| ORIGINAL ARTICLE |
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| Year : 2020 | Volume
: 9
| Issue : 1 | Page : 16-23 |
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Development of safety improvement method in city zones based on road network characteristics
Nemat Soltani1, Mahmoud Saffarzadeh2, Ali Naderan3, Milad Abolhasani4
1 Department of Road Safety and Intelligent Transportation System, Tarahan Parseh Transportation Research Institute, Tehran, Iran
2 Department of Civil and Environmental Engineering, Tarbiat Modares University, Tehran, Iran
3 Department of Civil Engineering, Islamic Azad University, Tehran Science and Research Branch, Tehran, Iran
4 Graduate Student of Carleton University, Ottawa, Canada
Correspondence Address:
Prof. Mahmoud Saffarzadeh
Room 405, Department of Civil and Environmental Engineering, Tarbiat Modares University, Tehran
Iran
 Source of Support: None, Conflict of Interest: None
DOI: 10.4103/atr.atr_44_19
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Background and Objective: Extensive studies have so far been carried out on developing safety models. Despite the extensive efforts made in identifying independent variables and methods for developing models, little research has been carried out in providing amendatory solutions for enhancing the level of safety. Thus, the present study first developed separate accident frequency prediction models by transportation modes, and then in the second phase, a development of safety improvement method (DSIM) was proposed. Materials and Methods: To this end, the data related to 14,903 accidents in 96 traffic analysis zones in Tehran, Iran, were collected. To evaluate the effect of intra-zone correlation, a multilevel model and a negative binomial (NB) model were developed based on both micro- and macro-level independent variables. Next, the DSIM was provided, aiming at causing the least change in the area under study and with attention to the defined constraints and ideal gas molecular movement algorithm. Results: Based on a comparison of the goodness-of-fit measures for the multilevel model with those of the NB model, the multilevel models showed a better performance in explaining the factors affecting accidents. This is due to considering the multilevel structure of the data in such models. The final results were obtained after 200 iterations of the optimization algorithm. Thus, to decrease accidents by 30% and cause the least change in the area under study, the independent variable of “vehicle kilometer traveled per road segment” underwent a considerable change, while little change was observed for the other variables. Conclusions: The final results of the DSIM showed that the ultimate solutions derived from this method can be different from the final solutions derived from the analysis of the results from the safety models. Hence, it is necessary to develop new methods to propose solutions for increasing safety.
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