Abstract
In this paper, we investigate the feasibility of using highway traffic officers (TOs) for transportation asset management (TAM) alongside their primary role of incident response. Asset data, typically captured via highway surveys on an annual basis, is unsuitable for those assets whose condition might rapidly change, such as vegetation, street lights, guardrails, or drainage systems. Therefore, we consider as a proof-of-concept, whether data collected from dashboard cameras installed in TO vehicles might provide analysts with near real-time asset data across an entire highway network. We consider a case study of a dedicated TO fleet deployed on the strategic road network (SRN) in England, UK, and develop a simulation based on publicly available data sets. Within the simulation, TOs patrol under two distinct regimes and respond to dynamically generated incidents. The first regime aims to minimise the the fleet’s incident response time, and the second aims to maximise the fleet’s coverage, with an aim to capture asset data across the entire highway network. Overall, our simulations show that the TOs deployed for TAM reduce the SRN junction-to-junction section inter-visit time by around 1 hour 45 minutes, whereas their incident response time is only increased by about 4 minutes. Moreover, 17% of SRN sections are not visited at all when the TOs prioritise fast incident response, which is reduced to 2% when the TOs prioritise the capture of asset data.
Original language | English |
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Publication status | Unpublished - 13 Jan 2022 |
Event | Transport Research Board 2022 - Duration: 9 Jan 2022 → 13 Jan 2022 |
Conference
Conference | Transport Research Board 2022 |
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Period | 9/01/22 → 13/01/22 |
Research Groups and Themes
- Engineering Mathematics Research Group
Keywords
- Transportation Asset Management
- Traffic Officers
- Simulation