Hotspot Identification for Shanghai Expressways Using the Quantitative Risk Assessment Method
- A new HSID method is developed based on the QRA technique. The occurrence of crashes is treated as the risk, and the probability and consequences of this risk are respectively modeled. While the crash occurrence probability for all passing vehicles is expressed by the expected crash frequency at each segment, the consequences refer to the total social losses (i.e., direct losses and indirect losses) of crashes. Thus, the high-risk sites are identified, where not only many crashes occur, but also the traffic operation is heavily influenced by crashes.
- A classical Empirical Bayes (EB) method is used to calculate the expected crash frequency for each site. Since observed frequency and prediction of the frequency of crashes are both considered in EB, the Bayesian negative binomial model is introduced as the crash prediction model (CPM).
- Total social losses are used as the consequences of crashes. That is to say, the direct occupant injuries and property losses and the additional delay losses caused by a crash are both considered. The two parts of losses are quantitatively monetized. While the direct losses are estimated based on the crash type, additional delay losses are calculated using the queue theory.
2. Literature Review
3. Study Area and Data Collection
3.1. Study Area
3.2. Traffic Flow Data
3.3. Crash Data
Crash Risk Assessment Model
5. Case Study
6. Results and Analysis
- The use of the QRA method enables the identification of a set of high-risk sites that reveal the potential total crash costs to society. The case study results show that the rankings of hotspots are different between the conventional EB method and the new QRA method.
- In the QRA framework for the probability of crashes, in order to take full account of the uncertainty existing between roadway characteristics and crashes, EB combined with the Bayesian negative binomial model is used to calculate the expected number of crashes. It is shown that the classical EB is applicable and provides a robust result for the probability of crashes.
- In the QRA framework, for the consequences of crashes, the equivalent monetary index is applied to unify the direct and indirect losses. Indirect losses of crashes are quantitatively estimated by using the queue theory. The traffic situation when crashes happen and the crash type are sampled using Monte Carlo sampling.
Conflicts of Interest
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Chen, C.; Li, T.; Sun, J.; Chen, F. Hotspot Identification for Shanghai Expressways Using the Quantitative Risk Assessment Method. Int. J. Environ. Res. Public Health 2017, 14, 20. https://doi.org/10.3390/ijerph14010020
Chen C, Li T, Sun J, Chen F. Hotspot Identification for Shanghai Expressways Using the Quantitative Risk Assessment Method. International Journal of Environmental Research and Public Health. 2017; 14(1):20. https://doi.org/10.3390/ijerph14010020Chicago/Turabian Style
Chen, Can, Tienan Li, Jian Sun, and Feng Chen. 2017. "Hotspot Identification for Shanghai Expressways Using the Quantitative Risk Assessment Method" International Journal of Environmental Research and Public Health 14, no. 1: 20. https://doi.org/10.3390/ijerph14010020