How does the value of time influence road user costs during work zone closures? A case study in El Paso, Texas, using simulation-based modeling methods

Jeffrey A Shelton (1) , Peter T Martin (2)
(1) Multi-Resolution Modeling, Texas A&M Transportation Institute, El Paso, Texas , United States
(2) Department of Civil Engineering, New Mexico State University, Las Cruces, New Mexico , United States

Abstract

It is becoming standard practice for many departments of transportation (DOTs) to use incentive/disincentive clauses (also known as road user costs) with contractors to stay on or ahead of schedule. These road user costs are clauses that DOTs use to calculate a monetary amount to encourage contractors to complete work prior to milestone dates and/or limit the time specified on the contract. The monetary amounts are typically vehicle operating costs and vehicle delay costs encumbered by highway users resulting from construction, maintenance, or rehabilitation activity. In this paper, we propose an innovative way of calculating these costs using varied values of time based on trip purpose and departure time. In addition, we use advanced pre-trip and en route traveler information to determine the influence it has on route choice. Several scenarios are modeled using an advanced, simulation-based dynamic traffic assignment model. The goal of this paper is to identify the governing factors that contribute to road use costs by determining different approaches to derive the value one places on a trip. The approach to this study is twofold: first several research methods were used to derive the value of time. Second, the use of advanced traveler information is introduced to determine if it plays a critical role in route choice. The proposed methodology shows differences in road user cost calculations. Which approach would be more receptive to a contractor while proposing roadway construction? A case study of a roadway construction project in El Paso, Texas, is used to compare different approaches to calculate road user costs.

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References

Barnes, G., & Langworthy, P. (2004). Per mile costs of operating automobiles and trucks. Transportation Research Record: Journal of the Transportation Research Board, 1864, 71–77. https://doi.org/10.3141/1864-10
Benekohal, R., Kaja-Mohideen, A., & Chitturi, M. (2003). Evaluation of construction work zone operational issues: Capacity, queue and delay (Report No. ITRC FR 00/01-4). Illinois Transportation Center, Illinois Department of Transportation.
Borchardt, D., & Voight, A. (1998). A short course on techniques for determining construction related road user costs. Texas Transportation Institute.
Chiu, Y.-C., Zhou, L., & Song, H. (2010) The development and calibration of the Anistropic Mesoscopic Simulation Model on uninterrupted flow facilities. Transportation Research, Part B: Methodological.
Council, F., Zaloshnja, E., Miller, T., & Persaud, B. (2005). Crash cost estimates by maximum police-reported injury severity within selected crash geometries (Report No. FHWA-HRT-05-051). Federal Highway Administration.
Daniels, G., Ellis, D., & Stockton, W. (1999). Techniques for manually estimating road user costs associated with construction projects. Texas Transportation Institute.
Dolama, M., Falls, L., & Regehr, J. (2020). Probabilistic methodology to quantify user delay costs for urban arterial work zones. Journal of Transportation Engineering, Part A: Systems, 146. https://doi.org/10.1061/JTEPBS.0000424
Kachroo, P., & Ozbay, K. M. A. (2018). Feedback control theory for dynamic traffic assignment (2nd ed.). Springer International. http://doi.org/10.1007.978-3-319-69231-9_3
Mallela, J., & Sadasivam, S. (2011). Work zone road user costs: Concepts and applications (Report No. FHWA-HOP-12-005). Applied Research Associates.
McFarland, W., Kabat, R., & Krammes, R. (1994). Comparison of contracting strategies for reducing project construction time. Texas Transportation Institute.
Nadimpalli, B., Martin, P., Chaudhuri, P., & Stevanovic, A. (2009). Road user impacts due to speed limit reduction in work zones—Which tool is best: QuickZone or VISUM [Paper presentation]. Transportation Research Board 89th Annual Meeting, Washington, DC. https://www.workzonesafety.org/files/documents/database_documents/TRB2010paper_Nadimpalli.pdf
Sadasivam, S., & Mallela, J. (2015). Application of work zone road user costs to determine schedule-related incentives and disincentives: Conceptual framework. Transportation Research Record: Journal of the Transportation Research Board, 2504, 39–45. https://doi.org/10.3141/2504-05
Shelton, J., Martin, P. T., & Valdez, G. (2017). Deriving the value of time in a border region using a state-of-the-art dynamic modeling approach [Paper presentation]. European Transport Conference, Barcelona, Spain. https://aetransport.org/past-etc-papers/conference-papers-2017?abstractId=5712&state=b
Texas Transportation Commission. (2020). Minute order: Border Highway West Expressway toll rates. https://ftp.dot.state.tx.us/pub/txdot/commission/2019/1031/13d2.pdf

Authors

Jeffrey A Shelton
jshelton@nmsu.edu (Primary Contact)
Peter T Martin
Shelton, J. A., & Martin, P. T. (2021). How does the value of time influence road user costs during work zone closures? A case study in El Paso, Texas, using simulation-based modeling methods. Journal of Sustainable Development of Transport and Logistics, 6(1), 18–31. https://doi.org/10.14254/jsdtl.2021.6-1.2

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