RESUMEN
A road network aims to facilitate the movement of commuters and goods in a safe, economical, and efficient way that contributes to growth in the economy. Road traffic incidents (RTIs), such as crashes, vehicle breakdowns, hazards, etc., are unexpected events that cause severe traffic congestion, unreliability, and pollution. The existing open-source RTI databases provide information on only a single type of incident, i.e., crashes that too focusing on the fatal ones. Other incidents, such as vehicle breakdowns, are underreported to the transport authorities as they are less severe than road traffic crashes. However, traffic congestion induced by on-road breakdowns is non-trivial, as reported by past studies. Furthermore, the existing RTI databases lack information on incident duration, a variable that indicates the time it takes for the authorities to clear the incident site and bring traffic operations back to normalcy. The increase in duration may reflect either the severity of the incident or/and the delay in emergency services and thus becomes a key indicator for traffic and safety management. Therefore, this paper aims to present the RTI data of the Sydney Greater Metropolitan Area (GMA), Australia, which includes crashes and breakdowns, along with their duration, covering 5.5 years, starting from the 1st January 2017. The uniqueness of this data is that the RTI duration, i.e., the clearance time of every incident, is provided along with other details, such as vehicles involved, traffic conditions, advisories imposed, etc., over a larger area. Further, the secondary data corresponding to the road network, zonal information, socioeconomic attributes, and travel characteristics collected from various sources were also included. The curated data could be employed to examine the factors influencing RTIs at the micro (individual incident) and macroscopic (zonal) levels.
RESUMEN
Globally, the increase in pedestrian fatalities due to road traffic crashes (RTCs) on transport networks has been a major concern. In low- and middle-income countries (LMICs), pedestrians face a high risk due to RTCs on the rural highway network. The safety evaluation methods, such as observational before-after, empirical Bayes, full Bayes, and cross-sectional methods have been used to identify risk factors of RTCs. However, these methods are data-intensive and have associated limitations. Thus, this study employed a matched case-control method to identify the risk factors of fatal pedestrian crashes. This study utilized crash, traffic volume, speed, geometric, and roadside environment data of a 175 km six-lane rural highway in India. The identified major risk factors, such as clear zone width, the presence of habitation, service roads, and horizontal curve sections, increase the likelihood of a fatal pedestrian crash. This study provides specific insights for modifying the speed limit of highway sections passing through habitation. On such highway sections, designers should shift focus to pedestrian safety. It also suggests that the service road design needs to be reconsidered from a pedestrian safety viewpoint. The proposed method can be used in any other setting having similar traffic and socio-economic conditions.