Lateral Control of an Autonomous and Connected Following Vehicle With Limited Preview Information

Lateral control of an autonomous and connected vehicle (ACV), especially in emergency situations, is important from the safety viewpoint. In these situations, the trajectory to be followed by an ACV must either be planned in real-time (e.g., for a possible evasion maneuver if the obstacle to be avoided is detected) or be communicated from its preceding vehicle. Typically, the trajectory information is available to the following ACV in the form of GPS time samples. From the viewpoint of lateral control, the lateral velocity information is not readily available and the feedback structure must reflect this reality. In this paper, we develop a methodology to synthesize a lateral control algorithm for a following ACV in a two-vehicle platoon in two steps: 1) From the limited preview information of the trajectory to be tracked via samples of GPS way points, we estimate the radius of curvature of the trajectory using “least-square” estimation and 2) develop a fixed-structure feedback control scheme for following the predecessor by synthesizing the set of stabilizing gains corresponding to lateral position error, heading error and heading rate error. Numerical simulation and experimental results corroborate the effectiveness of the proposed schemes.

I. Introduction

Keeping the vehicle on a desired and safe trajectory is central to the lateral control task for autonomous vehicles. If the desired trajectory is the center of the lane, we refer to it in a narrow sense as lane-keeping; broadly, lane-keeping is concerned with keeping a vehicle between the lane boundaries. While the proposed lateral controller can also be used for lane keeping, the primary topic of interest in this paper is the lateral control of a following Autonomous and Connected Vehicle (ACV or simply a vehicle) in a two-vehicle platoon during an emergency lane change scenario. A cue for an emergency lane change can arise from the front as an evasive maneuver for obstacle avoidance or from the behind as a response to an approaching emergency vehicle such as an ambulance. In such an emergency scenario, lane change trajectory must be constructed in real-time by a vehicle as one of the responses for obstacle avoidance and this trajectory must be tracked closely. In a similar scenario, it is possible that there can be multiple vehicles following a leader and the lead vehicle constructs the trajectory in real-time as it has the best view of the obstacle and conveys the lane change trajectory information to its followers in real-time. We make the assumption that the obstacle avoidance maneuver is not an extreme maneuver where the limits of vehicle maneuverability are tested; this is reasonable because we assume that the lead vehicle has the best view or information from infrastructure about the obstacle and does not have to follow any vehicle ahead. Usually, the trajectory information of the lead vehicle may only provide limited preview for the following vehicle(s); controlling the lateral dynamics of a following ACV with such limited preview information is the focus of this paper.