Traffic Stability Under Provision of Real-Time En-Route Air Pollution Information

Abstract

Travel time information has been estimated and provided to drivers to help them make better routing decisions and alleviate congestion. However, because of challenges in data collection and sensor working principle, travel time information is often delayed and hence inaccurate. This inaccuracy can misguide motorists and result in unstable traffic patterns that exacerbate congestion. To alleviate this negative effect of travel time information on traffic flow, we explored the potential of providing drivers with real-time average en-route air pollution information (in addition to travel time). We developed a new queueing model that considers choice behavior of drivers provided with both travel time and air pollution information. Our model captures the impact of real-time air pollution information and the subsequent effects on traffic patterns. Results of our theoretical and numerical analysis indicate that provision of real-time air pollution information to travelers may help stabilize traffic. We further investigated how demand, choice behavior, emission and environmental parameters can affect such benefit, which provides a systematic understanding of why real-time air pollution information disclosure may help stabilize traffic and mitigate congestion.