Abstract
To effectively evaluate the traffic safety risk of urban expressways in real time and ensure their traffic safety and smoothness, a real-time evaluation method of vehicle conflict risk of an urban expressway based on smartphone GPS data was proposed. We screened and processed smartphone GPS data to obtain vehicle behavior data, including acceleration and angular acceleration, and road state data, including average vehicle speed. Urban expressways were divided into four categories, closed straight section, closed curve section, vehicle entry section, and vehicle exit section; the evaluation indexes of abnormal vehicle behavior were established. Based on the improved entropy weight method, the vehicle conflict risk entropy was established to distribute the weight of different types of abnormal behaviors of vehicles. The evaluation system of vehicle conflict risk entropy was applied to the vehicle behavior data. Urban Expressways with more abnormal vehicle behavior were obtained to evaluate the risk of vehicle conflict in real time. The results showed that the easily obtained smartphone GPS data may be effectively used to analyze the abnormal behavior of vehicles, identify vehicle conflict risk points hidden in urban expressways in real time to provide effective methods for batch and dynamic real-time evaluations of vehicle conflict risks on urban expressways, and improve the traffic safety service level of urban expressways.
Highlights
With the recent emergence of mega cities and urban agglomerations, countries have actively adopted the construction of urban expressways to alleviate urban road traffic congestion and improve urban road traffic service levels [1, 2]
To meet the travel needs of residents as much as possible in the planning and design of urban expressways, the road characteristics of large numbers of imports and exports, small spacing, and complex road networks, which further lead to rapid changes in vehicle speed and a high frequency of vehicle lane changes that result in vehicle conflict risk and road traffic accidents, must be considered
According to a statistical report on road traffic accidents in China in 2017, there were an average of 554 road traffic accidents on urban expressways every month, which resulted in nearly 140 deaths and 572 injuries [4]. erefore, real-time vehicle conflict risk assessments on urban expressways and real-time corresponding traffic control on sections with excessive vehicle conflict risk would effectively improve the traffic service level of urban expressways
Summary
With the recent emergence of mega cities and urban agglomerations, countries have actively adopted the construction of urban expressways to alleviate urban road traffic congestion and improve urban road traffic service levels [1, 2]. (1) Data-driven: Based on the large number of vehicle collision data and road traffic accident data collected, based on improved neural network or Logit model, or via the computer processing of video images, the risk prediction of vehicle conflict may be realized. Hossain and Muromachi [9] evaluated the traffic safety of ramp vehicles on urban expressways based on a random polynomial logit model, and the prediction of vehicle collision was realized based on the Bayesian belief network model. E comprehensive evaluation method combined with various factors could not achieve real-time and accurate evaluations, and it tended to overconsider the impact of environment on vehicle conflict without considering the specific motion state of vehicles, which resulted in a low accuracy rate. We analyzed the impact of the dangerous movement state of vehicles in different sections of urban expressways on vehicle conflict and divided the urban expressway to establish a vehicle conflict risk entropy evaluation model and realize the real-time evaluation of vehicle conflict risk on urban expressways
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