Comprehensive Approach for Trajectory Optimization of Autopilot Vehicles Considering Handling Stability

LAN Fengchong, LI Shicheng, CHEN Jiqing, LIU Zhaolin


Automated driving vehicles have problems in local trajectory planning, such as insufficient consideration of vehicle handling stability, excessive simplification of vehicle models, and lack of objective evaluation of vehicle comfort. Considering the stability of vehicle handling, a three-degree-of-freedom model of vehicle is established. The lane changing scene of the self-driving car is simulated. The lane-changing trajectory is output by inputting the wheel angle,and the parameterization equation and driving trajectory characteristics of the vehicle are calculated. The BP neural network is used to identify the trajectory characteristics, and the change relationship between the lane change duration and lateral offset distance of the autonomous driving vehicle is obtained. At different lane changing speeds, according to different lane changing durations and lateral offset distances, the input wheel angles are used to obtain the lane change optimized by the trajectory clusters and steering stability parameters. Based on the conventional trajectory optimization method that only considers the driving efficiency and safety, the trajectory optimization objective function is constructed, by using the value of the yaw, roll, and lateral acceleration rate of the vehicle lane change process. A comprehensive trajectory optimization method based on driving efficiency, safety, comfort and steering stability is proposed. The trajectory optimization objective function is solved to obtain the optimal lane change trajectory. The joint simulation results show that the method is superior to the conventional trajectory optimization method, and the comfort and steering stability are improved by more than 20%.



Keywords:  automatic driving,  neural networks,  handling stability,  trajectory optimization

Full Text:



GLASER S, VANHOLME B, MAMMAR S, et al. Maneuver-based trajec - tory planning for highly autonomous vehicles on real road with traffic and driver interaction [J]. IEEE Transactions on Intelligent Transportation Systems, 2010, 11 (3): 589—606.

CHEN B C, LUAN B C, LEE K. Design of lane keeping system using adaptive model predictive control [C] // 2014 IEEE International Conference on Automation Science and Engineering (CASE) . New York: IEEE, 2014:922—926.

HUANG C, NAGHDY F, DU H. Model predictive control -based Vehicle Power and Propulsion Conference.Chicago: IEEE, 2011: 1—8. lane change control system for an autonomous vehicle [C] //IEEE Region 10 Conference. Tenco: IEEE, 2016:3349—3354.

SUN H , DENG W W, ZHANG S M , et al. Micro vehicle dynamic trajectory plan with global optimality [J]. Journal of Jilin University (Engineering and Technology Edition), 2014, 44 (4) :918—924. (In Chinese)

PEI Y L, WANG Y G, ZHANG Y. Microscopic model of automobile lane -changing virtual desire trajectory by spline curves[J]. Promet-Traffic and Transportation, 2010, 22 (3) :203—208.

GOMEZ -BRAVO F, CUESTA F, OLLERO A, et al. Continuous curvature path generation based on B -spline curves for parking manoeuvres [J]. Robotics and Autonomous Systems, 2008, 56 (4): 360—372.

COELINGH E, EIDEHALL A, BENGTSSON M. Collision warning with full auto brake and pedestrian detection a practical example of automatic emergency braking [C] //The 13th Int IEEE Conf on Intelligent Transportation Systems (ITSC) . Funchal: IEEE, 2010:155—160.

SOUDBAKHSH D, ESKANDARIAN A, CHICHKA D. Vehicle collision avoidance maneuvers with limited lateral acceleration using optimal trajectory control [J]. Journal of Dynamic Systems, Measurement, and Control, 2013, 135 (4) :1—12.

FU X X, JIANG Y H, HUANG D X, et al. A novel realtime trajectory planning algorithm for intelligent vehicles [J]. Control and Decision, 2015, 30 (10) :1751—1758.(In Chinese)

DIB W, SERRAO L, SCIARRETTA A. Optimal control to minimize trip time and energy consumption in electric vehicles [C] //IEEE Vehicle Power and Propulsion Conference.Chicago: IEEE, 2011:1—8.

ZHANG S M, DENG W W, ZHAO Q R, et al. Dynamic trajectory planning for vehicle autonomous driving [C] //Proceedings of the 2013 IEEE International Conference on Systems, Man, and Cybernetics. Washington DC:IEEE Computer Society, 2013: 4161—4166.

JULA H, KOSMATOPOULOS E B, IOANNOU P A. Collision avoidance analysis for lane changing and merging [J]. IEEE Transactions on Vehicular Technology, 2000, 49 (6): 2295—2308.


  • There are currently no refbacks.