Traffic Congestion Detection and Notification in the Urban Expressway System Using VANETs

Abstract

Cooperative vehicle-infrastructure technologies have made it possible for vehicles to collect and exchange real-time traffic information for the purpose of traffic guidance. However, traffic congestion detection using Vehicular Ad-hoc NETworks (VANETs) is inaccurate on urban expressways due to the complex road and traffic conditions. What’s more, the necessary control mechanism is lacking for the dissemination of congestion information. This study proposes an urban expressway congestion detection and notification method using VANETs. The method adopts the simplified Doppler frequency shift method to estimate and distinguish the degree of congestion along major and auxiliary roads. Human cognitive abilities are used to cooperatively amend the estimation and describe the overall situation of the congestion. The method also develops a spatial-temporal effectiveness model based on the field and potential energy theory to control the dissemination range and survival time of the congestion information, thus alleviating the vehicular network congestion. The proposed method ensures the accuracy and effectiveness of the congestion information and provides a reference for driver decision making and path planning.