Impact of Platooning Connected and Automated Heavy Vehicles on Interstate Freeway Work Zone Operations
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 149, Issue 3
Abstract
Work zones pose mobility issues to the traveling public and safety challenges to travelers and road maintenance workers. These safety and mobility issues may be exacerbated by the presence of heavy vehicles. Connected and automated vehicle (CAV) technologies have been identified as a potential solution for these issues. This paper investigates the operational impacts of connected and automated heavy vehicles (CAHV) on freeway work zone operations on interstate highways. A microsimulation model, calibrated to empirical work zone field data, was used to study the operational impacts of CAHV platoons under various work zone and traffic conditions. It was found that, as the CAHV market penetration rate increases, the average work zone delay and queue length decreases. In addition, as the demand and heavy vehicle percentage increases, so do the benefits of using CAHV technology. For example, it was found that, when all heavy vehicles are classified as CAHV, the average flow rate is approximately 67% higher, and the maximum queue size and average delay decrease by approximately 97%. The methodology used in this paper will help transportation agencies as they design work zones to accommodate heavy vehicles equipped with CAV technologies.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The authors of this paper would like to thank Dr. Ernest Tufuor, Dr. Antonio-Hurtado Beltran, and the Nebraska Department of transportation for assistance in data collection. The contents of this paper reflect the views of the authors, who are responsible for the facts and accuracy of the information presented herein.
References
Abdulsattar, H., H. Abdulsattar, A. Mostafizi, M. R. Siam, and H. Wang. 2020. “Measuring the impacts of connected vehicles on travel time reliability in a work zone environment: An agent-based approach.” J. Intell. Transp. Syst. 24 (5): 421–436. https://doi.org/10.1080/15472450.2019.1573351.
Abdulsattar, H., A. Mostafizi, and H. Wang. 2018. “Surrogate safety assessment of work zone rear-end collisions in a connected vehicle environment: Agent-based modeling framework.” J. Transp. Eng. Part A: Syst. 144 (8): 04018038. https://doi.org/10.1061/JTEPBS.0000164.
Adebisi, A., Y. Liu, B. Schroeder, J. Ma, B. Cesme, A. Jia, and A. Morgan. 2020. “Developing highway capacity manual adjustment factors for connected and automated traffic on freeway segments.” Transp. Res. Rec. 2674 (10): 401–415. https://doi.org/10.1177/0361198120934797.
Appiah, J., B. Naik, L. Rilett, Y. Chen, and S. J. Kim. 2017. Development of a state of the art traffic microsimulation model for Nebraska. Lincoln, NE: Nebraska DOT.
Bart, V. L. 2020. “The impact of connected and automated vehicles on highway work zone traffic efficiency and safety: A simulation study.” Master’s thesis, Civil Engineering and Geosciences, Delft Univ. of Technology.
Bevly, D., et al. 2017. Heavy truck cooperative adaptive cruise control: Evaluation, testing, and stakeholder engagement for near term deployment: Phase two final report. Washington, DC: US DOT.
Birgisson, B., C. Morgan, M. Yarnold, J. Warner, B. Glover, M. Steadman, S. Srinivasa, S. Cai, and D. Lee. 2020. Evaluate potential impacts, benefits, impediments, and solutions of automated trucks and truck platooning on Texas highway infrastructure. College Station, TX: Texas A&M Transportation Institute.
Bujanovic, P., and T. Lochrane. 2018. “Capacity predictions and capacity passenger car equivalents of platooning vehicles on basic segments.” J. Transp. Eng. Part A: Syst. 144 (10): 04018063. https://doi.org/10.1061/JTEPBS.0000188.
Dehman, A., and B. Farooq. 2021. “Are work zones and connected automated vehicles ready for a harmonious coexistence? A scoping review and research Agenda.” Transp. Res. Part C: Emerging Technol. 133 (Dec): 103422. https://doi.org/10.1016/j.trc.2021.103422.
Dong, S., H. Wang, D. Hurwitz, G. Zhang, and J. Shi. 2015. “Nonparametric modeling of vehicle-type-specific headway distribution in freeway work zones.” J. Transp. Eng. 141 (11): 05015004. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000788.
Egami, C. Y., M. L. Mon-Ma, J. R. Setti, and L. R. Rilett. 2006. “Automatic calibration of two-lane highway traffic simulation models using a genetic algorithm.” In Applications of advanced technology in transportation, 510–515. Reston, VA: ASCE.
FHWA (Federal Highway Administration). 2006. QuickZone. Washhington, DC: FHWA.
FHWA (Federal Highway Administration). 2012. Urban congestion trends. Washhington, DC: FHWA.
Fitzpatrick, D., G. Cordahi, L. O’Rourke, C. Ross, A. Kumar, and D. Bevly. 2016. Challenges to connected vehicle and automated vehicle applications in truck freight operations. Washington, DC: Transportation Research Board.
Goñi-Ros, B., W. J. Schakel, A. E. Papacharalampous, M. Wang, V. L. Knoop, I. Sakata, B. van Arem, and S. P. Hoogendoorn. 2019. “Using advanced adaptive cruise control systems to reduce congestion at sags: An evaluation based on microscopic traffic simulation.” Transp. Res. Part C: Emerging Technol. 102 (May): 411–426. https://doi.org/10.1016/j.trc.2019.02.021.
Greer, L., J. L. Fraser, D. Hicks, M. Mercer, and K. Thompson. 2018. Thompson. Intelligent transportation systems benefits, costs, and lessons learned: Update report. Washhington, DC: USDOT.
Guanetti, J., Y. Kim, and F. Borrelli. 2018. “Control of connected and automated vehicles: State of the art and future challenges.” Annu. Rev. Control 45 (Jan): 18–40. https://arxiv.org/abs/1804.03757.
Hallmark, S., D. Veneziano, and T. Litteral. 2019. Preparing local agencies for the future of connected and autonomous vehicles.. St. Paul, MN: Minnesota DOT.
Haque, M. S. 2022. “Improved traffic analysis methodology for lane closure on two-lane highway work zone.” Ph.D. dissertation, Dept. of Civil and Environmental Engineering, Univ. of Nebraska-Lincoln.
Haque, M. S., L. Zhao, L. R. Rilett, and E. O. A. Tufuor. 2022. “Calibration and validation of a microsimulation model of lane closures on two-lane highway work zone.” Trans. Res. Rec. 03611981221119456. https://doi.org/10.1177/03611981221119456.
HCM-6 (Highway Capacity Manual). 2016. Highway capacity manual: A guide for multimodal mobility analysis. 6th ed. Washington, DC: Transportation Research Board.
Hoque, M. M., Q. Lu, A. Ghiasi, and C. Xin. 2021. “Highway cost analysis for platooning of connected and autonomous trucks.” J. Transp. Eng., Part A: Syst. 147 (1): 04020148. https://doi.org/10.1061/JTEPBS.0000474.
Hu, X., and J. Sun. 2019. “Trajectory optimization of connected and autonomous vehicles at a multilane freeway merging area.” Transp. Res. Part C: Emerging Technol. 101 (Apr): 111–125. https://doi.org/10.1016/j.trc.2019.02.016.
Hurtado-Beltran, A., and L. R. Rilett. 2021. “Impact of CAV truck platooning on HCM-6 capacity and passenger car equivalent values.” J. Transp. Eng. Part A: Syst. 147 (2): 04020159. https://doi.org/10.1061/JTEPBS.0000492.
Janssen, R., H. Zwijnenberg, I. Blankers, and J. Kruijff. 2015. Truck platooning driving the future of transportation. Hague, Netherlands: Netherlands Organization for Applied Scientific Research.
Kang, S., H. Ozer, and I. L. Al-Qadi. 2019. “Benefit cost analysis (BCA) of autonomous and connected truck (ACT) technology and platooning.” In Airfield and highway pavements: Innovation and sustainability in highway and airfield pavement technology, 174–182. Reston, VA: ASCE.
Kittelson & Associates. 2019. “HCM CAV capacity adjustment factors: Capacity adjustment factors for connected and autonomous vehicles in the highway capacity manual.” In Proc., Present at the 17th National Transportation Planning Applications Conf. Salem, OR: Oregon DOT.
Kramer, O. 2017. Vol. 679 of Genetic algorithm essentials. New York: Springer.
Lee, S., O. Cheol, and G. Lee. 2021. “Impact of automated truck platooning on the performance of freeway mixed traffic flow.” J. Adv. Transp. 2021 (Jan): 8888930. https://doi.org/10.1155/2021/8888930.
Letter, C., and L. Elefteriadou. 2017. “Efficient control of fully automated connected vehicles at freeway merge segments.” Transp. Res. Part C: Emerging Technol. 80 (Jul): 190–205. https://doi.org/10.1016/j.trc.2017.04.015.
Majeed, A., and Z. Li. 2022. “Enhancing work zone capacity by a cooperative late merge system using decentralized and centralized control strategies.” J. Transp. Eng. Part A: Syst. 148 (2): 04021107. https://doi.org/10.1061/JTEPBS.0000632.
McHale, G. 2019. “FHWA level 1 truck platooning research program.” In Proc., Presentation at the Automated Vehicles Symp., 2019, 15–18. Washington, DC: US DOT.
Melson, C. L., M. W. Levin, B. E. Hammit, and S. D. Boyles. 2018. “Dynamic traffic assignment of cooperative adaptive cruise control.” Transp. Res. Part C: Emerging Technol. 90 (May): 114–133. https://doi.org/10.1016/j.trc.2018.03.002.
Morando, M. M., Q. Tian, L. T. Truong, and H. L. Vu. 2018. “Studying the safety impact of autonomous vehicles using simulation-based surrogate safety measures.” J. Adv. Transp. 2018 (Apr): 11. https://doi.org/10.1155/2018/6135183.
NTS (National Transportation Statistics). 2000. National transportation statistics 2000. Appendix A Truck Profile. Washington, DC: US DOT.
NWZS (National Work Zone Safety). 2021. “National work zone safety. Information clearinghouse.” Accessed April 29, 2021. https://www.workzonesafety.org/crash-information/work-zone-fatal-crashes-fatalities/#national.
Offei, E., and R. Young. 2014. Quantifying the impact of large percent trucks proportion on rural freeways. Laramie, WY: Univ. of Wyoming.
Pu, L., Y. Lin, L. Wang, and X. Yang. 2017. “Variable speed limit control for delay and crash reductions at freeway work zone area.” J. Transp. Eng. Part A: Syst. 143 (12): 04017062. https://doi.org/10.1061/JTEPBS.0000099.
RADAR. 2021. “Types of radar.” Accessed July 7, 2021. https://compass-seaschool.co.uk/types-of-radar-digital-quantum-broadband-and-doppler/.
RITIS (Regional Integrated Transportation Information System). 2021. “Regional integrated transportation information system.” Accessed April 28, 2021. https://ritis.org/intro.
Schoen, J. M., J. A. Bonneson, C. Zhu, B. Safi, A. Schroeder, C. H. Hajbabaie, N. Yeom, Y. Rouphail, W. Wang, and Y. Zou. 2015. NCHRP Project 3-107: Work Zone Capacity Methods for the Highway Capacity Manual. Raleigh, NC: Institute for Transportation Research and Education.
Shi, L., and P. Prevedouros. 2016. “Autonomous and connected cars: HCM estimates for freeways with various market penetration rates.” Proc. Transp. Res. 15 (Jan): 389–402. https://doi.org/10.1016/j.trpro.2016.06.033.
Spasovic, L. N., D. J. Bensenski, and J. Lee. 2019. Impact assessments of automated truck platooning on highway traffic flow and adjacent drivers. Piscataway, NJ: Rutgers Univ.
SPEED-MAC 2.0. 2021 “VER-MAC.” Accessed July 7, 2021. https://www.streetsmartrental.com/wp-content/uploads/speed-mac-2-0-product-sheet-ver-mac-007.pdf.
Spiegelman, C., E. Sug Park, and L. R. Rilett. 2010. Transportation statistics and microsimulation. Boca Raton, FL: CRC Press.
Sukennik, P. 2018. Micro-simulation guide for automated vehicles. Karlsruhe, Germany: PTV Group.
Sukennik, P. 2020. “CoEXist- Modeling autonomous vehicle with PTV Vissim.” Accessed November 24, 2021. https://company.ptvgroup.com/en-us/coexist-modeling-autonomous-vehicle-with-ptv-vissim.
TxDOT (Texas DOT). 2016. Texas truck flow band map. Colleage Station, TX: Texas DOT.
Ullman, G., and J. Schroeder. 2014. Mitigating work zone safety and mobility challenges through intelligent transportation systems: Case studies. Washington, DC: Federal Highway Administration.
WAVETRONIX. 2021. “SmartSensor HD.” Accessed July 7, 2021. https://www.wavetronix.com/products/en/3.
Yeom, C., N. M. W. Rouphail, W. Rasdorf, and B. J. Schroeder. 2016. “Simulation guidance for calibration of freeway lane closure capacity.” Transp. Res. Rec. 2553 (1): 82–89. https://doi.org/10.3141/2553-09.
Yu, M., and W. D. Fan. 2019. “Optimal variable speed limit control in connected autonomous vehicle environment for relieving freeway congestion.” J. Transp. Eng. Part A: Syst. 145 (4): 04019007. https://doi.org/10.1061/JTEPBS.0000227.
Zhao, L., L. Rilett, and M. S. Haque. 2022. “Calibration and validation methodology for simulation models of intelligent work zones.” Transp. Res. Rec. 2676 (5): 500–513. https://doi.org/10.1177/03611981221082591.
Zhou, J., L. E. Rilett, and E. Jones. 2019. “Estimating passenger car equivalent using the HCM-6 passenger cars equivalent methodology on four-lane level freeway segments in Western US.” Transp. Res. Rec. 2673 (11): 529–545. https://doi.org/10.1177/0361198119851448.
Zou, Y., and X. Qu. 2018. “On the impact of connected automated vehicles in freeway work zones: A cooperative cellular automata model based approach.” J. Intell. Connected Veh. 1 (1): 1–14. https://doi.org/10.1108/JICV-11-2017-0001.
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Published In
Journal of Transportation Engineering, Part A: Systems
Volume 149 • Issue 3 • March 2023
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Mar 14, 2022
Accepted: Oct 27, 2022
Published online: Dec 30, 2022
Published in print: Mar 1, 2023
Discussion open until: May 30, 2023
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