Quantifying Operational Disruptions as Measured by Transportation Network Reliability
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 6, Issue 4
Abstract
There is global interest by transportation planners and enterprise operators to monitor the inherent uncertainty of transportation networks. Traditional performance metrics may erroneously prioritize project initiatives based on disruptions measured from ideal driving speeds; however, commuters and enterprise operators have demonstrated the ability to accommodate recurrent highway congestion by adjusting departure times, transportation modes, origins, or destinations in logistics planning. Recent performance metrics of transportation network reliability have demonstrated the importance of measuring disruptions from normal operating conditions. Using disaggregate speed data, typical conditions are assessed by mean and median speeds across disparate hours of the day and days of the week. In this paper, we establish a quantitative multicriteria framework for measuring operational disruptions based on the intensity and duration of observed deviations from normal conditions. Advances in data collection provide the disaggregated data that can be used to identify when disruptions occur and the extent of affected volume. This approach influences the prioritization of infrastructure improvements based on deviations from typical conditions and informs appropriate mitigation strategies based on the category and time of disruption. A demonstration of the approach to a geographically diverse region is provided, with implications for several agency-planning horizons.
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Data Availability Statement
Some or all data, models, or code used during the study were provided by a third party
1.
Volume data from count station from Virginia Department of Transportation.
2.
Speed data associated with count stations from INRIX.
Direct requests for these materials may be made to the provider as indicated in the Acknowledgments.
Acknowledgments
This effort has been supported in part by the Virginia Department of Transportation (VDOT), the Virginia Transportation Research Council (VTRC), and the Commonwealth Center for Advanced Logistics Systems (CCALS).
Data used in this work may be issued based on the decision of the third-party providers.
References
Alsultan, M., J. Jun, and J. Lambert. 2019. “Systems evaluation for access management of multiscale transportation networks.” In Proc., 2019 IEEE Int. Systems Conf. (SysCon), 1–8. New York: IEEE.
Alsultan, M., J. Jun, and J. H. Lambert. 2020. “Program evaluation of highway access with innovative risk-cost-benefit analysis.” Reliab. Eng. Syst. Saf. 193 (Jan): 106649. https://doi.org/10.1016/j.ress.2019.106649.
Anam, S., J. S. Miller, D. Ph, M. Asce, and J. W. Amanin. 2020. “Managing traffic forecast uncertainty.” J. Risk Uncertainty Eng. Syst. Part A: Civ. Eng. 6 (2).
Angel, S., and A. M. Blei. 2016. “The productivity of American cities : How densification, relocation, and greater mobility sustain the productive advantage of larger U.S. metropolitan labor markets.” Cities 51 (Jan): 36–51. https://doi.org/10.1016/j.cities.2015.11.030.
Bostick, T. P., E. B. Connelly, J. H. Lambert, and I. Linkov. 2018. “Resilience science, policy and investment for civil infrastructure.” Reliab. Eng. Syst. Saf. 175 (Jul): 19–23. https://doi.org/10.1016/j.ress.2018.02.025.
Brilon, W., J. Geistefeldt, and M. Regler. 2005. “Reliability of freeway traffic flow: A stochastic concept of capacity.” In Proc., 16th Int. Symp. on Transportation and Traffic Theory, 125–144. Bochum, Germany: Ruhr-Univ.
Cambridge Systematics Inc. 2013. “Incorporating reliability performance measures into the transportation planning and programming processes.” In SHRP 2 reliability project L05 performance. Cambridge, MA: Cambridge Systematics.
Carrion, C., and D. Levinson. 2012. “Value of travel time reliability: A review of current evidence.” Transp. Res. Part A: Policy Pract. 46 (4): 720–741.
Chen, Z., and W. Fan. 2019. “Data analytics approach for travel time reliability pattern analysis and prediction.” J. Mod. Transp. 27 (4): 250–265. https://doi.org/10.1007/s40534-019-00195-6.
Collier, Z. A., and J. H. Lambert. 2018. “Time management of infrastructure recovery schedules by anticipation and valuation of disruptions.” J. Risk Uncertainty Eng. Syst. Part A: Civ. Eng. 4 (2): 04018012 https://doi.org/10.1061/AJRUA6.0000961.
Dowling, R., K. Parks, B. Nevers, J. Josselyn, and S. Gayle. 2015. Incorporating reliability into the congestion management process: A primer. Washington, DC: FHWA.
Dutta, N., and M. D. Fontaine. 2019. “Improving freeway segment crash prediction models by including disaggregate speed data from different sources.” Accid. Anal. Prev. 132 (Nov): 105253.
FHWA. 2016. MAP-21 proposed measures for congestion, reliability, and freight. Washington, DC: FHWA.
FHWA. 2017. Simplified highway capacity calculation method for the highway performance monitoring system. Washington, DC: FHWA.
FHWA. 2018. National performance measures for congestion, reliability, and freight, and CMAQ traffic congestion. Washington DC: FHWA.
Ganin, A. A., M. Kitsak, D. Marchese, J. M. Keisler, T. Seager, and I. Linkov. 2017. “Resilience and efficiency in transportation networks.” Sci. Adv. 3 (12): e1701079. https://doi.org/10.1126/sciadv.1701079.
Gong, L., and W. Fan. 2017. “Applying travel-time reliability measures in identifying and ranking recurrent freeway bottlenecks at the network level.” J. Transp. Eng. Part A: Syst. 143 (8): 04017042 https://doi.org/10.1061/JTEPBS.0000072.
Gong, L., and W. Fan. 2018. “Developing a systematic method for identifying and ranking freeway bottlenecks using vehicle probe data.” J. Transp. Eng. Part A: Syst. 144 (3): 04017083 https://doi.org/10.1061/JTEPBS.0000119.
Grant, M., B. Bowen, M. Day, R. Winick, J. Bauer, A. Chavis, and S. Trainor. 2011. Congestion management process: A guidebook. Washington, DC: FHWA.
Haimes, Y. Y., S. Kaplan, and J. H. Lambert. 2002. “Risk filtering, ranking, and management framework using hierarchical holographic modeling.” Risk Anal. 22 (2): 383–397. https://doi.org/10.1111/0272-4332.00020.
Hamilton, M. C., J. H. Lambert, and L. J. Valverde. 2015. “Climate and related uncertainties influencing research and development priorities.” J. Risk Uncertainty Eng. Syst. Part A: Civ. Eng. 1 (2): 04015005. https://doi.org/10.1061/AJRUA6.0000814.
Heshami, S., L. Kattan, D. Ph, P. Eng, Z. Gong, and S. Aalami. 2019. “Deterministic and stochastic freeway capacity analysis based on weather conditions.” J. Transp. Eng. Part A: Syst. 145 (5): 1–9. https://doi.org/10.1061/JTEPBS.0000232.
INCOSE (International Council on Systems Engineering). 2019. “Guide to the systems engineering body of knowledge (SEBoK), v. 2.0.” Accessed June 1, 2019. https://www.sebokwiki.org.
INRIX. 2019. Global traffic scorecard. Kirkland, WA: INRIX.
Kamga, C., and M. A. Yazici. 2014. “Temporal and weather related variation patterns of urban travel time: Considerations and caveats for value of travel time, value of variability, and mode choice studies.” Transp. Res. Part C: Emerg. Technol. 45 (Aug): 4–16. https://doi.org/10.1016/j.trc.2014.02.020.
Lambert, J. H., S. A. Theckdi, and Q. Zhou. 2011. Land development risk analysis for multimodal transportation corridors. Richmond, VA: Virginia Center for Transportation Innovation and Research.
Lambert, J. H., and T. Turley. 2005. “Priority setting for the distribution of localized hazard protection.” Risk Anal. 25 (3): 745–752. https://doi.org/10.1111/j.1539-6924.2005.00611.x.
Leung, M., J. H. Lambert, and A. Mosenthal. 2004. “A risk-based approach to setting priorities in protecting bridges against terrorist attacks.” Risk Anal. 24 (4): 963–984. https://doi.org/10.1111/j.0272-4332.2004.00500.x.
List, G., B. Williams, and N. Rouphail. 2014. Establishing monitoring programs for travel time reliability. Washington DC: National Academy of Sciences.
Lomax, T. 1997. Quantifying congestion NCHRP 398. Washington, DC: NCHRP.
Lomax, T., D. Schrank, S. Turner, and R. Margiotta. 2003. Selecting travel reliability measures. College Station, TX: Texas Transportation Institute.
Marchetti, C. 1994. “Anthropological invariants in travel behavior.” Technol. Forecasting Soc. Change 47 (1): 75–88. https://doi.org/10.1016/0040-1625(94)90041-8.
Muriel-Villegas, J. E., K. C. Alvarez-Uribe, C. E. Patiño-Rodríguez, and J. G. Villegas. 2016. “Analysis of transportation networks subject to natural hazards—Insights from a Colombian case.” Reliab. Eng. Syst. Saf. 152 (Aug): 151–165. https://doi.org/10.1016/j.ress.2016.03.006.
National Academies of Sciences Engineering and Medicine. 2014a. Value of travel time reliability in transportation decision making: Proof of concept Maryland. Washington, DC: National Academies Press.
National Academies of Sciences Engineering and Medicine. 2014b. Incorporating travel time reliability into the highway capacity manual. Washington, DC: National Academies Press.
National Academies of Sciences Engineering and Medicine. 2014c. Value of travel time reliability in transportation decision making: proof of concept Maryland. Washington, DC: National Academies of Sciences Engineering and Medicine.
Office of the Federal Register. 2017. Title 23 highways: Federal register. Washington, DC: Office of the Federal Register.
Olszewski, P., T. Dybicz, K. Jamroz, W. Kustra, and A. Romanowska. 2018. “Assessing highway travel time reliability using probe vehicle data.” Transp. Res. Rec. 2672 (15): 118–130. https://doi.org/10.1177/0361198118796716.
Quenum, A., H. Thorisson, D. Wu, J. H. Lambert, A. Quenum, H. Thorisson, D. Wu, and J. H. Lambert. 2019. “Resilience of business strategy to emergent and future conditions.” J. Risk Res. 1–19. https://doi.org/10.1080/13669877.2018.1485172.
Rogerson, E. C., J. H. Lambert, and A. F. Johns. 2013. “Runway safety program evaluation with uncertainties of benefits and costs.” J. Risk Res. 16 (5): 523–539. https://doi.org/10.1080/13669877.2012.725674.
RStudio Team. 2018. RStudio: Integrated development environment for R. Boston: RStudio.
Skabardonis, A., P. Varaiya, and K. F. Petty. 2008. “Measuring recurrent and nonrecurrent traffic congestion.” Transp. Res. Rec. 1856 (1): 118–124. https://doi.org/10.3141/1856-12.
Sullivan, B. E. C., and U. T. Division. 1997. “New model for predicting freeway incidents and incident delays.” J. Transp. Eng. 123 (1): 267–275. https://doi.org/10.1061/(ASCE)0733-947X(1997)123:4(267).
Teng, K. Y., S. A. Thekdi, and J. H. Lambert. 2012. “Risk and safety program performance evaluation and business process modeling.” IEEE Trans. Syst. Man Cybern. Part A Syst. Humans 42 (6): 1504–1513. https://doi.org/10.1109/TSMCA.2012.2199306.
Thekdi, S. A., and J. H. Lambert. 2015. “Integrated risk management of safety and development on transportation corridors.” Reliab. Eng. Syst. Saf. 138 (Jun): 1–12. https://doi.org/10.1016/j.ress.2014.11.015.
Thomas, T., A. Mondschein, T. Osman, and B. D. Taylor. 2018. “Not so fast? Examining neighborhood-level effects of traffic congestion on job access.” Transp. Res. Part A 113 (Jul): 529–541. https://doi.org/10.1016/j.tra.2018.04.015.
Thorisson, H., and J. H. Lambert. 2017. “Multiscale identification of emergent and future conditions along corridors of transportation networks.” Reliab. Eng. Syst. Saf. 167 (Nov): 255–263. https://doi.org/10.1016/j.ress.2017.06.005.
Transportation Research Board. 2007. Traffic monitoring data, successful strategies in collection and analysis. Washington, DC: Transportation Research Board.
Transportation Research Board. 2012. Analytical procedures for determining the impacts of reliability mitigation strategies. Washington DC: Transportation Research Board.
Transportation Research Board. 2016. “Highway capacity manual” In A guide for multimodal mobility analysis. 6th ed. Washington, DC: National Academies Press.
Tsang, J. L., J. H. Lambert, and R. C. Patev. 2002. “Extreme event scenarios for planning of infrastructure projects.” J. Infrastruct. Syst. 8 (2): 42–48. https://doi.org/10.1061/(ASCE)1076-0342(2002)8:2(42).
Turner, S. M., W. L. Eisele, R. J. Benz, and J. Douglas. 1998. Travel time data collection handbook. Washington, DC: FHWA.
University of Maryland Center for Advanced Transportation Technology Laboratory. n.d. “The RITIS vehicle probe project suite.” Accessed January 11, 2019. https://pda.ritis.org/suite/.
USDOT. 2011. The value of travel time savings: Departmental guidance for conducting economic evaluations revision 2 introduction. Washington, DC: USDOT.
Virginia Transportation Research Council. 2017. Considerations for calculating arterial system performance measures in Virginia. Charlottesville, VA: Virginia Transportation Research Council.
Washburn, S., S. S. Washburn, and D. S. Kirschner. 2006. “Rural freeway level of service based on traveler perception rural.” Transp. Res. Rec. 1988 (1): 31–37. https://doi.org/10.1177/0361198106198800104.
Washington State Department of Transportation. 2013. Development of a freight benefit/cost methodology for project planning. Pullman, WA: Washington State Department of Transportation.
Xu, J., and J. H. Lambert. 2013. “Distributed travel time savings of a multiscale transportation access management program.” Environ. Syst. Dec. 33 (3): 362–375. https://doi.org/10.1007/s10669-013-9459-0.
Xu, J., J. H. Lambert, and C. J. Tucker. 2013. “Highway access safety program evaluation with uncertain parameters.” J. Transp. Eng. 140 (2): 1–11. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000631.
Zhao, W., E. Mccormack, D. J. Dailey, and E. Scharnhorst. 2013. “Using truck probe GPS data to identify and rank roadway bottlenecks.” J. Transp. Eng. 139 (Jan): 1–7. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000444.
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©2020 American Society of Civil Engineers.
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Received: Sep 12, 2019
Accepted: Apr 1, 2020
Published online: Jul 28, 2020
Published in print: Dec 1, 2020
Discussion open until: Dec 28, 2020
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