Beijing University of Technology Reports Findings in Risk Management (Hotspot identification on urban arterials at the meso level): Risk Management

2022 MAR 28 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- New research on Risk Management is the subject of a report. According to news reporting originating in Beijing, People’s Republic of China, by NewsRx journalists, research stated, “Urban arterials form the main structure of city street networks, and typically have high traffic volume and high crash frequency. To reduce the number of crashes, hotspot identification (HSID) is the first step in the traffic safety management process, and often utilizes crash prediction models.”

Financial supporters for this research include Beijing Municipal Education Commission, International Science and Technology Cooperation Programme, National Natural Science Foundation of China, Ministry of Science and Technology of the People’s Republic of China.

The news reporters obtained a quote from the research from the Beijing University of Technology, “Classical crash prediction models investigate the relationship between roadway characteristics and traffic safety at the micro level, that is, they treat road segments and intersections as isolated units. Micro-level analysis has limitations, however, when examining urban arterial crashes: 1) signal spacing is typically short for urban arterials in dense street networks, and there are interactions between intersections and road segments that classical models do not accommodate; and 2) for practical engineering, a hotspot to which countermeasures are applied generally consists of several adjacent intersections and road segments instead of a single intersection or road segment. To address these concerns, signalized intersections and their adjacent road segments were combined into meso-level units, which were adopted to investigate traffic safety data from 21 urban arterials in Shanghai, China. To determine if the meso-level unit is the most suitable research unit for identifying hotspots on urban arterials, and if so, which HSID method can most consistently identify them, this study identified micro-level (separate intersection and road segment) and meso-level (combined intersection and road segment) hotspots using crash frequency, empirical Bayesian (EB), potential for safety improvement (PSI), and full Bayesian (FB) methods. To evaluate the performance of the HSID methods, hotspot consistency over two years was tested. The results showed 1) that EB and PSI performed better than the other methods no matter which research unit was used; 2) substantial inconsistency between the identified micro- and meso-level hotspots.”

According to the news reporters, the research concluded: “To identify both hazardous corridors and individual intersections and road segments on urban arterials, a combination of micro- and meso-level hotspots should be recommended to local transportation authorities.”

This research has been peer-reviewed.

For more information on this research see: Hotspot identification on urban arterials at the meso level. Accident Analysis & Prevention, 2022;169:106632. Accident Analysis & Prevention can be contacted at: Pergamon-elsevier Science Ltd, The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, England.

Our news correspondents report that additional information may be obtained by contacting Jia Li, Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, People’s Republic of China.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1016/j.aap.2022.106632. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.

The publisher of the journal Accident Analysis & Prevention can be contacted at: Pergamon-elsevier Science Ltd, The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, England.

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