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Crash risk factor identification using association rules in Nagpur city, Maharashtra, India


Affiliations
1 Civil Engineering Department, Visvesvaraya National Institute of Technology, South Ambazari Road, Nagpur 440 010, India
 

The increase in traffic volume in urban road networks poses a significant challenge to transportation safety. It is evident that different traffic zones experience unique crash patterns and severities. The different factors that affect crash rates are caused by the various character-istics of the drivers, weather conditions, design of road-side infrastructure and driving behaviour. Although studies have shown that various factors can affect crash rates, there are insufficient studies on the exact catego-rization of these factors. Accordingly, the present study focuses on traffic crashes on streets where the risks of an accident occurrence are higher, using Nagpur city, Maharashtra, India as a case study. Three levels of risk zones were selected, i.e. zone-I (low risk), zone-II (medi-um risk) and zone-III (high risk). The risk zones are created in ArcGIS software using the kernel density esti-mator function. The association rule was then used to find out the various crash risk factors within the zone. The results of the study reveal that the risk of pedestrian fatalities is higher in areas where the speed limit is more than 40 km/h and day-to-day pedestrian activity is pre-sent. Based on the results, we propose a lower speed limit in zone-I, in addition to providing pedestrian-crossing fa-cilities such as zebra crossings or refuge islands for cross-walks. Moreover, we propose implementing an awareness campaign for road traffic safety aimed at educating road users on how to follow road discipline, especially with regard to utilizing pedestrian facilities, aggressive young motorcyclists, lane changing and overtaking mano-euvres.

Keywords

Association rules, driver characteristics, risk factors, traffic crash, urban roads.
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  • Crash risk factor identification using association rules in Nagpur city, Maharashtra, India

Abstract Views: 305  |  PDF Views: 148

Authors

Bahuguna Dalai
Civil Engineering Department, Visvesvaraya National Institute of Technology, South Ambazari Road, Nagpur 440 010, India
Vishrut S. Landge
Civil Engineering Department, Visvesvaraya National Institute of Technology, South Ambazari Road, Nagpur 440 010, India

Abstract


The increase in traffic volume in urban road networks poses a significant challenge to transportation safety. It is evident that different traffic zones experience unique crash patterns and severities. The different factors that affect crash rates are caused by the various character-istics of the drivers, weather conditions, design of road-side infrastructure and driving behaviour. Although studies have shown that various factors can affect crash rates, there are insufficient studies on the exact catego-rization of these factors. Accordingly, the present study focuses on traffic crashes on streets where the risks of an accident occurrence are higher, using Nagpur city, Maharashtra, India as a case study. Three levels of risk zones were selected, i.e. zone-I (low risk), zone-II (medi-um risk) and zone-III (high risk). The risk zones are created in ArcGIS software using the kernel density esti-mator function. The association rule was then used to find out the various crash risk factors within the zone. The results of the study reveal that the risk of pedestrian fatalities is higher in areas where the speed limit is more than 40 km/h and day-to-day pedestrian activity is pre-sent. Based on the results, we propose a lower speed limit in zone-I, in addition to providing pedestrian-crossing fa-cilities such as zebra crossings or refuge islands for cross-walks. Moreover, we propose implementing an awareness campaign for road traffic safety aimed at educating road users on how to follow road discipline, especially with regard to utilizing pedestrian facilities, aggressive young motorcyclists, lane changing and overtaking mano-euvres.

Keywords


Association rules, driver characteristics, risk factors, traffic crash, urban roads.

References





DOI: https://doi.org/10.18520/cs%2Fv123%2Fi6%2F781-790