Road Crash losses have been on an growing trend for the preceding decade or so in India. consequently traffic safety organization has emerged as a topic of argument for researchers all over the world. For this reason Crash modeling on different factors causing them has to be conducted. Crash modelling helps to anybody to recognize the real causative agents behind an accident to occur. The effect of one cause can be greater than the other. And those causes can only be known from Crash modelling. In this paper it is tried try to divide this Crash modelling techniques into different categories based on the road geometrics characteristics, traffic characteristics and Environmental factors on urban roads and on rural roads of different developed countries. In both urban and rural road crash studies it can be seen that for the most part regression techniques like linear, multi-linear, logit and poisons regression were used for modelling the road crashes. It was also noticeable that frequently authors have tried to research on one reason and go profound into it to a certain extent considering all factors at a time. From the study of different researches the attention was paid to the safety effects of road environment such as traffic flow, lane width, number of accesses, speed and road connectors. In this paper it is tried to review as much papers as possible and various gaps in research along with future possibility of study in this area has been indicated. Starting from the basic models like Simple/Multiple regression model to the logistic and linear regressions to the new modeling techniques involving Negative Binomial/Zero inflated modelling, genetic mining and fuzzy logics have been discussed in the paper.
| Published in | American Journal of Traffic and Transportation Engineering (Volume 2, Issue 2) |
| DOI | 10.11648/j.ajtte.20170202.11 |
| Page(s) | 10-25 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2017. Published by Science Publishing Group |
Road Crash, Traffic Flow, Geometric Characteristics, Regression Modelling, Road Safety
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APA Style
Bangaram Naga Kiran, Nekkanti Kumaraswamy, Chundupalli Sashidhar. (2017). A Review of Road Crash Prediction Models for Developed Countries. American Journal of Traffic and Transportation Engineering, 2(2), 10-25. https://doi.org/10.11648/j.ajtte.20170202.11
ACS Style
Bangaram Naga Kiran; Nekkanti Kumaraswamy; Chundupalli Sashidhar. A Review of Road Crash Prediction Models for Developed Countries. Am. J. Traffic Transp. Eng. 2017, 2(2), 10-25. doi: 10.11648/j.ajtte.20170202.11
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Download@article{10.11648/j.ajtte.20170202.11,
author = {Bangaram Naga Kiran and Nekkanti Kumaraswamy and Chundupalli Sashidhar},
title = {A Review of Road Crash Prediction Models for Developed Countries},
journal = {American Journal of Traffic and Transportation Engineering},
volume = {2},
number = {2},
pages = {10-25},
doi = {10.11648/j.ajtte.20170202.11},
url = {https://doi.org/10.11648/j.ajtte.20170202.11},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtte.20170202.11},
abstract = {Road Crash losses have been on an growing trend for the preceding decade or so in India. consequently traffic safety organization has emerged as a topic of argument for researchers all over the world. For this reason Crash modeling on different factors causing them has to be conducted. Crash modelling helps to anybody to recognize the real causative agents behind an accident to occur. The effect of one cause can be greater than the other. And those causes can only be known from Crash modelling. In this paper it is tried try to divide this Crash modelling techniques into different categories based on the road geometrics characteristics, traffic characteristics and Environmental factors on urban roads and on rural roads of different developed countries. In both urban and rural road crash studies it can be seen that for the most part regression techniques like linear, multi-linear, logit and poisons regression were used for modelling the road crashes. It was also noticeable that frequently authors have tried to research on one reason and go profound into it to a certain extent considering all factors at a time. From the study of different researches the attention was paid to the safety effects of road environment such as traffic flow, lane width, number of accesses, speed and road connectors. In this paper it is tried to review as much papers as possible and various gaps in research along with future possibility of study in this area has been indicated. Starting from the basic models like Simple/Multiple regression model to the logistic and linear regressions to the new modeling techniques involving Negative Binomial/Zero inflated modelling, genetic mining and fuzzy logics have been discussed in the paper.},
year = {2017}
}
TY - JOUR T1 - A Review of Road Crash Prediction Models for Developed Countries AU - Bangaram Naga Kiran AU - Nekkanti Kumaraswamy AU - Chundupalli Sashidhar Y1 - 2017/07/13 PY - 2017 N1 - https://doi.org/10.11648/j.ajtte.20170202.11 DO - 10.11648/j.ajtte.20170202.11 T2 - American Journal of Traffic and Transportation Engineering JF - American Journal of Traffic and Transportation Engineering JO - American Journal of Traffic and Transportation Engineering SP - 10 EP - 25 PB - Science Publishing Group SN - 2578-8604 UR - https://doi.org/10.11648/j.ajtte.20170202.11 AB - Road Crash losses have been on an growing trend for the preceding decade or so in India. consequently traffic safety organization has emerged as a topic of argument for researchers all over the world. For this reason Crash modeling on different factors causing them has to be conducted. Crash modelling helps to anybody to recognize the real causative agents behind an accident to occur. The effect of one cause can be greater than the other. And those causes can only be known from Crash modelling. In this paper it is tried try to divide this Crash modelling techniques into different categories based on the road geometrics characteristics, traffic characteristics and Environmental factors on urban roads and on rural roads of different developed countries. In both urban and rural road crash studies it can be seen that for the most part regression techniques like linear, multi-linear, logit and poisons regression were used for modelling the road crashes. It was also noticeable that frequently authors have tried to research on one reason and go profound into it to a certain extent considering all factors at a time. From the study of different researches the attention was paid to the safety effects of road environment such as traffic flow, lane width, number of accesses, speed and road connectors. In this paper it is tried to review as much papers as possible and various gaps in research along with future possibility of study in this area has been indicated. Starting from the basic models like Simple/Multiple regression model to the logistic and linear regressions to the new modeling techniques involving Negative Binomial/Zero inflated modelling, genetic mining and fuzzy logics have been discussed in the paper. VL - 2 IS - 2 ER -
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