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Arabian Journal for Science and Engineering

, Volume 44, Issue 5, pp 4169–4182 | Cite as

Optimal Timing for Lane(s) Addition to an Existing Highway: A Benefit–Cost Approach

  • Muhammad Asif Khan
  • Anwaar AhmedEmail author
  • Wasim Irshad Ul Haq Kayani
Research Article - Civil Engineering
  • 31 Downloads

Abstract

The present study presents a comprehensive framework for optimal highway capacity expansion through lane(s) addition. The applicability of the proposed framework is demonstrated using data from a multi-lane urban arterial. In the proposed methodology, annualized widening costs (agency lane addition cost and work zone user delay cost) and excess user costs for do-nothing scenario (excess travel delay cost, excess vehicle operating cost and excess crash cost) were estimated for each analysis year within highway life cycle to estimate a range of traffic volumes for highway capacity expansion. Furthermore, a sensitivity analysis was conducted to evaluate the sensitivity of optimal time for highway capacity expansion to: (1) annual traffic growth rates (2) agency to user cost relative weights and (3) annual discount rate. Study results revealed that optimal highway capacity expansion time corresponds to an ADT ranging between approximately 34,430 and 37,600 vehicles per day for the case study traffic mix conditions. The sensitivity analysis results revealed that increase in agency to user cost relative weight and annual traffic growth rate would result in later and earlier optimal highway capacity expansion, respectively, while variations in annual discount rate have minimal impact on optimal highway capacity expansion timings. It is anticipated that the application of proposed framework can result in a sustainable decision by saving a huge amount of agency expenditures and excess user costs due to non-optimal decisions.

Keywords

Highway capacity expansion Optimal decision Economic analysis Sensitivity analysis Traffic growth rate 

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References

  1. 1.
    Federal Highway Administration (FHWA): Asset Management Primer. Department of Transportation, Washington, DC, Office of Asset Management, Federal Highway Administration, US (1999)Google Scholar
  2. 2.
    Governmental Accounting Standards Board (GASB) (1999) Statement No. 34: Basic Financial Statements and Management’s Discussion and Analysis for State and Local Governments. Governmental Accounting Standards Board, Norwalk, CTGoogle Scholar
  3. 3.
    Strategic Highway Research Program (SHRP) (2009) Performance measurement framework for highway capacity decision making. SHRP 2, Report S2-C02-RR, strategic highway research program, National Research CouncilGoogle Scholar
  4. 4.
    Sinha, K.C.; Labi, S.: Transportation Decision Making-Principles of Project Evaluation and Programming. Wiley, Hoboken (2007)zbMATHGoogle Scholar
  5. 5.
    Zhao, T.; Sundararajan, S.K.; Tseng, C.: Highway development decision-making under uncertainty: a real options approach. J. Infrastruct. Syst. 10(01), 23–32 (2004)CrossRefGoogle Scholar
  6. 6.
    Handy, S.; Boarnet, M.G.: Draft policy brief on highway capacity and induced travel. http://arb.ca.gov/cc/sb375/policies/policies.htm (2014). Accessed 20 April 2015
  7. 7.
    Bai, Q.; Ahmed, A.; Labi, S.; Sinha, K.C.; Traffic volume benchmarks for major arterial widening versus expressway construction: exploratory approach. J. Trans. Eng. A Syst. 143(8) (2017)Google Scholar
  8. 8.
    Yang, J.: Nested Markov decision framework for coordinating pavement improvement with capacity expansion. J. Transp. Eng. 138(04), 387–394 (2012)CrossRefGoogle Scholar
  9. 9.
    Abaza, K.A.: Optimum flexible pavement life cycle analysis model. J. Transp. Eng. 128(16), 542–549 (2002)CrossRefGoogle Scholar
  10. 10.
    Hong, T.H.; Hastak, M.: Evaluation and determination of optimal MR&R strategies in concrete bridge decks. J. Autom. Constr. 16, 165–175 (2007)CrossRefGoogle Scholar
  11. 11.
    Mamlouk, M.S.; Zaniewski, J.P.: Optimizing pavement preservation: an urgent demand for every highway agency. J. Pavement Eng. 2(2), 135–148 (2001)CrossRefGoogle Scholar
  12. 12.
    Marasteanu, M.; Velasquez, R.; Herb, W.; Tweet, J.; Turos, M.; Watson, M.; Stefan, H.G.: Determination of optimum time for the application of surface treatments to asphalt concrete pavements. Phase 2, report No. MN/RC 2008-16, Minnesota Department of Transportation (Mn DOT), St. Paul, Minnesota (2008)Google Scholar
  13. 13.
    Peshkin, D.G.; Hoerner, T.E.; Zimmerman, K.A.: Optimal timing of pavement preventive maintenance treatment applications. National Cooperative Highway Research Program (NSHRP) Report 523, Transportation Research Board, National Research Council, Washington, DC (2004)Google Scholar
  14. 14.
    Polus, A.; Pollatschek, M.A.: Criteria for widening of two-lane rural highway. Transp. Policy 2, 379–385. http://www.elsevier.com/locate/transpo1. (2004)
  15. 15.
    Litman, T.: What’s it worth? Economic evaluation for transportation decision-making. Presented at the internet symposium on benefit-cost analysis transportation association of Canada, February 2001. http://www.vtpi.org/worth.pdf (2001). Accessed 15 Feb 2015
  16. 16.
    Taggart, A.; Tachtsi, L.; Lugg, M.; Davies, H.: UKRLG framework for highway infrastructure asset management. Infrastruct. Asset Manag. 1(1), 10–19 (2017)CrossRefGoogle Scholar
  17. 17.
    Srinivasan, R.; Parlikad, A.K.: An approach to value-based infrastructure asset management. Infrastruct. Asset Manag. 4(3), 87–95 (2017)CrossRefGoogle Scholar
  18. 18.
    Adey, B.: A process to enable the automation of road asset management. In: 2nd International Symposium on Infrastructure Asset Management–SIAM 2017. Zurich, Switzerland (2017)Google Scholar
  19. 19.
    Beria, P.; Maltese, I.; Mariotti, I.: Multicriteria versus cost benefit analysis: a comparative perspective in the assessment of sustainable mobility. Eur. Transp. Res. Rev. 4, 137–152 (2012)CrossRefGoogle Scholar
  20. 20.
    Bai, H.; Chen, J.; Xie, Z.: A Multiple attributive decision making method for the no of lanes based on delay cost. Presented at international conference of chinese transportation professionals (ICCTP) 2010, pp 125–131 (2010)Google Scholar
  21. 21.
    Hansen, M.; Gillen, D.; Dobbins, A.; Huang, Y.; Puvathingal, M.: The air quality impacts of urban highway capacity expansion: traffic generation and land use change, UC Berkeley Working Paper, UCTC No 398 (2017)Google Scholar
  22. 22.
    Lu, J.; Ashuri, B.; Wang, X.; Kashani, H.: Optimal timing of investment in highway expansion. In: Proceedings of 91st Annual Conference of Transportation Research Board, Washington, DC (2011)Google Scholar
  23. 23.
    Iacono, M.; Levinson, D.; Rural highway enhancement and economic development: impacts on private 1 earnings and employment. http://nexus.umn.edu (2012). Accessed 23 Feb 2015
  24. 24.
    Moloney, M.; McKenna, T.; Fitzgibbon, K.; McKeogh, E.: Quality data for strategic infrastructure decisions in Ireland. Infrastruct. Asset Manag. 4(2), 40–49 (2017)CrossRefGoogle Scholar
  25. 25.
    Dawson, R.; Walsh, C.; Purnell, P.; Rogers, C.: Infrastructure business models, valuation and innovation for local delivery. Infrastruct. Asset Manag. 1(3), 66–67 (2017)CrossRefGoogle Scholar
  26. 26.
    Transportation Research Board: Highway Capacity Manual 2000. Washington, DC, Transportation Research Board (2000)Google Scholar
  27. 27.
    Walls, J.; Smith, M.R.; Life cycle cost analysis in pavement design. Technical Report FHWA-SA-98-079, Federal Highway Administration, Washington, DC (1998)Google Scholar
  28. 28.
    Transportation Research Board. National Research Council, Washington (2000).Google Scholar
  29. 29.
    Manual on Uniform Traffic Control Devices (MUTCD): Manual on Uniform Traffic Control Devices for Streets and Highways. US Department of Transportation, Washington, DC, Federal Highway Administration (2009)Google Scholar
  30. 30.
    Yu, W.; Lo, S.: Time-dependent construction social costs model. J. Construct. Manag. Econ. 23(3), 327–337 (2005)CrossRefGoogle Scholar
  31. 31.
    Roess, R.P.; Prassas, E.S.; McShane, W.R.: Traffic Engineering. Pearson Education Inc, Upper Saddle River (2004)Google Scholar
  32. 32.
    COMSIS Corporation, Scientific Applications International Corporation, Garman Associates: Development of diurnal traffic distribution and daily, peak and off-peak vehicle speed estimation procedures for air quality planning, Work Order B-94-06, Federal Highway Administration. U.S, Department of Transportation, Washington, DC (1995)Google Scholar
  33. 33.
    Irfan, M.; Khurshid, M.B.; Anastasopoulos, P.; Labi, S.; Moavenzadeh, F.: Planning stage estimation of highway project duration on the basis of anticipated project cost, project type and contract type. J. Proj. Manag. 29(01), 78–92 (2010)Google Scholar
  34. 34.
    Lamptey, G.; Ahmed, M.; Labi, S.; Sinha, K.C.; Life cycle cost analysis for INDOT pavement design procedures. Final Report FHWA/IN/JTRP- 2004/28, Purdue University, West Lafayette, IN (2005)Google Scholar
  35. 35.
    Victoria Transportation Policy Institute (VTPI) (2005) Transportation cost and benefit analysis: travel time costs, Victoria Transportation Policy Institute, Victoria, Canada. http://www.vtpi.org/tca/tca0502.pdf. Accessed 19 Aug 2005.
  36. 36.
    A Manual of User Benefit Analysis for Highways, 2nd edn. American Association of State Highway and Transportation Officials, Washington, DC (2003).Google Scholar
  37. 37.
    National Safety Council (NSC) (2001) Estimating the costs of unintentional injuries. 2000 National Safety Council, Spring Lake Drive, Itasca, IL. http://www.nsc.org/lrs/statinfo/estcost0.htm
  38. 38.
    Government of Pakistan (GOP): Pakistan Economic Survey 2012–13. Economic Advisor’s Wing, Finance Division, Government of Pakistan, Islamabad (2012)Google Scholar
  39. 39.
    Capital Development Authority (CDA) 2013. Contract Documents—CDA Office.Google Scholar
  40. 40.
    Pakistan Bureau of Statistics (PBS): Government of Pakistan. Islamabad, Pakistan (2015)Google Scholar
  41. 41.
    National Highway Authority (NHA) (2003) Annual Maintenance Plan. Road Asset Management System Directorate.Google Scholar
  42. 42.
    Gwilliam, K.: The Value of Time in Economic Evaluation of Transport Projects: Lessons from Recent Research, Transport No. OT-5, World Bank, Washington (1997)Google Scholar
  43. 43.
    O’Fallon, C.; Sullivan, C.: Understanding and managing weekend traffic congestion. In: 26th Australian Transport Research Forum, Wellington, New Zealand (2003)Google Scholar
  44. 44.
    Texas Transportation Institute (TTI) (2005) Freeway traffic conditions and trends in the Phoenix region, 2004. Prototype Annual Report.Google Scholar
  45. 45.
    McMahon, K.; Dahdah, S.: The true cost of road crashes: valuing life and the cost of a serious injury. International road assessment program. http://www.irap.net/en/about-irap-3/research-and-technical-papers (2008)
  46. 46.
    Federal Highway Administration (FHWA): Highway Statistics, 1997. Office of Highway Information Management, Federal Highway Administration, Washington, DC (1998)Google Scholar
  47. 47.
    Harkey, D.L.; Srinivasan, R.; Zegeer, C.V.; Persuad, B.; Lyon, C.; Eccles, K.; Council, F.M.; McGee, H.: Crash Reduction Factors for Traffic Engineering and Intelligent Transportation System Improvements-State of Knowledge Report NCHRP Results Digest 229. Transportation Research Board, NRC, Washington (2004)Google Scholar
  48. 48.
    Saltelli, A.; Chan, K.; Scott, E.M.: Sensitivity Analysis: Gauging the Worth of Scientific Models. Wiley, West Sussex (2000)Google Scholar
  49. 49.
    Kavitha, K.; Pandian, P.: Sensitivity analysis of costs in interval transportation problems. Appl. Math. Sci. 6(92), 4569–4576 (2012)MathSciNetzbMATHGoogle Scholar
  50. 50.
    Frey, H.C.; Patel, S.R.: Identification and review of sensitivity analysis methods. Risk Anal. 22(3), 553–577 (2002)CrossRefGoogle Scholar
  51. 51.
    Darter, M.I.; Smith, R.E.; Shahin, M.Y.: Use of life cycle cost analysis as the basis for determining the cost effectiveness of maintenance and rehabilitation treatments for developing a network level assignment procedure. In: Procedings of North American Pavement Management Conference, Vol. 2, Toronto, Ontario (1985)Google Scholar
  52. 52.
    Peterson, D.E.: Life cycle cost analysis of pavements. national cooperative highway research program, NCHRP, Synthesis of Highway Practice 122, Transportation Research Board, TRB, National Research Council, Washington, DC (1985)Google Scholar
  53. 53.
    Administration, Federal Highway (FHWA): Economic Analysis Primer, Federal Highway Administration. U.S, Department of Transportation, Washington, DC (2002)Google Scholar
  54. 54.
    Lamptey, G.: Optimal scheduling of pavement preventive maintenance using life cycle cost analysis. MS Thesis, Purdue Univ., West Lafayette, IN (2004)Google Scholar
  55. 55.
    Labi, S.; Sinha, K.C.: Life cycle evaluation of flexible pavement preventive maintenance. J. Transp. Eng. 131(10), 744–751 (2005)CrossRefGoogle Scholar
  56. 56.
    Federal Highway Administration (FHWA) (1998) Life cycle cost analysis in pavement design—in search of better investment decisions. Report FHWA-SA-98-079. Federal Highway Administration, US Department of Transportation, Washington, DCGoogle Scholar

Copyright information

© King Fahd University of Petroleum & Minerals 2018

Authors and Affiliations

  1. 1.Graduate Student Upper Great Plains Transportation Institute (UGPTI)North Dakota State University (NDSU)FargoUSA
  2. 2.Military College of EngineeringNational University of Sciences and TechnologyRisalpurPakistan

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