Abstract
Truck drivers adhere to delivery schedules making them more likely to reroute rather than cancel a trip when faced with inclement weather. While previous studies modeled the direct effects of adverse weather on total traffic volumes, none considered the particular implications for trucks. The ability to predict spatial and temporal shifts in truck traffic resulting from adverse weather is novel and useful for decision makers tasked with long-range freight planning and for the trucking industry. With deeper insights into rerouting around adverse weather, the trucking industry will be able to more efficiently plan and accurately estimate billable miles. Thus, this study applied dynamic spatial panel regression that captures rerouting behavior of trucks due to adverse weather conditions. Results showed that changes in truck traffic volume due to adverse weather conditions, e.g. surface runoff, snow mass, and humidity, exhibited spatial (direct and indirect) and temporal shifts (short and long term effects).
Acknowledgement
The authors thank the Southern Plains Transportation Center (SPTC) a University Transportation Center funded by the U.S. Department of Transportation, for sponsoring the project that lead to this paper. The authors confirm contribution to the paper as follows: study conception and design: S. Hernandez; data gathering and processing: T. Akter and K. Diaz; analysis and interpretation of results: T. Akter, S. Mitra, S. Hernandez; draft manuscript preparation: T. Akter. All authors reviewed the results and approved the final version of the manuscript.
Disclosure statement
No potential conflict of interest was reported by the authors.
ORCID
Taslima Akter http://orcid.org/0000-0001-9585-7346
Suman Kumar Mitra http://orcid.org/0000-0002-7776-5779
Sarah Hernandez http://orcid.org/0000-0002-4243-1461
Karla Corro-Diaz http://orcid.org/0000-0002-1936-4547