Safe Autonomous Overtaking with Intention Estimation
This paper investigates the problem of overtaking a lead car by an autonomous ego car on a two-lane road in the presence of an oncoming car. We propose an intention-aware overtaking controller for the ego car. The intention of the lead car is estimated via a combination of active model discrimination and model selection algorithms. Then, a safe overtaking controller is designed based on vector fields that take into account the estimated intent, and ensure safety of the overtaking maneuver. Simulation results demonstrate the efficacy of the proposed approach.
Automatic auxiliary supervision equipment was launched for Highway patrol tasks in Taiwan in 2015. This study uses filming instead of taking photos of damages on the road at night. In addition, virtual detection points were set to identify the location of a patrol vehicle between being on a viaduct or ground. More importantly, the data of damage types was analyzed further for road management and maintenance.