Longitudinal Performance Assessment of Traffic Signal System Impacted by Long-Term Interstate Construction Diversion Using Connected Vehicle Data — Oak Academic Publishing
Research ArticleOpen AccessGoogle Scholar indexed
Longitudinal Performance Assessment of Traffic Signal System Impacted by Long-Term Interstate Construction Diversion Using Connected Vehicle Data
Local arterials can be significantly impacted by diversions from adjacent work zones. These diversions often occur on unofficial detour routes due to guidance received on personal navigation devices. Often, these routes do not have sufficien t sensing or communication equipment to obtain infrastructure-based tra ffic signal performance measures, so other data sources are required to identify locations being significantly affected by diversions. This paper examines the network impact caused by the start of an 18-month closure of the I-65/70 interchange (North Split), which usually serves approximately 214,000 vehicles per day in Indianapolis, IN. In anticipation of some proportion of the public diverting from official detour routes to local streets, a connected vehicle monitoring program was established to provide daily performances measures for over 100 intersections in the area without the need for vehicle sensing equipment. This study reports on 13 of the most impacted signals on an alternative arterial to identify locations and time of day where operations are most degraded, so that decision makers have quantitative information to make informed adjustments to the system. Individual vehicle movements at the studied locations are analyzed to estimate changes in volume, split failures, downstream blockage, arrivals on green, and travel times. Over 130,000 trajectories were analyzed in an 11-week period. Weekly afternoon peak period volumes increased by approximately 455%, split failures increased 3%, downstream blockage increased 10%, arrivals on green decreased 16%, and travel time increase 74%. The analysis performed in this paper will serve as a framework for any agency that wants to assess traffic signal performance at hundreds of locations with little or no existing sensing or communication infrastructure to prioritize tactical retiming and/or longer-term infrastructure investments.
KeywordsTraffic Signal Performance MeasuresConnected VehicleLongitudinal StudyBig Data
Schrank, D., Albert, L., Eisele, B. and Lomax, T. (2021) 2021 Urban Mobility Report. Texas A&M Transportation Institute, College Station.
Federal Highway Administration, Office of Operations (2017) Making Work Zones Work Better. https://ops.fhwa.dot.gov/aboutus/one_pagers/wz.htm
Lochrane, T.W.P., Al-Deek, H., Paracha, J. and Scriba, T. (2013) Understanding Driver Behavior in Work Zones. Public Roads, 76, p. https://www.fhwa.dot.gov/publications/publicroads/13marapr/04.cfm
Li, X., Cao, Y., Zhao, X. and Xie, D. (2015) Drivers’ Diversion from Expressway under Real Traffic Condition Information Shown on Variable Message Signs. KSCE Journal of Civil Engineering, 19, 2262-2270. https://doi.org/10.1007/s12205-014-0692-y
Gan, H. and Ye, X. (2012) Urban Freeway Users’ Diversion Response to Variable Message Sign Displaying the Travel Time of Both Freeway and Local Street. IET Intelllgent Transport Systemsgent, 6, 78-86. https://doi.org/10.1049/iet-its.2011.0070
Gan, H. (2013) Investigation of Driver Response to the Enhanced Urban Freeway Variable Message Sign Information. KSCE Journal of Civil Engineering, 17, 1455-1461. https://doi.org/10.1007/s12205-013-0231-2
Jou, R.C., Lam, S.H., Liu, Y.H. and Chen, K.H. (2005) Route Switching Behavior on Freeways with the Provision of Different Types of Real-Time Traffic Information. Transportation Research Part A: Policy and Practice, 39, 445-461. https://doi.org/10.1016/j.tra.2005.02.004
Chorus, C.G., Molin, E.J.E. and van Wee, B. (2006) Use and Effects of Advanced Traveller Information Services (ATIS): A Review of the Literature. Transport Reviews, 26, 127-149. https://doi.org/10.1080/01441640500333677
Petrella, M. and Lappin, J. (2004) Comparative Analysis of Customer Response to Online Traffic Information in Two Cities Los Angeles, California, and Seattle, Washington. Transportation Research Record, 1886, 10-17. https://doi.org/10.3141%2F1886-02
Yim, Y., Khattak, A.J. and Raw, J. (2002) Traveler Response to New Dynamic Information Sources: Analyzing Corridor and Areawide Behavioral Surveys. Transportation Research Record, 1803, 66-75. https://doi.org/10.3141%2F1803-10
Liang, Z. and Wakahara, Y. (2014) Real-Time Urban Traffic Amount Prediction Models for Dynamic Route Guidance Systems. EURASIP Journal on Wireless Communications and Networking, 2014, Article No. 85. https://doi.org/10.1186/1687-1499-2014-85
Memarian, A., Rosenberger, J.M., Mattingly, S.P., Williams, J.C. and Hashemi, H. (2019) An Optimization-Based Traffic Diversion Model during Construction Closures. Computer-Aided Civil and Infrastructure Engineering, 34, 1087-1099. https://doi.org/10.1111/mice.12491
Effinger, J., Horowitz, A.J., Liu, Y. and Shaw, J. (2013) Bluetooth Vehicle Reidentification for Analysis of Work Zone Diversion. Presented at 92nd Annual Meeting of Transportation Research Board, Washington DC, 13-17 January 2013, 1-15.
Hainen, A.M., Wasson, J.S., Hubbard, S.M.L., Remias, S.M., Farnsworth, G.D. and Bullock, D.M. (2011) Estimating Route Choice and Travel Time Reliability with Field Observations of Bluetooth Probe Vehicles. Transportation Research Record, 2256, 43-50. https://doi.org/10.3141%2F2256-06
Haseman, R.J., Wasson, J.S. and Bullock, D.M. (2010) Real-Time Measurement of Travel Time Delay in Work Zones and Evaluation Metrics Using Bluetooth Probe Tracking. Transportation Research Record, 2169, 40-53. https://doi.org/10.3141%2F2169-05
McNamara, M., Li, H., Remias, S., Richardson, L., Cox, E., Horton, D., et al. (2015) Using Real-Time Probe Vehicle Data to Manage Unplanned Detour Routes. ITE Journal, 85, 32-37.
Day, C., Bullock, D.M., Li, H., Remias, S.M., Hainen, A.M., Freije, R.S., et al. (2014) Performance Measures for Traffic Signal Systems: An Outcome-Oriented Approach. Purdue University, West Lafayette. https://doi.org/10.5703/1288284315333
Federal Highway Administration (FHWA) (2019) Every Day Counts: An Innovation Partnership with States. Federal Highway Administration, Washington DC.
Day, C., Bullock, D., Li, H., Lavrenz, S., Smith, W.B.B. and Sturdevant, J. (2015) Integrating Traffic Signal Performance Measures into Agency Business Processes. Purdue University, West Lafayette. https://doi.org/10.5703/1288284316063
Zhao, Y., Zheng, J., Wong, W., Wang, X., Meng, Y. and Liu, H.X. (2019) Estimation of Queue Lengths, Probe Vehicle Penetration Rates, and Traffic Volumes at Signalized Intersections Using Probe Vehicle Trajectories. Transportation Research Record, 2673, 660-670. https://doi.org/10.1177%2F0361198119856340
Cetin, M. (2012) Estimating Queue Dynamics at Signalized Intersections from Probe Vehicle Data: Methodology Based on Kinematic Wave Model. Transportation Research Record, 2315, 164-172. https://doi.org/10.3141%2F2315-17
Li, H., Mackey, J., Luker, M., Taylor, M. and Bullock, D.M. (2019) Application of High-Resolution Trip Trace Stitching to Evaluate Traffic Signal System Changes. Transportation Research Record, 2673, 188-201. https://doi.org/10.1177%2F0361198119841043
Zhang, K., Jia, N., Zheng, L. and Liu, Z. (2019) A Novel Generative Adversarial Network for Estimation of Trip Travel Time Distribution with Trajectory Data. Transportation Research Part C: Emerging Technologies, 108, 223-244. https://doi.org/10.1016/j.trc.2019.09.019
Transportation Research Board (TRB) (2010) Highway Capacity Manual 2010. National Research Council (NRC), Washington DC.
Saldivar-Carranza, E., Li, H., Mathew, J., Hunter, M., Sturdevant, J. and Bullock, D.M. (2021) Deriving Operational Traffic Signal Performance Measures from Vehicle Trajectory Data. Transportation Research Record, Article ID: 036119812110067. https://doi.org/10.1177%2F03611981211006725
Saldivar-Carranza, E.D. (2021) Scalable Operational Traffic Signal Performance Measures from Vehicle Trajectory Data. Purdue University, West Lafayette. https://doi.org/10.25394/PGS.14371691.v1
Waddell, J.M., Remias, S.M. and Kirsch, J.N. (2020) Characterizing Traffic-Signal Performance and Corridor Reliability Using Crowd-Sourced Probe Vehicle Trajectories. Journal of Transportation Engineering, Part A: Systems, 146, Article ID: 04020053. https://doi.org/10.1061/JTEPBS.0000378
Huang, J., Li, G., Wang, Q. and Yu, H. (2013) Real Time Delay Estimation for Signalized Intersection Using Transit Vehicle Positioning Data. 2013 13th International Conference on ITS Telecommunications, Tampere, 5-7 November 2013, 216-221. https://doi.org/10.1109/ITST.2013.6685548
Day, C.M., Li, H., Richardson, L.M., Howard, J., Platte, T., Sturdevant, J.R., et al. (2017) Detector-Free Optimization of Traffic Signal Offsets With Connected Vehicle Data. Transportation Research Record: Journal of the Transportation Research Board, 2620, 54-68. https://doi.org/10.3141%2F2620-06
Saldivar, E., Carranza, D., Li, H. and Bullock, D.M. (2021) Identifying Vehicle Turning Movements at Intersections from Trajectory Data. IEEE Xplore.