Stochastic and Safe Multi-Risk Fusion for Autonomous Navigation in the Presence of PLEVs

Risk assessment and management in urban scenarios are difficult for automated vehicles due to perception uncertainties and the latent stochastic and high-dynamic behaviors of other agents e.g., Personal Light Electric Vehicles (PLEVs). Although the Predictive Inter-Distance Profile (PIDP) provides a continuous assessment of the risk between multiple agents, it fails when there are significant uncertainties in the estimated states of the agents. In this paper, we propose a Stochastic PIDP (sPIDP) to handle the uncertainties in the motion of the agents. sPIDP projects the uncertainties to the inter-distance between the agents. Furthermore, an Uncertainty-aware MPC is proposed to perform risk management. Statistical results considering multiple traffic scenarios show that our method is efficient for safe navigation.