01661604

Component

Truck-based transportation is the predominant mode used to transport goods and raw materials within the United States. While trucks play a major role in local commerce, a significant portion of truck activity is also long haul in nature. Long-haul truck drivers often need to stop at a designated truck stop or rest area to rest. Unfortunately, drivers are continuously faced with the problem of not being able to secure a safe parking spot since many truck stops and rest areas become fully occupied, and information about parking and availability is limited. Truck drivers faced with full parking lots/facilities either continue driving until a safe parking spot is located or park illegally. Both scenarios pose a hazard to the truck driver, as well as the surrounding road users. One of the solutions proposed to aid trucker parking is the provision of truck parking availability information. Furthermore, providing truck drivers with forecasts of availability would be even more useful, since many truck drivers plan their parking in advance of arrival. Building on one year of nearly continuous truck parking data collection, the authors propose a method for developing a forecasting model that can predict truck parking occupancy for any specified time within the present day, using only historical and real-time truck parking occupancy data from a trucking logistics facility in the northern San Joaquin Valley during 2016. The authors tested several different models using curve fitting methods. The models were verified against successive weekdays with performance measured using the Root Mean Square Error (RMSE). For a particular day, the authors found the maximum error range between 13 to 40 trucks when applied to a logistics facility with a capacity of around 800 parking slots. The authors recommend further research build upon this model to enable it to provide next-day forecasts.

This paper was sponsored by TRB committee AT060 Standing Committee on Trucking Industry Research.

18-06736

English

18p

2018

Transportation Research Board 97th Annual Meeting

Digital/other

Figures; References; Tables

Case studies; Forecasting; Fourier analysis; Mathematical prediction; Parking; Roadside rest areas; Time series; Truck drivers; Trucks

Long haul; Occupancy

California; San Joaquin Valley

Freight Transportation; Highways; Motor Carriers; Operations and Traffic Management; Planning and Forecasting

Transportation Research Board Annual Meeting 2018 Paper #18-06736

TRIS, TRB, ATRI

Jan 8 2018 11:44AM