Path Planning and Tracking for Vehicle Collision Avoidance in Lateral and Longitudinal Motion Directions

Description

In recent years, the control of Connected and Automated Vehicles (CAVs) has attracted strong attention for various automotive applications. One of the important features demanded of CAVs is collision avoidance, whether it is a stationary or a moving obstacle. Due to complex traffic conditions and various vehicle dynamics, the collision avoidance system should ensure that the vehicle can avoid collision with other vehicles or obstacles in longitudinal and lateral directions simultaneously. The longitudinal collision avoidance controller can avoid or mitigate vehicle collision accidents effectively via Forward Collision Warning (FCW), Brake Assist System (BAS), and Autonomous Emergency Braking (AEB), which has been commercially applied in many new vehicles launched by automobile enterprises. But in lateral motion direction, it is necessary to determine a flexible collision avoidance path in real time in case of detecting any obstacle. Then, a path-tracking algorithm is designed to assure that the vehicle will follow the predetermined path precisely, while guaranteeing certain comfort and vehicle stability over a wide range of velocities. In recent years, the rapid development of sensor, control, and communication technology has brought both possibilities and challenges to the improvement of vehicle collision avoidance capability, so collision avoidance system still needs to be further studied based on the emerging technologies. In this book, we provide a comprehensive overview of the current collision avoidance strategies for traditional vehicles and CAVs. First, the book introduces some emergency path planning methods that can be applied in global route design and local path generation situations which are the most common scenarios in driving. A comparison is made in the path-planning problem in both timing and performance between the conventional algorithms and emergency methods. In addition, this book introduces and designs an up-to-date path-planning method based on artificial potential field methods for collision avoidance, and verifies the effectiveness of this method in complex road environment. Next, in order to accurately track the predetermined path for collision avoidance, traditional control methods, humanlike control strategies, and intelligent approaches are discussed to solve the path-tracking problem and ensure the vehicle successfully avoids the collisions. In addition, this book designs and applies robust control to solve the path-tracking problem and verify its tracking effect in different scenarios. Finally, this book introduces the basic principles and test methods of AEB system for collision avoidance of a single vehicle. Meanwhile, by taking advantage of data sharing between vehicles based on V2X (vehicle-to-vehicle or vehicle-to-infrastructure) communication, pile-up accidents in longitudinal direction are effectively avoided through cooperative motion control of multiple vehicles. Contents Acknowledgments Introduction Background Collision Avoidance Systems for a Single Vehicle Cooperative Collision Avoidance Systems for Multiple-Vehicles Combined Lateral and Longitudinal Motion Control for Collision Avoidance Contributions of This Book Path-Planning Algorithms for Collision Avoidance Commonly Used Global Path-Planning Algorithms Trajectories Generation for a Local Path Planner Summary Path-Tracking Algorithms for Collision Avoidance PID Control Preview-Following Control Model Predictive Control Sliding Mode Control Fuzzy Logic Control Summary Optimal Local Trajectory for Vehicle Collision Avoidance Maneuvers Introduction Autonomous System Architecture Crash Mitigation Motion Planning Vehicle Dynamic Modeling Definition of the Potential Crash Severity Index (PCSI) Obstacle Description Controller Design for Motion Planning Case Study Evaluation of Collision Avoidance Mitigate Crash Severity Related to Crash Angle Summary Design of Robust Feedback Controller for Path Tracking Model-Based Control Algorithm for Path Tracking Automated Path Tracking Architecture Modeling Feedback Control Scheme Robust Controller Design Case Study Summary Collision Avoidance in Longitudinal Direction With/Without V2X Communication Introduction Effectiveness of FCW and AEB in Longitudinal Collision Avoidance Kinematic Approach Perceptual Approach AEB Test Scenarios, Procedures, and Simulations Multiple-Vehicle Collision Avoidance Using V2X Communication Communication Structures Spacing Policy String Stability Mathematical Model for Cooperative Collision Avoidance Numerical Simulations Summary Conclusions and Future Works Conclusions Future Works MATLAB Programs References Authors' Biographies