Dynamic highway congestion detection and prediction based on shock waves

  • Authors:
  • Dijiang Huang;Swaroop Shere;Soyoung Ahn

  • Affiliations:
  • Arizona State University, Tempe, AZ, USA;Arizona State University, Tempe, AZ, USA;Arizona State University, Tempe, AZ, USA

  • Venue:
  • Proceedings of the seventh ACM international workshop on VehiculAr InterNETworking
  • Year:
  • 2010

Quantified Score

Hi-index 0.00

Visualization

Abstract

Existing highway traffic monitoring system requires to deploy a large number of sensors and video cameras to detect traffic congestions, which is costly and prone to errors and failures [1]. In this paper, we present a distributed traffic detection and prediction solution by using shock wave traffic model. We develop a Hello protocol to maintain the vehicle sequence on the same lane. Based on the measurements of velocity and distance between immediate leading and following vehicles, a vehicle can detect and compute shock wave velocity incurred by vehicle merges or obstacles on the highway. When velocity changes occur continuously, congestions will be formed, which can be detected and predicted by the vehicles through a shock wave detection procedure. Our solution is effective since we only require vehicles to communicate with its neighboring vehicles within its wireless communication range.