An Autonomous T-Intersection Driving Strategy Considering Oncoming Vehicles Based on Connected Vehicle Technology

Autonomous driving strategies for intersection scenarios are challenging due to the varying traffic conditions of oncoming vehicles. Based on the connected vehicle technology, this article proposes an autonomous T-intersection driving strategy considering the oncoming vehicles for motion-planning and path following. A finite-state machine (FSM) is developed in the motion planner to decide the driving strategies considering the oncoming vehicles. Information pieces from the connected vehicle, specifically vehicle position and speed, are selected and effectively utilized to construct the temporal windows that manage the driving states transition of the FSM. Speed profiles in different driving states are modified for collision avoidance. Then, a path-following controller based on the back-stepping method is designed to track the planned path and speed simultaneously. The proposed strategy is validated by both simulation and experimental investigations. The results show the controlled vehicle can safely and quickly pass through the intersection using the proposed driving strategy that avoids possible collisions with the oncoming vehicles.

[1]  Georg Bretthauer,et al.  Invariant Trajectory Tracking With a Full-Size Autonomous Road Vehicle , 2010, IEEE Transactions on Robotics.

[2]  Guoyuan Wu,et al.  Platoon-based multi-agent intersection management for connected vehicle , 2013, 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013).

[3]  Sebastian Thrun,et al.  Path Planning for Autonomous Vehicles in Unknown Semi-structured Environments , 2010, Int. J. Robotics Res..

[4]  Thierry Fraichard,et al.  From Reeds and Shepp's to continuous-curvature paths , 1999, IEEE Transactions on Robotics.

[5]  Mark A. Minor,et al.  Backstepping vehicle steering controller using integral and robust control based on dynamic state estimation , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[6]  Yanjun Huang,et al.  Lane Keeping Control of Autonomous Vehicles With Prescribed Performance Considering the Rollover Prevention and Input Saturation , 2020, IEEE Transactions on Intelligent Transportation Systems.

[7]  Junmin Wang,et al.  Driver-Assistance Lateral Motion Control for In-Wheel-Motor-Driven Electric Ground Vehicles Subject to Small Torque Variation , 2018, IEEE Transactions on Vehicular Technology.

[8]  Junmin Wang,et al.  Robust Vehicle Driver Assistance Control for Handover Scenarios Considering Driving Performances , 2021, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[9]  Igor Skrjanc,et al.  Time optimal path planning considering acceleration limits , 2003, Robotics Auton. Syst..

[10]  Urbano Nunes,et al.  Trajectory Planning with Velocity Planner for Fully-Automated Passenger Vehicles , 2006, 2006 IEEE Intelligent Transportation Systems Conference.

[11]  Jonathan P. How,et al.  Real-Time Motion Planning With Applications to Autonomous Urban Driving , 2009, IEEE Transactions on Control Systems Technology.

[12]  Fumio Miyazaki,et al.  A stable tracking control method for an autonomous mobile robot , 1990, Proceedings., IEEE International Conference on Robotics and Automation.

[13]  Hong Chen,et al.  Simultaneous Trajectory Planning and Tracking Using an MPC Method for Cyber-Physical Systems: A Case Study of Obstacle Avoidance for an Intelligent Vehicle , 2018, IEEE Transactions on Industrial Informatics.

[14]  Byungkyu Brian Park,et al.  Development and Evaluation of a Cooperative Vehicle Intersection Control Algorithm Under the Connected Vehicles Environment , 2012, IEEE Transactions on Intelligent Transportation Systems.

[15]  Munther A. Dahleh,et al.  Maneuver-based motion planning for nonlinear systems with symmetries , 2005, IEEE Transactions on Robotics.

[16]  Jonas Sjöberg,et al.  Autonomous cooperative driving: A velocity-based negotiation approach for intersection crossing , 2013, 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013).

[17]  Vicente Milanés Montero,et al.  Controller for Urban Intersections Based on Wireless Communications and Fuzzy Logic , 2010, IEEE Transactions on Intelligent Transportation Systems.

[18]  Christos G. Cassandras,et al.  Optimal control and coordination of connected and automated vehicles at urban traffic intersections , 2015, 2016 American Control Conference (ACC).

[19]  Xiaohui Li,et al.  Real-Time Trajectory Planning for Autonomous Urban Driving: Framework, Algorithms, and Verifications , 2016, IEEE/ASME Transactions on Mechatronics.

[20]  João P. Hespanha,et al.  Trajectory-Tracking and Path-Following of Underactuated Autonomous Vehicles With Parametric Modeling Uncertainty , 2007, IEEE Transactions on Automatic Control.

[21]  Jihua Huang,et al.  A Low-Order DGPS-Based Vehicle Positioning System Under Urban Environment , 2006, IEEE/ASME Transactions on Mechatronics.

[22]  Wisama Khalil,et al.  Trajectory Planning of Unicycle Mobile Robots With a Trapezoidal-Velocity Constraint , 2010, IEEE Transactions on Robotics.

[23]  Henk Wymeersch,et al.  Traffic Coordination at Road Intersections: Autonomous Decision-Making Algorithms Using Model-Based Heuristics , 2017, IEEE Intelligent Transportation Systems Magazine.

[24]  S. Ilgin Guler,et al.  Using connected vehicle technology to improve the efficiency of intersections , 2014 .