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Analysis of pedestrian accident injury-severities at road junctions and crossings using an advanced random parameter modelling framework: The case of Scotland by Adebola Olowosegun; Nathaniel Babajide; Adeyemi Akintola; Grigorios Fountas; Achille Fonzone is a Engineering article available to read on EtoBox.
What is Analysis of pedestrian accident injury-severities at road junctions and crossings using an advanced random parameter modelling framework: The case of Scotland about?
This paper investigates the determinants of injury severities in pedestrian-motor vehicle accidents at signalised and unsignalised junctions, and at physically-controlled and human-controlled crossings in Scotland. The accident data were drawn from the official police crash report database of the UK spanning a period between 2010 and 2018. Correlated random parameter ordered probit models with heterogeneity in the means were developed in order to account for the multi-layered impact of unobserved heterogeneity on statistical estimation. The model estimation results showed that the severities of accident injuries are affected by roadway, location, weather, vehicle, and driver characteristics as well as temporal attributes (including time and day of the accident). Factors such as the urban context, lighting and weather conditions and road surface conditions were found to result in correlated random parameters, thus capturing the intricate, yet interactive effects of unobserved heterogeneity, and particularly the unobserved behavioural response of road users to different traffic control types at junctions and crossings. Vehicle type, driver’s gender and day-of-the-week were observed t
Who reads Analysis of pedestrian accident injury-severities at road junctions and crossings using an advanced random parameter modelling framework: The case of Scotland?
It is typically read by researchers, students, and practitioners in Engineering.
- Author
- Adebola Olowosegun; Nathaniel Babajide; Adeyemi Akintola; Grigorios Fountas; Achille Fonzone
- Publisher
- Elsevier BV
- Published
- 2022
- Language
- EN
- Field
- Engineering (Physical Sciences)