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Frontier economics: predicting road travel time

Elliott, D. and Campos, L. and Smith, Ron P. (2011) Frontier economics: predicting road travel time. In: Infraday Conference, 2011, Berlin. (Unpublished)

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Abstract

This paper summarises the development of a model created for the England’s Highways Agency, which uses time series and cross sectional econometric techniques to predict average journey times on any given section of the England’s major road network. The purpose of the model is to simulate the impact of changes in road conditions on road delays across complex road network systems and over extended periods. The empirical analysis is based on separate time-series equations for each road section, where average travel time is regressed against several features describing road conditions on that section, including lagged journey time on that section and on adjacent sections. The equations for the separate sections are combined to form an interacting system, where shocks are transmitted between sections. To estimate the relevant parameters we used longitudinal data across more than 2,500 road sections in England over a two year period, with data recorded at 15 minute intervals. Hence the modelling process made use of 190m records. Although primarily descriptive, two specific features make this analysis particularly suitable for simulation. First, it captures important non-linear features of traffic flow dynamics as, for example, the persistent impact of an accident on road delays after the accident has been cleared and the propagation of delays to different sections of the road network. Although primarily descriptive, two specific features make this analysis particularly suitable for simulation. First, it captures important non-linear features of traffic flow dynamics as, for example, the persistent impact of an accident on road delays after the accident has been cleared and the propagation of delays to different sections of the road network. The prediction of average travel times on road networks under different conditions can have multiple applications. The Highways Agency has used this model to understand better (1) the main drivers of road delays across its network; (2) the impact of past investments on current road delays; and (3) the likely impact of future investments on road delays.

Metadata

Item Type: Conference or Workshop Item (Paper)
School: Birkbeck Faculties and Schools > Faculty of Business and Law > Birkbeck Business School
Research Centres and Institutes: Applied Macroeconomics, Birkbeck Centre for, Innovation Management Research, Birkbeck Centre for
Depositing User: Sarah Hall
Date Deposited: 13 May 2014 08:26
Last Modified: 02 Aug 2023 17:10
URI: https://eprints.bbk.ac.uk/id/eprint/9718

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