Integration of Traffic Information into the Path Planning among Moving Obstacles

Abstract

This paper investigates the integration of traffic information (TI) into the routing in the presence of moving obstacles. When traffic accidents occur, the incidents could generate different kinds of hazards (e.g., toxic plumes), which make certain parts of the road network inaccessible. On the other hand, the first responders, who are responsible for management of the traffic incidents, need to be fast and safely guided to the incident place. To support navigation in the traffic network affected by moving obstacles, in this paper, we provide a spatio-temporal data model to structure the information of traffic conditions that is essential for the routing, and present an extended path planning algorithm, named MOAAstar-TI (Moving Obstacle Avoiding A* using Traffic Information), to generate routes avoiding the obstacles. A speed adjustment factor is introduced in the developed routing algorithm, allowing integration of both the information of vehicles and traffic situations to generate routes avoiding the moving obstacles caused by the incidents. We applied our system to a set of navigation scenarios. The application results show the potentials of our system in future application in real life.

A Social Media Based Approach for Route Planning During Urban Events

“…But the vehicle speed is largely dependent on traffic conditions and could change over time. One of the possible ways to address this is to include a speed adjustment factor into the routing algorithm [26]. Last but not least, in this paper the occurrence probability of the events is used for drivers to select the roads they prefer.…”