How Connected and Automated Vehicle–Exclusive Lanes Affect On-Ramp Junctions
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 147, Issue 2
Abstract
Connected and automated vehicle (CAV) exclusive lanes are an important application of intelligent transportation technologies on highways. However, current research on CAV exclusive lanes mainly focuses on basic road segments rather than on on-ramp junctions. This paper analyzed the impact of CAV exclusive lanes on the traffic capacity of on-ramp junctions through theoretical analysis and numerical simulation. This paper established a capacity model for heterogeneous traffic consisting of CAVs and manual vehicles (MVs) considering the CAV degradation mechanism. Three key parameters, namely the CAV penetration rate, the proportion of CAVs on regular lanes, and a CAV platoon coefficient, were introduced into the heterogeneous traffic capacity model. Based on this input, the relationship between traffic capacity and the three parameters was analyzed on regular lanes. The critical CAV penetration rate at which a CAV exclusive lane reaches saturation was expressed mathematically. An on-ramp junction scenario with a CAV exclusive lane was simulated numerically with microscopic heterogeneous traffic flow models. Experimental results showed that congestion at the junction area no longer spread upstream after the CAV penetration rate exceeded 70% without CAV exclusive lanes. However, for the case in which a CAV exclusive lane was used, CAVs on the exclusive lane traveled quickly through the junction and effectively relieved traffic congestion when the CAV penetration rate reached 40%. The results also showed that a long acceleration lane slightly reduced the CAV platoon coefficient. In addition, a CAV exclusive lane improved traffic capacity when the CAV penetration rate was higher than 30%, regardless of the length of the acceleration lane.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
All data, models, and code generated or used during the study appear in the published article.
Acknowledgments
This paper is supported by the National Key Research and Development Program of China (No. 2019YFB1600200).
References
Bujanovic, P., and T. Lochrane. 2018. “Capacity predictions and capacity passenger car equivalents of platooning vehicles on basic segments.” J. Transp. Eng., Part A: Systems 144 (10): 04018063. https://doi.org/10.1061/JTEPBS.0000188.
Chen, D., S. Ahn, M. Chitturi, and D. A. Noyce. 2017. “Towards vehicle automation: Roadway capacity formulation for traffic mixed with regular and automated vehicles.” Transp. Res. Part B: Methodol. 100 (Jun): 196–221. https://doi.org/10.1016/j.trb.2017.01.017.
Dong, C., H. Wang, Y. Li, Y. Liu, and Q. Chen. 2019. “Economic comparison between vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) at freeway on-ramps based on microscopic simulations.” IET Intel. Transport Syst. 13 (11): 1726–1735. https://doi.org/10.1049/iet-its.2018.5537.
Ge, J. I., S. S. Avedisov, C. R. He, W. B. Qin, M. Sadeghpour, and G. Orosz. 2018. “Experimental validation of connected automated vehicle design among human-driven vehicles.” Transp. Res. Part C: Emerging Technol. 91 (Jun): 335–352. https://doi.org/10.1016/j.trc.2018.04.005.
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.
Goodall, N. J., B. B. Park, and B. L. Smith. 2014. “Microscopic estimation of arterial vehicle positions in a low-penetration-rate connected vehicle environment.” J. Transp. Eng. 140 (10): 04014047. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000716.
Jiang, R., and Q. S. Wu. 2002. “Cellular automata models for synchronized traffic flow.” J. Phys. A: Math. Gen. 36 (2): 381. https://doi.org/10.1088/0305-4470/36/2/307.
Kesting, A., M. Treiber, M. Schönhof, and D. Helbing. 2008. “Adaptive cruise control design for active congestion avoidance.” Transp. Res. Part C: Emerging Technol. 16 (6): 668–683. https://doi.org/10.1016/j.trc.2007.12.004.
Lee, J., and J. H. Kim. 2019. “Phantom traffic: Platoon formed at low traffic density.” J. Transp. Eng. 145 (2): 04018082. https://doi.org/10.1061/JTEPBS.0000206.
Li, Y., H. Wang, W. Wang, L. Xing, S. Liu, and X. Wei. 2017. “Evaluation of the impacts of cooperative adaptive cruise control on reducing rear-end collision risks on freeways.” Accid. Anal. Prev. 98 (Jan): 87–95. https://doi.org/10.1016/j.aap.2016.09.015.
Liu, Y., H. Wang, C. Dong, and Q. Chen. 2020. “A car-following data collecting method based on binocular stereo vision.” IEEE Access 8 (1): 25350–25363. https://doi.org/10.1109/ACCESS.2020.2965833.
Ma, K., and H. Wang. 2019. “Influence of exclusive lanes for connected and autonomous vehicles on freeway traffic flow.” IEEE Access 7 (1): 50168–50178. https://doi.org/10.1109/ACCESS.2019.2910833.
McDougall, D., and R. O. Moore. 2017. “Optimal strategies for the control of autonomous vehicles in data assimilation.” Physica D 351–352 (Aug): 42–52. https://doi.org/10.1016/j.physd.2017.04.001.
Milanés, V., and S. E. Shladover. 2014. “Modeling cooperative and autonomous adaptive cruise control dynamic responses using experimental data.” Transp. Res. Part C: Emerging Technol. 48 (Nov): 285–300. https://doi.org/10.1016/j.trc.2014.09.001.
Pueboobpaphan, R., and B. Van Arem. 2010. “Driver and vehicle characteristics and platoon and traffic flow stability: Understanding the relationship for design and assessment of cooperative adaptive cruise control.” Transp. Res. Rec. 2189 (1): 89–97. https://doi.org/10.3141/2189-10.
Qin, Y., H. Wang, and B. Ran. 2018. “Impact of connected and automated vehicles on passenger comfort of traffic flow with vehicle-to-vehicle communications.” KSCE J. Civ. Eng. 23 (2): 821–832. https://doi.org/10.1007/s12205-018-1990-6.
Shladover, S. E., D. Su, and X.-Y. Lu. 2012. “Impacts of cooperative adaptive cruise control on freeway traffic flow.” Transp. Res. Rec. 2324 (1): 63–70. https://doi.org/10.3141/2324-08.
Stern, R. E., et al. 2018. “Dissipation of stop-and-go waves via control of autonomous vehicles: Field experiments.” Transp. Res. Part C: Emerging Technol. 89 (Apr): 205–221. https://doi.org/10.1016/j.trc.2018.02.005.
Sun, Y., H. Ge, and R. Cheng. 2018. “An extended car-following model under V2V communication environment and its delayed-feedback control.” Physica A 508 (Oct): 349–358. https://doi.org/10.1016/j.physa.2018.05.102.
Vander Laan, Z., and K. F. Sadabadi. 2017. “Operational performance of a congested corridor with lanes dedicated to autonomous vehicle traffic.” Int. J. Transp. Sci. Technol. 6 (1): 42–52. https://doi.org/10.1016/j.ijtst.2017.05.006.
Wang, C., S. Gong, A. Zhou, T. Li, and S. Peeta. 2020. “Cooperative adaptive cruise control for connected autonomous vehicles by factoring communication-related constraints.” Transp. Res. Procedia 38 (1): 242–262. https://doi.org/10.1016/j.trpro.2019.05.014.
Wang, H., Y. Qin, W. Wang, and J. Chen. 2019. “Stability of CACC-manual heterogeneous vehicular flow with partial CACC performance degrading.” Transportmetrica B: Transp. Dyn. 7 (1): 788–813. https://doi.org/10.1080/21680566.2018.1517058.
Wang, M. 2018. “Infrastructure assisted adaptive driving to stabilise heterogeneous vehicle strings.” Transp. Res. Part C: Emerging Technol. 91 (Jun): 276–295. https://doi.org/10.1016/j.trc.2018.04.010.
Yuan, Y.-M., R. Jiang, M.-B. Hu, Q.-S. Wu, and R. Wang. 2009. “Traffic flow characteristics in a mixed traffic system consisting of ACC vehicles and manual vehicles: A hybrid modeling approach.” In Proc., 15th World Congress on Intelligent Transport Systems and ITS America’s 2008 Annual Meeting. Washington, DC: Intelligent Transportation System America.
Zheng, L., P. J. Jin, and H. Huang. 2015. “An anisotropic continuum model considering bi-directional information impact.” Transp. Res. Part B: Methodol. 75 (May): 36–57. https://doi.org/10.1016/j.trb.2015.02.011.
Zhu, W.-X., and L.-D. Zhang. 2018. “A new car-following model for autonomous vehicles flow with mean expected velocity field.” Physica A 492 (Feb): 2154–2165. https://doi.org/10.1016/j.physa.2017.11.133.
Information & Authors
Information
Published In
Copyright
© 2020 American Society of Civil Engineers.
History
Received: Nov 14, 2019
Accepted: Sep 11, 2020
Published online: Nov 27, 2020
Published in print: Feb 1, 2021
Discussion open until: Apr 27, 2021
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.