state; and is

Wherein the constraint control technique comprises a cost minimization control strategy, and wherein the alternate stop trajectory from the start state to the end state is associated with a zero cost.

12. A control device for trajectory planning for a vehicle, the control device controlling a circuit configured to:

obtaining a reference trajectory over a limited time range, the reference trajectory comprising a speed reference over time over the limited time range;

determining a backup stopping trajectory within the limited time range, the backup stopping trajectory having a starting state and a final state, the final state being defined as a safe state;

forming an ending state set within the limited time range based on at least one predetermined constraint, wherein the ending state set comprises ending states corresponding to the starting states of the alternate stopping tracks;

generating a nominal trajectory within at least a portion of the limited time range based on a constraint control technique, the nominal trajectory being dependent on the obtained reference trajectory and an ending constraint, wherein the ending constraint defines that the nominal trajectory includes the ending state; and is

Wherein the constraint control technique comprises a cost minimization control strategy, and wherein the alternate stop trajectory from the start state to the end state is associated with a zero cost.

13. A vehicle comprising the control apparatus according to claim 12.

Technical Field

The present disclosure relates to Automated Driving (AD) and Advanced Driver Assistance Systems (ADAS). More particularly, the present disclosure relates to trajectory planning for vehicles within a drivable area.

Background

Today, many vehicles have a variety of driver support functions in the form of Advanced Driver Assistance Systems (ADAS). Moreover, many of these support functions form the basis for current and future Automatic Driving (AD) functions. Examples of ADAS features or functions include lane departure warning systems, lane centering, lane keeping assist, driver assist, lane change assist, parking sensors, pedestrian protection systems, blind spot monitors, Adaptive Cruise Control (ACC), anti-lock braking systems, and so forth. These functions supplement the conventional driver controls of the vehicle with one or more warnings or automatic actions in response to certain conditions.

Autonomous vehicles are rapidly evolving and often have impressive news and demonstrations of technological advances. However, one of the biggest challenges of AD is to ensure that the autonomous vehicle can plan and execute trajectories safely.

More specifically, in modern vehicles, the driver remains a critical component, as he is responsible for making many decisions regarding safe operation of the vehicle in terms of speed, steering, obstacle recognition and avoidance, etc. Therefore, to achieve the vision of fully automated operation in the automotive industry, new and improved systems relating to various aspects of automated driving are needed.

The present disclosure relates to the problem of planning a trajectory for an autonomous vehicle that is stable and above all safe not only for the occupants of the vehicle but also for people in the surroundings (pedestrians, other vehicles, cyclists, etc.).

Disclosure of Invention

It is therefore an object of the present disclosure to provide a method for trajectory planning for a vehicle, a computer-readable storage medium, a control device and a vehicle comprising the control device that alleviate all or at least part of the disadvantages of the currently known systems.

More specifically, it is an object of the present disclosure to provide a method for trajectory planning of a vehicle, which allows the vehicle to travel at higher speeds while still ensuring safety in an improved way compared to currently known solutions. Similarly, it is an object to provide a corresponding computer readable storage medium, control device and vehicle comprising the control device.

This object is achieved by a method for trajectory planning for a vehicle, a computer-readable storage medium, a control device and a vehicle comprising the control device as defined in the appended claims. In the present context, the term "exemplary" should be understood as serving as an example, instance, or illustration.

According to a first aspect of the present disclosure, a method for trajectory planning for a vehicle is provided. The method includes obtaining a reference trajectory over a limited time range, wherein the reference trajectory includes a speed reference over time over the limited time range. In addition, the method includes determining a backup stopping trajectory within a limited time frame. The alternate stop trajectory has a start state and terminates in a final state, wherein the final state is defined as a safe state. The method further includes forming an ending state set within a limited time range based on at least one predetermined constraint, wherein the ending state set includes an ending state corresponding to a starting state of the alternate stopping track. Further, the method includes generating a nominal trajectory within at least a portion of the limited time range based on a constraint control technique, wherein the nominal trajectory is dependent on the obtained reference trajectory and the ending constraint. The ending constraint defines that the nominal track includes an ending state. The constraint control technique includes a cost minimization control strategy, and the alternate stop trajectory from the start state to the final state is associated with a zero cost. The proposed method provides a trajectory planning solution that can achieve a good compromise between stability (being able to accurately track a reference) and safety (a limited time horizon always containing a backup stopping trajectory) based on constrained control techniques such as, for example, a Model Predictive Control (MPC) framework.

According to the proposed method, the backup stopping component is mainly used to ensure that the vehicle can reach a safe state (e.g. stop) within a limited time frame. Furthermore, by forming a set of ending states and forcing the nominal trajectory plan to always include ending states from the set, the costs associated with spare stopping trajectories can be mitigated. Without the ending state set, conventional MPC-based control strategies would sacrifice stability (i.e., deviate from the reference trajectory) because of the costs associated with the alternate stopping trajectory.

However, the inventors have realized that a trace (for the duration of a limited time range) may be considered "safe" if an ending constraint is set, i.e. a constraint that the generated nominal trace must include one of the states from the ending state set. The advantageous effect is then that the alternate stopping track does not need to incur any cost, so that the nominal part of the generated track is not affected and stability can be achieved. However, if we encounter a situation where we must start executing an alternate stop track, the end state set only starts containing states other than the "reference track," and since the generated track must include one state from the end set, there is a cost and the nominal track starts to deviate from the reference track (i.e., sacrifice stability for safety).

In the present context, a trajectory may be understood as a time-dependent path. Considering the one-dimensional (1D) case where our reference parameter is a speed parameter of the vehicle, the trajectory is then defined as the speed value (discrete or continuous) that the vehicle exhibits or will exhibit over a specified period of time.

The term "limited time range" is to be understood as a time range of a defined length, preferably a time range of a predetermined length (e.g. 5 seconds, 10 seconds, 15 seconds). In the case where the length of the limited time range is 10 seconds, the limited time range extends from the current time point (t ═ 0) to the end time (t ═ t)_end) Is then t_end10 seconds. The limited time range may also be referred to as a prediction range.

According to a second aspect of the present disclosure, there is provided a (non-transitory) computer readable storage medium storing one or more programs configured for execution by one or more processors of a vehicle control system, the one or more programs comprising instructions for performing a method according to any one of the embodiments disclosed herein. For this aspect of the disclosure, there are similar advantages and preferred features as the first aspect of the disclosure previously discussed.

As used herein, the term "non-transitory" is intended to describe a computer-readable storage medium (or "memory") that does not include a propagated electromagnetic signal, but is not intended to otherwise limit the type of physical computer-readable storage device that the term computer-readable medium or memory encompasses. For example, the terms "non-transitory computer readable medium" or "tangible memory" are intended to encompass types of storage devices that do not necessarily permanently store information, including, for example, Random Access Memory (RAM). Program instructions and data stored in a tangible computer accessible storage medium in a non-transitory form may further be transmitted by transmission media or signals such as electrical, electromagnetic, or digital signals, which may be transmitted over communication media such as a network and/or a wireless link. Thus, as used herein, the term "non-transitory" is a limitation on the media itself (i.e., tangible, not a signal), and not a limitation on the persistence of data storage (e.g., RAM and ROM).

According to a third aspect of the present disclosure, a control apparatus for trajectory planning of a vehicle is provided. The control device includes a control circuit configured to obtain a reference trajectory over a limited time range. The reference trajectory includes a speed reference over time within a limited time range. The control circuit is further configured to determine a backup stop trajectory within a limited time frame, wherein the backup stop trajectory has a start state and a final state. The final state is defined as the safe state. Further, the control circuit is configured to form an end state set within a limited time range based on at least one predetermined constraint. The end state set includes at least one end state corresponding to a start state of the alternate stop track. Still further, the control circuit is configured to generate the nominal trajectory within at least a portion of the limited time range based on a constraint control technique. The nominal trajectory depends on the obtained reference trajectory and the ending constraint. The ending constraint defines that the nominal track includes an ending state. Further, the constraint control technique includes a cost minimization control strategy, and wherein the alternate stop trajectory from the start state to the final state is associated with a zero cost. For this aspect of the disclosure, there are similar advantages and preferred features as the first aspect of the disclosure previously discussed.

Further embodiments of the disclosure are defined in the dependent claims. It should be emphasized that the term "comprises/comprising" when used in this specification is taken to specify the presence of stated features, integers, steps or components. It does not preclude the presence or addition of one or more other features, integers, steps, components or groups thereof.

These and other features and advantages of the present disclosure will be further elucidated below with reference to the embodiments described hereinafter.

Drawings

Other objects, features and advantages of embodiments of the present disclosure will become apparent from the following detailed description, with reference to the accompanying drawings, in which:

fig. 1 is a schematic flow chart illustration of a method for trajectory planning of a vehicle according to an embodiment of the present disclosure.

Fig. 2 shows two schematic diagrams illustrating an exemplary embodiment of a method for trajectory planning of a vehicle according to an embodiment of the present disclosure.

Fig. 3 shows a schematic diagram illustrating an exemplary embodiment of a method for trajectory planning of a vehicle according to an embodiment of the present disclosure.

Fig. 4 is a schematic side view of a vehicle having a control apparatus for lane-level map matching of the vehicle traveling on a road according to an embodiment of the present disclosure.

Detailed Description

Those skilled in the art will appreciate that the steps, services and functions described herein may be implemented using individual hardware circuits, using software functioning in conjunction with a programmed microprocessor or general purpose computer, using one or more Application Specific Integrated Circuits (ASICs) and/or using one or more Digital Signal Processors (DSPs). It will also be understood that when the present disclosure is described in terms of a method, it may also be embodied in one or more processors and one or more memories coupled to the one or more processors, where the one or more memories store one or more programs that, when executed by the one or more processors, perform the steps, services, and functions disclosed herein.

In the following description of the exemplary embodiments, the same reference numerals denote the same or similar components.

Fig. 1 shows a schematic flowchart representation of a method 100 for controlling advanced driver assistance features (ADAS) or Automated Driving (AD) features of a vehicle traveling on a road segment according to an example embodiment of the present disclosure. More specifically, method 100 provides trajectory tracking/generation features for autonomous or semi-autonomous vehicles (i.e., ADAS-equipped vehicles). In this context, vehicles are to be interpreted broadly and include cars, buses, trucks and construction vehicles.

Even though the present disclosure focuses on vehicles, and particularly on cars, the teachings herein are also applicable to other industries that utilize trajectory planning, such as, for example, robotics, avionics, and the like.

The method 100 comprises obtaining 101 a reference trajectory over a limited time range. The reference trajectory comprises at least a speed reference (v) over time in a limited time range_ref). Alternatively or additionally, the reference trajectory may include a positionReference (p)_ref) Yaw reference (Θ)_ref) Acceleration reference (a)_ref) And the like.

The position reference is preferably in the form of a set of x and y positions in the road surface. These alternative or additional parameters may be used, for example, to generate steering inputs for following the target path. The reference trajectory may be given based on the current traffic scenario (e.g., based on the geographic location of the vehicle and surrounding traffic), and may be predefined or may be dynamic based on sensor observations. Thus, the reference trajectory may be part of (local) "map data" and may be obtained, for example, from an external entity (which is part of the vehicle management system) via an external network (e.g., a cellular network).

The term limited time range is to be understood as a time range of a defined length, preferably a time range of a predetermined length (e.g. 5 seconds, 10 seconds, 15 seconds). In the case where the length of the limited time range is 10 seconds, the limited time range extends from the current time point (t ═ 0) to the end time (t ═ t)_end) Is then t_end10 seconds. The limited time range may also be referred to as a prediction range.

Further, the method 100 includes determining 102 one or more alternate stopping trajectories (which may also be referred to as safety stopping trajectories) within a limited time frame. The alternate stop track has a start state and terminates in a final state. The final state of each alternate stop trajectory is defined as the safe state. In one example embodiment of the present disclosure, the final state is a state in which the speed of the vehicle is zero. However, the method may also be used for other applications (e.g. robotics), in which case the safety state may e.g. be when a robot unit (e.g. a robot arm) reaches a predetermined position and/or configuration (e.g. a fully open handle). According to one embodiment, the backup stopping trajectory is in the maximum deceleration trajectory of the vehicle, i.e. the transition from the first vehicle speed to the standstill is made as fast as possible. The backup stopping trajectory can therefore be interpreted as an emergency stopping action, wherein the priority is to bring the vehicle to a standstill as quickly as possible, with reduced consideration of the comfort of the occupants.

Further, the method 100 comprises forming 103 a set of ending states (terminal sets of states) within a limited time range based on at least one predetermined constraint. The ending state set includes at least one ending state (terminal state) corresponding to a starting state of the alternate stopping track. The at least one predetermined constraint may for example be the road geometry of the surroundings of the vehicle, the maximum deceleration capacity of the vehicle or weather data.

In other words, vehicle dynamics, road conditions, and/or reference trajectory speed may be considered when forming the ending state set. In more detail, each state in the ending set must satisfy a condition that enables the final state (safe state, e.g., vehicle speed is zero) to be reached. Therefore, in order to ensure that this is possible, various vehicle characteristics may be considered, such as vehicle weight, braking capability, road conditions, and the like. These various characteristics define one or more constraints for forming the ending state set.

Next, nominal trajectories within at least a portion of the limited time range are generated 104 based on a constraint control technique. The constraint control technique may be based on a Model Predictive Control (MPC) framework. However, other techniques, such as referencing and commanding speed governors, may also be employed. The nominal trajectory depends on the obtained reference trajectory and an ending constraint, wherein the ending constraint defines that the control trajectory includes a state from an ending state set. Further, the constraint control technique includes a cost minimization control strategy, and wherein the alternate stopping trajectory from the ending state to the final state is associated with a zero cost.

In other words, the proposed method 100 provides a trajectory planning solution that ensures that there is always a "safe trajectory" (i.e., a standby stopping trajectory) within a limited time frame without sacrificing stability. In more detail, as long as we do not need to "follow" the alternate stop trajectory, the controller is "settling" (i.e., the nominal trajectory converges to the reference trajectory) because the alternate stop trajectory is not associated with any cost. By the term "need not follow the alternate stop trajectory" we understand that the alternate stop trajectory need not be initiated at a subsequent time sample (as will be further illustrated and explained with reference to fig. 2).

The advantage of the proposed method is then that a trajectory planning module can be implemented which achieves a good compromise between stability (being able to track the reference accurately) and safety (the limited time frame always includes the executable standby stopping trajectory, which is guaranteed by including the end state in the generated target trajectory (nominal trajectory)). In other solutions, in order to be able to ensure safety, a backup stop trajectory is included within a limited time frame. However, including the "alternate stopping trajectory" only for a limited time frame would force the trajectory planning module to deviate from the reference trajectory in these existing solutions. This is because the emergency braking action is associated with a high cost and since the cost minimization control strategy finds the best trajectory by minimizing the cost, it will sacrifice convergence to the reference trajectory to avoid exposure to the "emergency braking situation". Even if the alternate stop trajectory is not the maximum deceleration trajectory (emergency braking action), it still incurs costs and impairs the ability to stabilize against the high speed reference trajectory.

Furthermore, it may not be possible to secure an infinite time range, so a challenge contemplated in this disclosure is how to "secure" a finite time range without sacrificing stability (e.g., unreasonably slow driving).

The inventors have realized that the likelihood of being exposed to an "emergency braking" situation is relatively low and therefore we do not need a trajectory planning system that generates a target trajectory based on the assumption that there is an emergency stop in each planned range. Thus, by forming a set of ending states and ensuring that the nominal trajectory always includes one of these ending states, but since no cost is spent allocating a spare stopping trajectory, the trajectory planning module is allowed to focus on stabilizing the nominal trajectory relative to the reference trajectory, and still be able to ensure that the "safe state" can be reached within a limited time frame.

In other words, the method generates a nominal trajectory based on a constraint control strategy that only needs to include one of the end states in order to be able to (with high probability) claim that the generated trajectory is "safe" within a prediction horizon (a limited time horizon). Therefore, the alternate stop trajectory need not include any cost, since the end state is defined such that the vehicle can execute the alternate stop trajectory (and thus reach the safe state) as long as it can reach the end state. Thus, it can be said that the ending state set provides the necessary degrees of freedom to stabilize the nominal trajectory without sacrificing the security of the trajectory planning module.

Executable instructions for performing these functions are optionally included in a non-transitory computer-readable storage medium or other computer program product configured for execution by one or more processors.

Fig. 2 shows two schematic diagrams illustrating an exemplary embodiment of a method for trajectory planning of a vehicle traveling on a road segment. In more detail, the top graph shows the generated trajectory at time t-k, while the bottom graph shows the generated trajectory at the following time step t-k +3, i.e. three 25 sample times later. The diagram includes a velocity reference v indicated by the dashed line 21_refA reference track of the form. The sampling time is set according to the application and specifications and may be, for example, 1 millisecond, 10 milliseconds, or 100 milliseconds, corresponding to a sampling rate of 1000Hz, 100Hz, or 10Hz, respectively.

Thus, once the reference trajectory 21 is obtained within the limited time frame, at least one alternate stop trajectory within the limited time frame is determined. The alternate stop trajectory has a start state 22 and terminates in a final state 23, which is defined as a safe state (here, a state in which the speed of the vehicle is zero). In this context, a vehicle state in which the vehicle is not moving is considered "safe". This is because the parked vehicle is not responsible for being hit by other road users. We can compare with other technical areas, for example, a chemical reactor that is normally considered to be closed is safe, a circuit that is closed can be considered to be safe or a ship that is docked in a port can be considered to be safe.

Further, a trailing set of states 22 is formed within a limited time range based on at least one constraint. The end state set includes at least one end state 22 corresponding to the start state of the alternate stop track. The end state may be said to be formed based on a set of constraints or criteria (e.g., vehicle dynamics, road geometry, passenger comfort, etc.) to ensure that the safe state may be reached. The end state or states may then be the vehicle state or states (position, speed and azimuth) that the vehicle must assume if it is to reach a safe state according to the estimated trajectory. An alternative alternate stop trajectory is represented by the dashed line between the corresponding end state 22 and the final state 23. In the illustrated example, the selected end state corresponds to the start state of the alternate stop trajectory in the form of the maximum deceleration trajectory.

In more detail, the outer boundary of the end state set is the starting state of the maximum deceleration trajectory. Typically, this trajectory allows the highest speed of the starting state. In one exemplary embodiment, the alternate stop trajectory is a maximum deceleration trajectory (which may also be referred to as an emergency braking trajectory). Little or no consideration is given to passenger comfort for the alternate stop trajectory in the form of a maximum deceleration trajectory. By selecting the alternate stop trajectory in the form of the maximum deceleration trajectory, the nominal trajectory is most likely stable at the high reference speed.

Further, the constraint-based control technique generates a nominal trajectory (here, represented by a vehicle speed parameter) over at least a portion of the limited time range. The nominal trajectory depends at least on the obtained reference trajectory 21 and the ending constraint. The ending constraint defines that the nominal trajectory includes states 22 from an ending state set 24. As described above, the constraint control technique includes a cost minimization control strategy, and wherein the alternate stopping trajectory from a starting state (corresponding to an ending state) to a final state is associated with a zero cost. Naturally, the nominal trajectory may be further based on other constraints depending on the intended application and the specifications associated therewith. For example, various vehicle parameters may define additional constraints (maximum acceleration, turning radius, vehicle size, etc.), and further, user preferences may also indicate other constraints related to comfort (e.g., lateral acceleration, vertical acceleration, etc.).

Still further, the limited time range includes a nominal time range (defined as a first portion of the limited time range) and a standby stop time range (defined as a second portion of the limited time range). Preferably, the nominal track is included in a nominal time range and the alternate stop track is included in an alternate stop time range.

The ratio between the nominal time range and the backup stop range may be set based on user preferences and/or based on the current surroundings of the vehicle (e.g., highway cruising, rush hour traffic in densely populated areas, etc.). For example, if the limited time range is ten seconds (or any other suitable value depending on the performance of the vehicle's perception system), the nominal time range may be five seconds and the alternate stop time range may be five seconds, i.e., a ratio of 50/50. However, other ratios are possible, such as 60/40, 40/60, 70/30, 30/70, and so forth.

As described above, as long as there is a backup stopping trajectory considered in a limited time frame, improvement of the safety of the occupant can be achieved. Also, the controller (operating under the constraint control technique) is "stable" (e.g., allowing the vehicle to converge toward the reference speed) as long as we do not need to execute the alternate stop trajectory. Thus, during "normal" operation, the safe state 23 is set at the end of the finite time range during each sampling/updating/iteration of the trajectory plan. The bottom graph further illustrates this, where each update is simply moved forward in time by a limited time range. An important aspect to consider is that we have "planned" a backup stopping trajectory within a limited time frame, i.e. the vehicle can reach a safe state within a limited time frame. Thus, with the proposed method it is considered to be ensured that the vehicle can always reach a "safe state" within the planned range, and still maintain a good stability performance of the nominal trajectory planning.

However, if the vehicle sensors detect an unexpected obstacle (e.g., a pedestrian crossing the street) blocking the vehicle's target path, the safe state, and thus the alternate stopping trajectory, will propagate "inward" into the nominal time horizon, thereby beginning to incur the cost of generating the nominal trajectory. More specifically, the formation (or shape) of the ending state set will be affected, which in turn will affect the nominal trajectory. In that case, the nominal trajectory will begin to deviate from the reference trajectory 21 (e.g., the vehicle speed will be reduced) to account for the costs associated with the new ending state set 22. This is shown in fig. 3, fig. 3 showing a diagram illustrating a method for trajectory planning of a vehicle.

More specifically, the diagram of fig. 3 shows an example scenario or situation in which an obstacle is detected (e.g., by the perception system of the vehicle) in a subsequent time sample 25 continuing from the bottom diagram of fig. 2. The detection of an obstacle forces the trajectory planning module to plan to reach the standstill state 23 faster than the previous time sample 25 (bottom diagram of fig. 2). Thus, the alternate stop trajectory is adjusted and the ending state set 24 is updated accordingly. As a result, the vehicle cannot move from the reference speed (v)_ref) The safe state is reached at maximum deceleration and the end state 22 closest to the reference trajectory 21 differs from the reference trajectory 21 sufficiently for the trajectory planning module to sacrifice stability for safety when generating the nominal trajectory (indicated by the double arrow 26).

In other words, the ending state set 24 includes only states outside of the "reference track," and since the generated nominal track must include one state from the ending state set 24, a cost is incurred and the nominal track begins to deviate from the reference track 21 (i.e., stability is sacrificed for safety).

Further, in another exemplary embodiment, the method includes obtaining a predicted trajectory of at least one dynamic object (e.g., a pedestrian, a cyclist, another vehicle, etc.) located in a surrounding environment of the vehicle. For example, the predicted trajectory may be formed based on sensor data obtained from at least one sensor and a predetermined (motion) model. Then, an ending state set is formed further based on each predicted trajectory. The sensor data may originate from onboard sensors of the ego vehicle (e.g., radar, LIDAR, cameras, etc.), connected infrastructure devices (e.g., traffic lights, traffic cameras, toll collection systems, etc.), and/or other vehicles accessible through the vehicle-to-vehicle (V2V) solution. Thus, at each sample time, the current traffic conditions are considered when populating the end state set with end states. The illustrated examples of fig. 2 and 3 show the case where the nominal trajectory includes an ending state 22 corresponding to the alternate stopping trajectory in the form of a maximum deceleration, and those skilled in the art will readily appreciate that other ending states 22 within the set of ending states may be selected for inclusion in the nominal trajectory. Which ending state to include in the nominal track generation may be selected based on predetermined preferences and particular scenarios (user settings, environmental data, etc.). Furthermore, as shown in fig. 2 and 3, the "shape" of the end state set 24 is dynamic, and it can be said that the "shape" of the end state set 24 affects the "stability" of the nominal trajectory (i.e., the ability to accurately track the reference trajectory 21). Thus, the shape of the ending state set may be affected by external objects appearing or disappearing in the surroundings of the vehicle.

Fig. 4 is a schematic side view of a vehicle 1 comprising a control device 10 for controlling an Advanced Driver Assistance (ADAS) feature or an Automated Driving (AD) feature of the vehicle 1 travelling on a road section. The ADAS or AD feature may be, for example, a trajectory planning feature. The vehicle 1 further comprises a sensing system 6, an Inertial Measurement Unit (IMU)7 and a positioning system 5. In the present context, the perception system 6 is to be understood as a system responsible for acquiring raw sensor data from sensors 6a, 6b, 6c, such as cameras, LIDAR and RADAR, ultrasound sensors, and converting the raw data into a scene understanding. The positioning system 5 is configured to monitor the geographic position and orientation of the vehicle and may take the form of a Global Navigation Satellite System (GNSS), such as GPS. However, the positioning system may alternatively be implemented as a Real Time Kinematic (RTK) GPS to improve accuracy. The IMU 7 is understood to be an electronic device configured to measure inertial movements of the vehicle 1. The IMU 7 typically has six degrees of freedom, three accelerometers and three gyroscopes.

The control device 10 includes one or more processors 11, a memory 12, a sensor interface 13, and a communication interface 14. The processor 11 may also be referred to as control circuitry 11 or control circuitry 11. The control circuit 11 is configured to execute instructions stored in the memory 12 to perform a method for trajectory planning of a vehicle according to any of the embodiments disclosed herein. In other words, the memory 12 of the control device 10 may include one or more (non-transitory) computer-readable storage media for storing computer-executable instructions that, when executed by one or more computer processors 11, may, for example, cause the computer processors 11 to perform the techniques described herein. Optionally, memory 12 includes high speed random access memory, such as DRAM, SRAM, DDR RAM or other random access solid state memory devices; and, optionally, non-volatile memory, such as one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, or other non-volatile solid-state storage devices.

In more detail, the control circuit 11 is configured to obtain a reference trajectory over a limited time range, the reference trajectory comprising a speed reference over time over the limited time range. The reference trajectory may be obtained from the remote server 2, for example from the local memory unit 12 or via an external network accessible via the vehicle antenna 8. Furthermore, the control circuit 11 is configured to determine a standby stop trajectory within a limited time range. The alternate stop trajectory has a start state and a final state, the final state being defined herein as a safe state.

Next, the control circuit 11 is configured to form an end state set within a limited time range based on at least one predetermined constraint. The end state set includes at least one end state corresponding to a start state of the alternate stop track. Further, the control circuit 11 is configured to generate the nominal trajectory within at least a portion of the limited time range based on a constraint control technique (e.g., MPC). The nominal trajectory depends on the obtained reference trajectory and the ending constraint. The ending constraint defines that the nominal track includes an ending state. The constraint control technique includes a cost minimization control strategy, and the alternate stop trajectory from the start state to the final state is associated with a zero cost.

Further, the vehicle 1 may be connected to the external network 2 via, for example, a wireless link (e.g., for map data retrieval). The same or some other wireless link may be used to communicate with other vehicles in the vicinity of the vehicle or with local infrastructure elements. The cellular communication technology may be used for remote communication, e.g. to external networks, and if the used cellular communication technology has low latency, it may also be used for inter-vehicle, vehicle-to-vehicle (V2V) and/or vehicle-to-infrastructure V2X communication. Examples of cellular radio technologies are GSM, GPRS, EDGE, LTE, 5G NR, etc., also including future cellular solutions. However, in some solutions, short-range communication technologies are used, for example wireless Local Area Networks (LANs) such as IEEE 802.11 based solutions. ETSI is making cellular standards for vehicle communications and 5G is considered a suitable solution due to, for example, low latency and efficient handling of high bandwidth and communication channels.

The present disclosure has been presented above with reference to specific embodiments. However, other embodiments than the above described are possible and are within the scope of the present disclosure. Different method steps than those described above, performing the method by hardware or software, may be provided within the scope of the present disclosure. Thus, according to an exemplary embodiment, there is provided a non-transitory computer readable storage medium storing one or more programs configured for execution by one or more processors of a vehicle control system, the one or more programs including instructions for performing a method according to any of the above embodiments. Alternatively, according to another exemplary embodiment, the cloud computing system may be configured to perform any of the methods presented herein. The cloud computing system may comprise distributed cloud computing resources that collectively perform the methods presented herein under the control of one or more computer program products.

Generally speaking, a computer-accessible medium may include any tangible or non-transitory storage or memory medium such as an electronic, magnetic or optical medium, for example, a diskette or CD/DVD-ROM coupled to a computer system via a bus. As used herein, the terms "tangible" and "non-transitory" are intended to describe computer-readable storage media (or "memory") that does not include propagated electromagnetic signals, but are not intended to otherwise limit the type of physical computer-readable storage device that the term computer-readable media or memory encompasses. For example, the terms "non-transitory computer readable medium" or "tangible memory" are intended to encompass types of storage devices that do not necessarily permanently store information, including, for example, Random Access Memory (RAM). Program instructions and data stored in a tangible computer accessible storage medium in a non-transitory form may further be transmitted by transmission media or signals such as electrical, electromagnetic, or digital signals, which may be transmitted over communication media such as a network and/or a wireless link.

The processor 11 (associated with the control device 10) may be or include any number of hardware components for performing data or signal processing or for executing computer code stored in the memory 12. The device 10 has an associated memory 12, and the memory 12 may be one or more devices for storing data and/or computer code for performing or facilitating the various methods described in this specification. The memory may include volatile memory or nonvolatile memory. Memory 12 may include database components, object code components, script components, or any other type of information structure for supporting the various activities of the specification. According to exemplary embodiments, any distributed or local storage device may be used with the systems and methods of the present description. According to an exemplary embodiment, memory 12 is communicatively connected to processor 11 (e.g., via circuitry or any other wired, wireless, or network connection) and includes computer code for performing one or more of the processes described herein.

It should be understood that the sensor interface 13 may also provide the possibility to acquire sensor data directly or via dedicated sensor control circuitry 6 in the vehicle. The communication/antenna interface 14 may further provide the possibility to send the output to a remote location (e.g. a remote operator or a control center) by means of the antenna 5. Further, some sensors in the vehicle may communicate with the control device 10 using local network settings such as CAN bus, I2C, ethernet, fiber optics, and the like. The communication interface 14 may be arranged to communicate with other control functions of the vehicle and may therefore also be considered a control interface; however, a separate control interface (not shown) may be provided. The local communication within the vehicle may also be of a wireless type with a protocol such as WiFi, LoRa, Zigbee, bluetooth or similar medium/short range technologies.

It is therefore understood that parts of the described solution may be implemented in a vehicle, in a system provided outside the vehicle or in a combination of vehicle interior and exterior; for example, in a server in communication with the vehicle, a so-called cloud solution. For example, the sensor data may be sent to an external system, and the system proceeds to determine one or more alternate stopping trajectories and form an ending state set. The different features and steps of the embodiments may be combined in other combinations than those described.

It should be noted that the word "comprising" does not exclude the presence of other elements or steps than those listed and the word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. It should also be noted that any reference signs do not limit the scope of the claims, that the disclosure may be implemented at least in part by both hardware and software, and that several "means" or "units" may be represented by the same item of hardware.

Although the figures may show a particular order of method steps, the order of steps may differ from that depicted. In addition, two or more steps may be performed simultaneously or partially concurrently. Such variations will depend on the software and hardware systems chosen and on designer choice. All such variations are within the scope of the present disclosure. Likewise, software implementations could be accomplished with standard programming techniques with rule based logic and other logic to accomplish the various connection steps, processing steps, comparison steps and decision steps. The embodiments mentioned and described above are given by way of example only and should not limit the disclosure. Other solutions, uses, objects and functions within the scope of the disclosure as claimed in the above-described patent embodiments should be apparent to those skilled in the art.