New Model of Travel-Time Prediction Considering Weather Conditions: Case Study of Urban Expressway

Abstract

In the prediction problem of urban expressway travel time, in addition to the influence of traffic flow characteristics on travel time, the influence of various traffic environmental factors makes the change of traffic conditions with time uncertain, and the uncertainty and ambiguity in the transportation environment affect the travel-time prediction to varying degrees. This paper studied the influence of weather conditions on expressway travel-time prediction, focusing on the impacts of rain intensity and visibility. The southern section of Sanyuanli-Guangzhou Airport Expressway was selected as a case study to analyze characteristics of travel time under different weather conditions, to determine the change law of travel time and vehicle speed under different rainfall intensity and visibility, and to quantify the uncertainty and fuzziness factors through membership function and parameter weight. The mapping relationship between the influencing factors and travel time was obtained through decision rules, and a travel-time prediction model was established based on soft set theory. The experimental results showed that, compared with the Bureau of Public Roads (BPR) function model, the travel-time prediction model considering weather conditions reduces the prediction error and effectively improves the calculation accuracy.