Trajectory planning with miscellaneous safety critical zones

Highly automated vehicles have the potential to provide a variety of benefits e.g., decreasing traffic injuries and fatalities by offering people the freedom to choose how to spend their time in their vehicle without jeopardizing the safety of themselves or other traffic participants. Since smooth and safe trajectory planning is essential for successfully commercialization of automated vehicles, this paper presents a low-complexity trajectory planning algorithm in the Model Predictive Control (MPC) framework. In particular, the proposed algorithm accounts for safety critical zones of miscellaneous shape defined by both the planned longitudinal and lateral motion of the automated vehicle. The automated vehicle is thereby able to efficiently utilize the free road space and traverse dense traffic situation in a self-assertive manner rather than exhibit an excessively conservative behavior. The proposed algorithm is thereby considered to be a building block for Advanced Driver Assistance Systems (ADAS) and eventually highly automated vehicles which are safe, smooth, and self-assertive