Sfyridis, Alexandros;
Agnolucci, Paolo;
(2022)
Factors Affecting Road Traffic: Identifying Drivers of Annual Average Daily Traffic Using Least Absolute Shrinkage and Selection Operator Regression.
Transportation Research Record
10.1177/03611981221141435.
(In press).
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Abstract
Road traffic data is important for various applications in transport studies, such as those related to safety, environmental damages, and economic evaluations. Although significant improvement in estimation accuracy has been achieved, less is known about the association of specific factors with road traffic volumes. This paper presents an investigation of the relation of various road, area, and socioeconomic characteristics with annual average daily traffic in England and Wales for four different road classes and five vehicle types. This is achieved by applying least absolute shrinkage and selection operator regression on a comprehensive set of land use, socioeconomic, public transport, and roadway variables. The output reveals that specific socioeconomic and roadway characteristics are those that are mainly associated with traffic volumes across all vehicle types and road classes. Moreover, the association of other variables with traffic volume varies, depending on the road class and vehicle type, creating space for future research. The results can support urban planning and inform policies related to transport congestion and environmental impact mitigation.
| Type: | Article |
|---|---|
| Title: | Factors Affecting Road Traffic: Identifying Drivers of Annual Average Daily Traffic Using Least Absolute Shrinkage and Selection Operator Regression |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1177/03611981221141435 |
| Publisher version: | https://doi.org/10.1177/03611981221141435 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Annual Average Daily Traffic (AADT), COUNTS, DEMAND, EMISSIONS, Engineering, Engineering, Civil, K-FOLD, Least Absolute Shrinkage and Selection Operator (LASSO), MODELS, PREDICTION, road traffic, Science & Technology, SPATIAL INTERPOLATION, Technology, transport, TRANSPORT, Transportation, Transportation Science & Technology, TRAVEL BEHAVIOR, VOLUME |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Bartlett School Env, Energy and Resources |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10164691 |
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