Abstract
<div class="section abstract"><div class="htmlview paragraph">The driving risk field model offers a feasible approach for assessing driving
risks and planning safe trajectory in complex traffic scenarios. However, the
conventional risk field fails to account for the vehicle size and acceleration,
results in the same trajectories are generated when facing different vehicle
types and unable to make safe decisions in emergency situations. Therefore, this
paper firstly introduces the acceleration and vehicle size of surrounding
vehicles for improving the driving risk model. Then, an integrated
decision-making and planning model is proposed based on the combination of the
novelty risk field and model predictive control (MPC), in which driving risk and
vehicle dynamics constraints are taken into consideration. Finally, the multiple
driving scenarios are designed and analyzed for validate the proposed model. The
results demonstrate that the proposed decision-making and planning method
exhibits superior performance in addressing discrepancies related to vehicle
acceleration and geometric. Besides, the improved driving risk field model is
able to effectively model the various driving behavior in complex traffic
scenarios, and has superior performance for reflecting the realistic driving
risk distribution.</div></div>