Critical risk factors associated with fatal/severe crash outcomes in personal mobility device rider at-fault crashes: A two-step inter-cluster rule mining technique.

Personal Mobility Devices (PMDs) have witnessed an extraordinary surge in popularity, emerging as a favored mode of urban transportation. This has sparked significant safety concerns, paralleled by a stark increase in PMD-involved crashes. Research indicates that PMD user behavior, especially in urban areas, is crucial in these crashes, underscoring the need for an extensive investigation into key factors, particularly those causing fatal/severe outcomes.

Investigating factors affecting bus/minibus accident severity in a developing country for different subgroup datasets characterised by time, pavement, and light conditions.

Developing countries are primarily associated with poor roadway and lighting infrastructure challenges, which has a considerable effect on their traffic accident fatality rates. These rates are further increased as bus/minibus drivers indulge in risky driving, mainly during weekends when traffic and police surveillance is low to maximise profits. Although these factors have been mentioned in the literature as key indicators influencing accident severity of buses/minibuses, there is currently no study that explored the complex mechanisms underpinning the simultaneous effect of pavement and light conditions on the generation of accident severity outcomes while considering weekly temporal stability of the accident-risk factors.

Application of naïve Bayesian approach in detecting reproducible fatal collision locations on freeway.

Detecting high-collision-concentration locations based solely on collision frequency may produce different results compared to those considering the severities of the collisions. In particular, it can lead government agencies focusing sites with a high collision frequency while neglecting those with a lower collision frequency but a higher percentage of injury and fatal collisions. This study developed systematic ways of detecting reproducible fatal collision locations (R) using the naïve Bayes approach and a continuous risk profile (CRP) that estimates the true collision risk by filtering out random noise in the data.

Enforcement avoidance behavior near automated speed enforcement areas in Korean expressways.

Automated speed enforcement system (ASES) has been deployed as a safety countermeasure on Korean roadways to reduce speeding-related traffic crashes; information on ASES locations is mandated to be open to the public. However, because drivers are alerted about enforcement via on-board navigation systems and roadside signs, they can avoid enforcement by momentarily reducing their speeds near ASES locations. This enforcement avoidance behavior (EAB) can induce sudden changes in speed near the enforcement locations and thereby increase risk of crash occurrence.

Geocoding police collision report data from California: a comprehensive approach.

Background: Collision geocoding is the process of assigning geographic descriptors, usually latitude and longitude coordinates, to a traffic collision record. On California police reports, relative collision location is recorded using a highway postmile marker or a street intersection. The objective of this study was to create a geocoded database of all police-reported, fatal and severe injury collisions in the California Statewide Integrated Traffic Records System (SWITRS) for years 1997-2006 for use by public agencies.