Analysis of the influence of expressway emergencies on transmission speeds and travel delays

Abstract

Expressway emergencies tend to cause traffic congestion, and understanding the travel time delays of on-road vehicles under different combinations of event scenarios and road traffic conditions is valuable for guiding the accurate emer-gency dispatch services. Most existing studies used methods that combine the Lighthill–Whitham–Richards (LWR) theory and basic traffic diagrams to solve this problem, but the discrete traffic flow characteristics caused by the pres-ence of heavy vehicles have not been considered, thus affecting the applicability of those results to road traffic charac-teristics in China. Moreover, there is a lack of systematic research on multiple combinations of unexpected event sce-narios and traffic conditions, and the guidance value of the previously obtained results is limited. In order to improve the applicability of the prediction model and accurately predict the severity of emergencies, based on a logistic model that is applicable to emergencies, a velocity–density model is constructed to describe discrete traffic flow characteris-tics. Based on LWR theory, the internal driving force of expressway traffic state evolution under emergency conditions is explored. Combined with real-time traffic flow data, the parameters of the logistic model are calibrated, and a lo-gistic velocity–density model is constructed using a goodness-of-fit test and a marching method, including the free-flow velocity, turning density and heavy vehicle mixing ratio. Thus, the problem that existing models lack applicability to road traffic characteristics in China is solved. Travel time delay is associated with the impact range of an emergency, and it is an effective index for evaluating the severity of emergency incidents. Thus, the travel time delays under differ-ent scenarios, different numbers of blocked lanes and different orthogonal combinations of approximate saturation conditions are explored, and the impacts of lane blockage on emergency incidents and travel time delays are obtained. The conclusions show that the presented logistic velocity–density model constructed based on discrete traffic flow characteristics can properly quantify the impact of the presence of heavy vehicles. Additionally, the results can provide theoretical support for handling emergencies and emergency rescues.