Assessing the Value of Delay to Short-Haul Carriers

 

Q. Miao*¹, X.B. Wang² and T.M. Adams³

 

^1,2 Zachry Department of Civil Engineering, Texas A&M University College Station, TX 77843-3136. *miaoq04@neo.tamu.edu

³ Department of Civil & Environmental Engineering, University of Wisconsin Madison, WI 53706.

 

ABSTRACT

This paper aims at examining the commercial vehicle operators' value of delay (VOD) due to highway congestion in urban area. The VOD is a fundamental parameter that influences the private sector's response to public freight projects and policies. This paper adopts two methods to estimate the VOD; one being the stated preference (SP) survey and the other being simulation of a carrier's fleet operations. The former applies a Logit model and estimates a driver perceived VOD as $56.48 per vehicle per hour for the regular short-haul delivers. The latter gauges the economic impact of delay on carrier's fleet operations in the Houston highway network. The operations essentially reflect more of a just-in-time system due to the rather stringent time window constraints. The simulation is conducted on a rolling time horizon with a heuristic algorithm for dispatching trucks. The major findings include, but are not limited to as follows. The drivers paid by miles perceive a significantly higher VOD than the others; the drivers are more willing to pay for a faster trip when the toll charges do not come out of their own pockets; VOD increases with uncertainty and demand for capacity. The comparison between the survey and the simulation results also indicates that the interviewed drivers perceive a significantly lower VOD than they may actually experience as a fleet, an indicator of myopic vision.

Keywords: Value of Time; Value of Delay; Short-Haul Carrier; Stated Preference; Logit Model; Simulation.

 

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References

[1] Freight Analysis Framework, Commodity Origin-Destination Database: 2002-2035. November 20, 2006. Federal highway Administration: Freight Management and Operations.         [ Links ]

[2] E.C. Sullivan, Continuation Study to Evaluate the Impacts of the SR 91 Value-Priced Express Lanes -Final Report. Project Report to the State of California Department of Transportation, Traffic Operation Program, HOV Systems Branch, pp. 123-135, December, 2000.         [ Links ]

[3] E.C. Sullivan, State Route 91 Value-Priced Express Lanes: Updated Observations. In Transportation Research Record: Journal of the Transportation Research Board, Vol. 1812, No. 5, Transportation Research Board of the National Academies, Washington, D.C., 2002, pp. 37-42.         [ Links ]

[4] J. Supemak, J. Golob, T. Golob, C. Kaschade, C. Kazimi, E. Schreffler and D. Steffey. I-15 Congestion Pricing Project Monitoring and Evaluation Services. Phase II Year Three Overall Report, San Diego Council of Governments, CA, 2001.         [ Links ]

[5] C.R. Swenson, C. Alasdair, and M.W. Burris. Toll Price Traffic Demand Elasticity Analysis on Variable Priced Toll Bridges. ITE annual meeting, Chicago, IL, 2001.         [ Links ]

[6] D.A. Hensher and W.H. Greene. The Mixed Logit Model: The State of Practice, Transportation, Vol. 30, No. 2, 2003, pp. 133-176.         [ Links ]

[7] J.A. Small, C. Winston, and J. Yan. Uncovering the Distribution of Motorists: Preferences for Travel Time and Reliability. Econometrica, Vol. 73, No. 4, 2005, pp. 1367-1382.         [ Links ]

[8] M. Fosgerau and L. Engelson. The Value of Travel Time Variance. Transportation Research Part B: Methodological, Vol. 45, No. 1, 2011, pp. 1-8.         [ Links ]

[9] G.C. de Jong, M. Gommers, H. Inwood and J. Klooster. Time Valuation in Freight Transport: Method and Results. in PTRC European Transport Highways and Planning 20th Annual Summer Meeting, London: PTRC, 1992.         [ Links ]

[10] G.C. de Jong, Y. van de Vyvre, and H. Inwood. The Value of Time for Freight Transport. in World Conference on Transport Research, Sydney, NSW, 1995.         [ Links ]

[11] G.C. de Jong. Freight and coach value of time studies. in Easthampstead Park Seminar on the Value of Time, Easthampstead, London: PTRC, 1996.         [ Links ]

[12] M. Wigan, N. Rockliffe, T. Thoresen, and D. Tsolakis. Valuing Long-Haul and Metropolitan Freight Travel Time and Reliability. Journal of Transportation and Statistics, Vol. 3, No. 3, pp. 2000, 83-89.         [ Links ]

[13] M. Wigan, T.N. Fuller, N.R. Rockliffe, D. Tsolakis and T. Thoresen. Economic evaluation of road investment proposals: Valuing travel time savings for freight. Project Report, AustRoads, AP-R230-03, pp. 164, Sydney, Australia, 2003.         [ Links ]

[14] A.S. Fowkes and N. Shinghal. The Leeds Adaptive Stated Preference Methodology. Working paper, Institute of Transportation Studies, University of Leeds, UK, 2002.         [ Links ]

[15] K. Kawamura. Perceived Value of Time for Truck Operators, In Transportation Research Record: Journal of the Transportation Research Board, Vol. 1725, No. 5, Transportation Research Board of the National Academies, Washington, D.C., 2000, pp. 31-36.         [ Links ]

[16] M.A. Figliozzi, Analysis of the Efficiency of Urban Commercial Vehicle Tours: Data Collection, Methodology, and Policy Implications. Transportation Research Part B, Vol. 41, No. 9, 2007, pp. 1014-1032.         [ Links ]

[17] M.A. Figliozzi, The Impacts of Congestion on Commercial Vehicle Tour Characteristics and Cost. Transportation Research Part E, Vol. 46, No. 4, 2010, pp. 496-506.         [ Links ]

[18] Manual: User Benefit Analysis for Highway, American Association of State Highway and Transportation Officials, National Cooperative Highway Research Program (NCHRP) Project 02-23, Washington, D. C., 2003.         [ Links ]

[19] Economic Effects of Transportation: The Freight Story. ICF Consulting, Virginia and HLB Decision-Economics, Maryland, 2002.         [ Links ]

[20] FHWA Freight BCA Study: Summary of Phase II Results. ICF Consulting, Virginia and HLB Decision-Economics, Maryland, 2004.         [ Links ]

[21] E.S. Mot, J.S. Cramer and E.M. van der Gulik. Choice of Mode of Payment, Report 228, Stichting Voor Economisch Onderzoek, In dutch, 1989.         [ Links ]

[22] A. Pires, G. Putnik and P. Ávila. A Survey Analysis of the Resource Selection Models in Agile/Virtual Enterprises. Journal of Applied Reserach and Technology, Vol. 10, No. 3, pp. 416-427, 2012.         [ Links ]

[23] M.M. Solomon. Algorithms for the Vehicle Routing and Scheduling Problems with Time Constraints, Operations Research, Vol. 35, No. 2, pp. 254-265, 1987.         [ Links ]

[24] G. Clarke and W. Wright. Scheduling of Vehicles from A Central Depot to A Number of Delivery Points, Operations Research, Vol. 12, No. 4, pp. 568-581, 1964.         [ Links ]

[25] M. Cedillo-Campos and C. Sánchez. Dynamic Self-Assessment of Supply Chains Performance: an Emerging Market Approach. Journal of Applied Research and Technology, Vol. 11, No. 3, pp. 338-347.         [ Links ]

[26] S. Guillén-Burguete, H. Sánchez-Larios, J. Vázquez-Vázquez. An Optimal Transportation Schedule of Mobile Equipment. Journal of applied Research and Technology, Vol. 10, No. 5, pp. 713-723.         [ Links ]

[27] K. J. Fender and D. A. Pierce. An Analysis of the Operational Costs of Trucking: A 2012 Update, American Transportation Research Institute (ATRI), 2012.         [ Links ]