FIELD

The disclosure relates to a trajectory determination method adapted for a self-driving vehicle, and more particularly to a method for estimating a best driving path based on current driving environment.

BACKGROUND

In recent years, research and development related to self-driving has been flourishing, and most of the relatively more mature and commercially viable self-driving systems on the market today operate according to fixed routes in enclosed areas. However, the driving situations or settings are more complicated on the general road environment, which may have mixed flows of pedestrians and vehicles, including various motor vehicles (e.g., cars, trucks, buses and motorcycles) and bikes, etc.

In order to make the use of self-driving vehicles practically and deeply applicable to the general road environment, many manufacturers have started to develop technologies related to the dynamic trajectory of self-driving vehicles. The ability to determine the path enables the self-driving vehicle to make decisions that more closely resembles normal driving behavior of human drivers when it encounters environmental obstacles; for example, the self-driving vehicle may overtake the vehicle in front or dodge obstacles in the same lane. This ability affects the safety of the self-driving vehicle and its ability to deal with complex situations.

However, the conventional self-driving vehicles do not have a defined logic in the way that it decides on its driving behavior based on the current driving environment, which leads to high uncertainty. As an example, when there is a slow vehicle in the front, actions that can be taken by such a conventional self-driving vehicle may include following the slow car, braking hard, overtaking the slow car, etc. However, without a defined logic, developers or inspectors cannot confirm whether the self-driving vehicle behaves normally, and cannot make judgement on the actions taken by the self-driving vehicle when an accident occurs. In addition, the conventional self-driving vehicles make decisions based on only the current environment, and are unable to deal with changes in the environment that may interfere with the planned path, such as incoming pedestrians, moving cars, etc., so this also raises safety concerns.

SUMMARY

Therefore, an object of the disclosure is to provide a trajectory determination method for a vehicle. The trajectory determination method plans a trajectory for the vehicle by taking into consideration intended trajectory of an obstacle, thereby enhancing the safety of the planned trajectory.

According to the disclosure, the trajectory determination method is implemented by a processing module that is electrically connected to a trajectory generation module, an obstacle detection module, a lane space detection module, and a road information module. The trajectory generation module generates a plurality of trajectory data pieces. Each of the trajectory data pieces includes multiple trajectory points that cooperatively compose a candidate vehicle trajectory for the vehicle to follow during a vehicle travelling time period, and multiple proposed vehicle velocities of the vehicle respectively at the trajectory points. The obstacle detection module detects obstacles that are spaced apart and within a predetermined distance from the vehicle to generate obstacle data pieces that are respectively related to the obstacles. Each of the obstacle data pieces includes an obstacle location, an obstacle velocity and an obstacle acceleration of the corresponding one of the obstacles. The lane space detection module detects a pair of lateral distances respectively for two sides of the vehicle, wherein each of the lateral distances is a distance between the vehicle and one of the obstacles that is at the respective side of the vehicle and that is spaced apart from the vehicle laterally. The road information module provides a speed limit of a road on which the vehicle is travelling. The trajectory determination method includes: A) for each of the trajectory data pieces, acquiring a block flag, multiple TTC (time to collision) values and multiple time gap values based on the obstacle data pieces and the proposed vehicle velocities at the trajectory points of the trajectory data piece, wherein the block flag indicates whether the obstacles include a front obstacle in the candidate vehicle trajectory of the trajectory data piece, wherein each of the TTC values corresponds to a respective one of the trajectory points and indicates a length of time after which the vehicle at the trajectory point will collide with the front obstacle and wherein each of the time gap values corresponds to a respective one of the trajectory points and indicates a time difference between passages of the vehicle at the trajectory point and the front obstacle through the obstacle location of the front obstacle; B) for each of the trajectory data pieces, acquiring an intersection flag and multiple PTTC (prediction time to collision) values based on the obstacle data pieces and the proposed vehicle velocities at the trajectory points of the trajectory data piece, wherein the intersection flag indicates whether the obstacles include a potentially-colliding obstacle with a predicted obstacle path that intersects the candidate vehicle trajectory of the trajectory data piece, and wherein each of the PTTC values corresponds to a respective one of the trajectory points and indicates a possible length of time after which the potentially-colliding obstacle will collide with the vehicle; C) for each of the trajectory data pieces, acquiring a buffer distance for each of the trajectory points of the trajectory data piece based on the lateral distances detected by lane space detection module; D) for each of the trajectory data pieces, acquiring a lane-change flag that indicates whether the candidate vehicle trajectory of the trajectory data piece will cause a lane change for the vehicle; E) for each of the trajectory data pieces, acquiring a safety flag based on the obstacle data pieces and the vehicle travelling time period, wherein the safety flag indicates whether the lane change is safe; and F) based on the speed limit, the block flag, the intersection flag, the lane-change flag, the safety flag, the TTC values, the time gap values, the PTTC values and the buffer distance that are acquired for each of the trajectory data pieces, determining a target trajectory data piece from among the trajectory data pieces for the vehicle to drive along the candidate vehicle trajectory of the target trajectory data piece.

