Vehicle path generation and tracking in mixed road traffic

Given the condition of mixed road traffic, few models exist that can predict the motion of a vehicle in it. Mixed road traffic can be defined as being both, lane indisciplined and heterogeneous. This study aims at developing a model that can analyze a given traffic condition, generate a safe trajectory and provide a control input to the vehicle to follow it. The paper explains the flow of the model, starting with traffic interaction, leader detection, and waypoint derivation. Post this, the trajectory is generated, the tracking errors are discussed and a controller is designed to navigate the trajectory by minimizing the discussed errors. Since the assumption of low speed is made, a kinematic model is used when generating feasibility criteria for the trajectory. Once the trajectory is determined to be feasible, a closed-loop Proportional Integral Derivative (PID) controller provides steering input to the vehicle to follow the trajectory. The controller tuning is performed using a dynamic bicycle model considering the error with respect to the trajectory. The trajectory generation model and the controller for trajectory following are implemented in independent simulator environments. The resulting output is a collision-free trajectory as followed by the subject vehicle (SV) to meet the generated waypoints which are based on the traffic scenario.