Aggregate crash prediction model based on gravity model: Introducing crash risk distribution concept
Crash prediction models (CPMs) can be valuable for future transportation planning decisions. This study aims to develop CPMs based on the trip distribution step of the common four-step demand models. For this purpose, the Gravity Model is used. For model calibration, the frequency of severe crashes...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-03-01
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| Series: | Transportation Engineering |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666691X2400071X |
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| author | Saman Dabbaghfeizi Ali Naderan Ali Tavakoli-Kashani |
| author_facet | Saman Dabbaghfeizi Ali Naderan Ali Tavakoli-Kashani |
| author_sort | Saman Dabbaghfeizi |
| collection | DOAJ |
| description | Crash prediction models (CPMs) can be valuable for future transportation planning decisions. This study aims to develop CPMs based on the trip distribution step of the common four-step demand models. For this purpose, the Gravity Model is used. For model calibration, the frequency of severe crashes (including the total of fatal and injury crashes) between each origin-destination (OD) pair of traffic analysis zones (TAZs) in the city of Qom in Iran has been used as the dependent variable. The number of trip distributions by purpose, traffic characteristics on the links, and road network characteristics has been used as the explanatory variables. The model validation results show a significant relationship between the mentioned variables. Therefore, in addition to predicting the crash frequency according to trip number changes in the future, the developed model in this study determines the relationship between the crash frequency with the OD characteristics of the trips that lead to crashes. This makes it possible to evaluate the impact of different travel demand management scenarios on safety so that the crash risk (i.e., crash occurrence probability) of trips distributed between TAZs is identified and prioritized and can be planned to improve or reduced them. |
| format | Article |
| id | doaj-art-a57a182e66974ffb9f45199efe4139cf |
| institution | OA Journals |
| issn | 2666-691X |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Transportation Engineering |
| spelling | doaj-art-a57a182e66974ffb9f45199efe4139cf2025-08-20T02:34:53ZengElsevierTransportation Engineering2666-691X2025-03-011910029710.1016/j.treng.2024.100297Aggregate crash prediction model based on gravity model: Introducing crash risk distribution conceptSaman Dabbaghfeizi0Ali Naderan1Ali Tavakoli-Kashani2Department of Civil Engineering, Science and Research Branch, Islamic Azad University, Tehran, IranDepartment of Civil Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran; Corresponding author.Department of Civil Engineering, Iran University of Science and Technology, Tehran, IranCrash prediction models (CPMs) can be valuable for future transportation planning decisions. This study aims to develop CPMs based on the trip distribution step of the common four-step demand models. For this purpose, the Gravity Model is used. For model calibration, the frequency of severe crashes (including the total of fatal and injury crashes) between each origin-destination (OD) pair of traffic analysis zones (TAZs) in the city of Qom in Iran has been used as the dependent variable. The number of trip distributions by purpose, traffic characteristics on the links, and road network characteristics has been used as the explanatory variables. The model validation results show a significant relationship between the mentioned variables. Therefore, in addition to predicting the crash frequency according to trip number changes in the future, the developed model in this study determines the relationship between the crash frequency with the OD characteristics of the trips that lead to crashes. This makes it possible to evaluate the impact of different travel demand management scenarios on safety so that the crash risk (i.e., crash occurrence probability) of trips distributed between TAZs is identified and prioritized and can be planned to improve or reduced them.http://www.sciencedirect.com/science/article/pii/S2666691X2400071XAggregate crash prediction model (ACPM)Crash prediction model (CPM)Crash risk distribution (CRD)Gravity model (GM)Four-step demand model (FSDM) |
| spellingShingle | Saman Dabbaghfeizi Ali Naderan Ali Tavakoli-Kashani Aggregate crash prediction model based on gravity model: Introducing crash risk distribution concept Transportation Engineering Aggregate crash prediction model (ACPM) Crash prediction model (CPM) Crash risk distribution (CRD) Gravity model (GM) Four-step demand model (FSDM) |
| title | Aggregate crash prediction model based on gravity model: Introducing crash risk distribution concept |
| title_full | Aggregate crash prediction model based on gravity model: Introducing crash risk distribution concept |
| title_fullStr | Aggregate crash prediction model based on gravity model: Introducing crash risk distribution concept |
| title_full_unstemmed | Aggregate crash prediction model based on gravity model: Introducing crash risk distribution concept |
| title_short | Aggregate crash prediction model based on gravity model: Introducing crash risk distribution concept |
| title_sort | aggregate crash prediction model based on gravity model introducing crash risk distribution concept |
| topic | Aggregate crash prediction model (ACPM) Crash prediction model (CPM) Crash risk distribution (CRD) Gravity model (GM) Four-step demand model (FSDM) |
| url | http://www.sciencedirect.com/science/article/pii/S2666691X2400071X |
| work_keys_str_mv | AT samandabbaghfeizi aggregatecrashpredictionmodelbasedongravitymodelintroducingcrashriskdistributionconcept AT alinaderan aggregatecrashpredictionmodelbasedongravitymodelintroducingcrashriskdistributionconcept AT alitavakolikashani aggregatecrashpredictionmodelbasedongravitymodelintroducingcrashriskdistributionconcept |