Longitudinal and Lateral Control for Automated Yielding Maneuvers
Artikel i vetenskaplig tidskrift, 2016
Automated driving is predicted to enhance traffic safety, transport efficiency, and driver comfort. To extend the capability of current advanced driver assistance systems, and eventually realize fully automated driving, the intelligent vehicle system must have the ability to plan different maneuvers while adapting to the surrounding traffic environment. This paper presents an algorithm for longitudinal and lateral trajectory planning for automated driving maneuvers where the vehicle does not have right of way, i.e., yielding maneuvers. Such maneuvers include, e.g., lane change, roundabout entry, and intersection crossing. In the proposed approach, the traffic environment which the vehicle must traverse is incorporated as constraints on its longitudinal and lateral positions. The trajectory planning problem can thereby be formulated as two loosely coupled low-complexity model predictive control problems for longitudinal and lateral motion. Simulation results demonstrate the ability of the proposed trajectory planning algorithm to generate smooth collision-free maneuvers which are appropriate for various traffic situations.
model predictive control
Advanced driver assistance systems