Identifying Influencing Factors of Road Accidents in Emerging Road Accident Blackspots

Abstract

This study deals with identifying the accident blackspots and the influencing factors causing accidents using factored analysis in a medium-sized city (Tirunelveli) in India. From the literature review, the geospatial technique to identify the blackspots and the factors causing accidents was used for analysis. The most influencing factors driving the accidents were identified and ranked based on the repetitive occurrence of accidents in the blackspot area. The spearman ranking system showed the correlation among the factors causing accidents. The factor analysis technique was utilized to identify the key factors driving the repetitive accidents and group them. This study will help transportation planners understand the factors causing accidents and take appropriate measures to reduce the casualties in the road construction planning stage and existing conditions.

Eye-Tracking Analysis of Proposed Signage Design to Prevent Accidents Caused by the Abrupt Appearance of Dividers on Indian Roads

“…Around the world, traffic accidents are a serious problem. One of the main causes of road accidents is irresponsible driving, which is innately influenced by infrastructure and traffic conditions, among other things [4]. A study conducted by scholars, specifically for Pune city, stated that for better traffic management, installing suitable signs in accordance with IRC 67-2012 would be a good solution.…”

GIS-Based Spatial Analysis Model for Assessing Impact and Cumulative Risk in Road Traffic Accidents via Analytic Hierarchy Process (AHP)—Case Study: Romania

“…The use of geographic information system (GIS) in road accident analysis has developed extensively due to the ability to analyze large volumes of geospatial data and to determine spatial patterns in their occurrence, and the most common methods are: Fuzzy-AHP to determine significant determinants of road accidents [46,47]; accident characteristics analysis: location, user information, road type, vehicle, and crash severity using GIS [8,9,32,[48][49][50][51][52][53][54][55]; clustering techniques in GIS to determine hotspots and blackspots using kernel density, adjacent neighbor distance, and K functions [19,[56][57][58][59][60][61]; Getis and Moran's I-statistics [62]; and determining risk zones for vehicle crashes in GIS using neuro-fuzzy approaches [45].…”

Identification of hazardous road sites: a comparison of blackspot methodology of Narogong Road Bekasi and Johor Federal Roads

“…Passengers can potentially enhance the likelihood of a traffic accident by distracting drivers [20]. Pedestrian mistakes, such as crossing in front of automobiles, walking on the road, and crossing the road away from crosswalks and streets near the facility, causes traffic accidents [21].…”

“…Several studies have revealed vehicle characteristics that impact collision risk include poor maintenance and worn tyres [31] [32]. Common factors contributing to accidents involving public or school transport vehicles include distracted braking, insufficient illumination, excessive loading, and improper usage or alteration of vehicles [33]. Lack of safety equipment in vehicles increases the risk of severe injuries, severe disabilities, and fatalities [34][35].…”