Estimating Truck Travel Time to Passenger Car or Traffic Stream Travel Time Ratio in North Carolina, USA

ABSTRACT

The differences in travel times of passenger cars, traffic stream, and trucks depend on the area type, temporal factors, reference speed, and traffic condition. These explanatory variables account for the effect of geometric conditions and variations in the traffic flow. The focus of this research is to examine the correlations and estimate truck travel time to passenger car or traffic stream travel time ratio of a road link (dependent variable) as a function of these explanatory variables. Travel time data for Mecklenburg County and Iredell County in North Carolina, USA were gathered for the year 2017 to examine correlations, develop generalized estimating equations (GEE) models, and identify explanatory variables influencing the ratios. Gamma log-link distribution-based models are the best-fitted models to estimate the average travel time (ATT) of trucks to the ATT of passenger cars or traffic stream ratios. Notable differences in the coefficients were observed when the ATT of trucks was compared with the ATT of passenger cars or traffic stream. The area type (urban or rural) was observed to influence the ratios differently. The influence of traffic condition, reference speed (or free-flow speed), day-of-the-week (DOW) and time-of-the-day (TOD) on the ratios also varied with the area type.

KEYWORDS:

• Truck
• passenger car
• traffic stream
• travel time

Acknowledgments

The authors thank the staff of North Carolina Department of Transportation (NCDOT) and Regional Integrated Transportation Information System (RITIS) for their help with data needed for this research. The National Performance Management Research data set used in this research is based upon work supported by the Federal Highway Administration under contract number DTFH61-17-C-00003.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Disclaimer

This paper is disseminated in the interest of information exchange. The views, opinions, findings, and conclusions reflected in this paper are the responsibility of the authors only and do not represent the official policy or position of USDOT, NCDOT, the University of North Carolina at Charlotte or other entity. The authors are responsible for the facts and the accuracy of the data presented herein. This paper does not constitute a standard, specification, or regulation.

Additional information

Funding

This work was based on ideas and information collected for a project supported by the United States Department of Transportation - Office of the Assistant Secretary for Research and Technology (USDOT/OST-R) University Transportation Centers Program (Grant # 69A3551747127).