A corridor-level pedestrian crash risk assessment framework using autonomous vehicle sensor data
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Description
This thesis proposes an Extreme Value Theory modelling framework to assess corridor-wide pedestrian crash risk using autonomous vehicle sensor data. The proposed framework was applied to vehicle-pedestrian traffic conflicts on an arterial corridor in Miami, USA, captured by a fleet of Argoverse autonomous vehicles—a Ford Motors subsidiary. The proposed extreme value modelling framework with the block maxima sampling technique has been found to provide a reasonable estimate of historical pedestrian crash frequencies on that corridor. This thesis demonstrates the potential of using autonomous vehicle sensor data for network-level pedestrian safety.
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| ID Code: | 243836 |
|---|---|
| Item Type: | QUT Thesis (Master of Philosophy) |
| Supervisor: | Haque, Md. Mazharul (Shimul) & Ali, Yasir |
| Keywords: | autonomous vehicle, extreme value thory model, pedestrian safety analysis, vulnerable road users, vehicle-pedestrian conflict |
| DOI: | 10.5204/thesis.eprints.243836 |
| Pure ID: | 147300727 |
| Divisions: | Current > QUT Faculties and Divisions > Faculty of Engineering Current > Schools > School of Civil & Environmental Engineering |
| Institution: | Queensland University of Technology |
| Deposited On: | 12 Oct 2023 06:54 |
| Last Modified: | 12 Oct 2023 06:54 |
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