Impact of Fundamental Elements of Connected and Autonomous Technology on Right-Turn Gap Acceptance Behavior at an Uncontrolled Intersection
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 149, Issue 3
Abstract
Different original equipment manufacturers (OEMs) provide different connected and autonomous vehicle (CAV) solutions. However, previous studies that estimated the impact of CAV on driving behaviors assumed CAVs are identical, with an integrated form of technologies. In this study, a simulation was conducted to investigate how different fundamental elements of CAV technology (i.e., communication range, number of vehicular interactions, and car-following distance) affect right-turn gap acceptance behavior at unsignalized intersections. The results of the statistical analysis, critical gaps comparison, platooning analysis, and logistic regression revealed that (1) all elements increase the lag acceptance rate compared with all human-driven vehicles; (2) a longer communication range and more vehicular interactions make CAVs turn conservatively from a minor road, causing the critical gap to increase; (3) a shorter car-following distance causes CAVs to generate longer platoons and shorter gaps on a major road, which decreases acceptance probability; and (4) CAVs with a shorter car-following distance on a minor road are more aggressive in accepting gap/lag, causing the critical gap to decrease and acceptance probability to increase. The study conducted an impact analysis of CAV technologies from a novel perspective, and the results can be used as a technical report of CAV’s performance to help build transportation policies.
Get full access to this article
View all available purchase options and get full access to this article.
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 thank Dr. Dominique Lord and Mr. Xiang Fang for leading the field data collection in CVEN 617—Traffic Engineering: Characteristics at Texas A&M. The authors confirm the contributions to the study: conception and design: Yongxin Peng and Xiaoyu Guo; analysis and interpretation of results: Yongxin Peng; draft manuscript preparation: Yongxin Peng and Xiaoyu Guo; and proofreading: Yongxin Peng, Xiaoyu Guo, Manze Guo, and Guohua Song. All authors reviewed the results and approved the final version of the manuscript.
References
5GAA (5G Automotive Association). 2022. “Exploring the technology: C-V2X.” Accessed May 28, 2022. https://5gaa.org/5g-technology/c-v2x/.
Ahmed, A., A. F. M. Sadullah, and A. Shukri Yahya. 2016. “Field study on the behavior of right-turning vehicles in Malaysia and their contribution on the safety of unsignalized intersections.” Transp. Res. Part F Traffic Psychol. Behav. 42 (Oct): 433–446. https://doi.org/10.1016/j.trf.2015.03.006.
Alanazi, F. K. 2021. Improving operation efficiency of a major-minor T-intersection in mixed traffic with connected automated vehicles. Akron, OH: Univ. of Akron.
Aria, E. 2016. “Investigation of automated vehicle effects on drivers’ behavior and traffic performance.” Transp. Res. Procedia 15 (Jan): 761–770. https://doi.org/10.1016/j.trpro.2016.06.063.
Arvin, R., A. J. Khattak, M. Kamrani, and J. Rio-Torres. 2021. “Safety evaluation of connected and automated vehicles in mixed traffic with conventional vehicles at intersections.” J. Intell. Transp. Syst. 25 (2): 170–187. https://doi.org/10.1080/15472450.2020.1834392.
Asadi, F. E., A. K. Anwar, and J. C. Miles. 2019. Investigating the potential transportation impacts of connected and autonomous vehicles, 1–6. New York: IEEE.
Beanland, V., M. G. Lenné, N. Candappa, and B. Corben. 2013. “Gap acceptance at stop-controlled T-intersections in a simulated rural environment.” Transp. Res. Part F Traffic Psychol. Behav. 20 (Sep): 80–89. https://doi.org/10.1016/j.trf.2013.05.006.
Brilon, W., R. Koenig, and R. J. Troutbeck. 1999. “Useful estimation procedures for critical gaps.” Transp. Res. Part A Policy Pract. 33 (3): 161–186. https://doi.org/10.1016/S0965-8564(98)00048-2.
Brown, B. 2017. “Evidence stacks up in favor of self-driving cars in 2016 NHTSA fatality report.” Digital Trends. Accessed August 13, 2020. https://www.digitaltrends.com/cars/2016-nhtsa-fatality-report/.
Center for Sustainable Systems. 2021. Autonomous vehicles factsheet. Pub. No. CSS16-18. Ann Arbor, MI: Univ. of Michigan.
Chen, X., Y. Qi, and G. Liu. 2013. “Empirical study of gap-acceptance behavior of right-turn-on-red drivers on dual right-turn lanes.” J. Transp. Eng. 139 (2): 173–180. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000489.
Darbha, S., S. Konduri, and P. R. Pagilla. 2019. “Benefits of V2V communication for autonomous and connected vehicles.” IEEE Trans. Intel. Transp. Syst. 20 (5): 1954–1963. https://doi.org/10.1109/TITS.2018.2859765.
Deluka Tibljaš, A., T. Giuffrè, S. Surdonja, and S. Trubia. 2018. “Introduction of autonomous vehicles: Roundabouts design and safety performance evaluation.” Sustainability 10 (4): 1060. https://doi.org/10.3390/su10041060.
Dutta, M., and M. A. Ahmed. 2018. “Gap acceptance behavior of drivers at uncontrolled T-intersections under mixed traffic conditions.” J. Mod. Transport. 26 (2): 119–132. https://doi.org/10.1007/s40534-017-0151-9.
Federal Communications Commission. 2020. First report and order, further notice of proposed rulemaking and order of proposed modification, 4–5. Washington, DC: Engineering and Technology of Federal Communication Commission.
FMCAS (Federal Motor Carrier Safety Administration). 2016. 2016 CMV traffic safety fact sheet, traffic safety facts research note, 72. Washington, DC: National Highway Traffic Safety Administration.
Friedman, J., T. Hastie, R. Tibshirani, B. Narasimhan, K. Tay, N. Simon, and J. Qian. 2021. Package ‘glmnet.’ Lasso and elastic-net regularized generalized linear models. R(>=3.6.0). Sacramento, CA: Foundation for Open Access Statistics.
Ginsburg, B. P., K. Subburaj, S. Samala, K. Ramasubramanian, J. Singh, S. Bhatara, S. Murali, D. Breen, M. Moallem, and B. Leonard. 2018. A multimode 76-to-81GHz automotive radar transceiver with autonomous monitoring, 158–160. New York: IEEE.
Grace-Martin, K. n.d. “Interpreting interactions in regression.” The Analysis Factor. Accessed April 30, 2022. https://www.theanalysisfactor.com/interpreting-interactions-in-regression/.
Guo, R., X. Wang, and W. Wang. 2014. “Estimation of critical gap based on Raff’s definition.” Comput. Intell. Neurosci. 2014 (Jan): e236072. https://doi.org/10.1155/2014/236072.
Horswill, M. S., A. Hill, and L. Silapurem. 2020. “The development and validation of video-based measures of drivers’ following distance and gap acceptance behaviours.” Accid. Anal. Prev. 146 (Oct): 105626. https://doi.org/10.1016/j.aap.2020.105626.
Hunt, M., D. N. Harper, and C. Lie. 2011. “Mind the gap: Training road users to use speed and distance when making gap-acceptance decisions.” Accid. Anal. Prev. 43 (6): 2015–2023. https://doi.org/10.1016/j.aap.2011.05.020.
Keboola. 2020. “The ultimate guide to logistic regression for machine learning.” Accessed September 17, 2021. https://www.keboola.com/blog/logistic-regression-machine-learning.
Kesting, A., M. Treiber, and D. Helbing. 2010. “Enhanced intelligent driver model to access the impact of driving strategies on traffic capacity.” Philos. Trans. R. Soc. London, Ser. A 368 (1928): 4585–4605. https://doi.org/10.1098/rsta.2010.0084.
Kong, D., L. Sun, and Y. Chen. 2022. “Traffic dynamics around freeway merging area with mixed conventional vehicles and connected and autonomous vehicles.” Int. J. Mod. Phys. C 33 (10): 2250128. https://doi.org/10.1142/S0129183122501285.
Kopelias, P., E. Demiridi, K. Vogiatzis, A. Skabardonis, and V. Zafiropoulou. 2020. “Connected & autonomous vehicles—Environmental impacts—A review.” Sci. Total Environ. 712 (Apr): 135237. https://doi.org/10.1016/j.scitotenv.2019.135237.
Lay, M. G. 2019. Handbook of road technology. 4th ed. Boca Raton, FL: CRC Press.
Leong, L. V., V. W. W. Lim, and W. C. Goh. 2020. “Effects of short exit lane on gap-acceptance and merging behavior of drivers turning right at unconventional T-junctions.” Int. J. Civ. Eng. 18 (1): 19–36. https://doi.org/10.1007/s40999-019-00456-9.
Li, X., O. Oviedo-Trespalacios, and A. Rakotonirainy. 2020. “Drivers’ gap acceptance behaviours at intersections: A driving simulator study to understand the impact of mobile phone visual-manual interactions.” Accid. Anal. Prev. 138 (Apr): 105486. https://doi.org/10.1016/j.aap.2020.105486.
Li, Y., H. Hao, R. B. Gibbons, and A. Medina. 2021. “Understanding gap acceptance behavior at unsignalized intersections using naturalistic driving study data.” Transp. Res. Rec. 2675 (9): 1345–1358. https://doi.org/10.1177/03611981211007140.
Liu, H., X. Kan, S. E. Shladover, X.-Y. Lu, and R. E. Ferlis. 2018a. “Impact of cooperative adaptive cruise control on multilane freeway merge capacity.” J. Intell. Transp. Syst. 22 (3): 263–275. https://doi.org/10.1080/15472450.2018.1438275.
Liu, H., X. Kan, S. E. Shladover, X.-Y. Lu, and R. E. Ferlis. 2018b. “Modeling impacts of cooperative adaptive cruise control on mixed traffic flow in multi-lane freeway facilities.” Transp. Res. Part C Emerging Technol. 95 (Oct): 261–279. https://doi.org/10.1016/j.trc.2018.07.027.
Liu, Y., J. Guo, J. Taplin, and Y. Wang. 2017. “Characteristic analysis of mixed traffic flow of regular and autonomous vehicles using cellular automata.” J. Adv. Transp. 2017 (Oct): e8142074. https://doi.org/10.1155/2017/8142074.
Lunardon, N., G. Menardi, and N. Torelli. 2021. Package ‘ROSE.’ Random over-sampling examples. R. Indianapolis: R Foundation.
Mafi, S., Y. Abdelrazig, and R. Doczy. 2018. “Analysis of gap acceptance behavior for unprotected right and left turning maneuvers at signalized intersections using data mining methods: A driving simulation approach.” Transp. Res. Rec. 2672 (38): 160–170. https://doi.org/10.1177/0361198118783111.
Maze, T. H. 1981. “A probabilistic model of gap acceptance behavior.” Transp. Res. Rec. 795: 8–13.
Miller, A., and R. Pretty. 1968. Overtaking on two-lane rural roads. Washington, DC: Transportation Research Board.
Montanaro, U., S. Dixit, S. Fallah, M. Dianati, A. Stevens, D. Oxtoby, and A. Mouzakitis. 2019. “Towards connected autonomous driving: Review of use-cases.” Veh. Syst. Dyn. 57 (6): 779–814. https://doi.org/10.1080/00423114.2018.1492142.
Mosquet, X., T. Dauner, N. Lang, M. Russmann, A. Mei-Pochtler, R. Agrawal, and F. Schmieg. 2015. Revolution in the driver’s seat: The road to autonomous vehicles. Boston: Boston Consulting Group.
NHTSA (National Highway Traffic Safety Administration). 2020. “Automated vehicles for safety.” Accessed August 13, 2020. https://www.nhtsa.gov/technology-innovation/automated-vehicles-safety.
Ogallo, H. O., and M. K. Jha. 2014. “Methodology for critical-gap analysis at intersections with unprotected opposing left-turn movements.” J. Transp. Eng. 140 (9): 04014045. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000691.
Olia, A., S. Razavi, B. Abdulhai, and H. Abdelgawad. 2018. “Traffic capacity implications of automated vehicles mixed with regular vehicles.” J. Intell. Transp. Syst. 22 (3): 244–262. https://doi.org/10.1080/15472450.2017.1404680.
Papadoulis, A., M. Quddus, and M. Imprialou. 2019. “Evaluating the safety impact of connected and autonomous vehicles on motorways.” Accid. Anal. Prev. 124 (Mar): 12–22. https://doi.org/10.1016/j.aap.2018.12.019.
Patil, G. R., and D. S. Pawar. 2014. “Temporal and spatial gap acceptance for minor road at uncontrolled intersections in India.” Transp. Res. Rec. 2461 (1): 129–136. https://doi.org/10.3141/2461-16.
Pollatschek, M. A., A. Polus, and M. Livneh. 2002. “A decision model for gap acceptance and capacity at intersections.” Transp. Res. Part B Methodol. 36 (7): 649–663. https://doi.org/10.1016/S0191-2615(01)00024-8.
PTV Group. 2018. PTV. VISSIM 10—User manual. Karlsruhe, Germany: PTV Group.
Raff, M. S. 1950. A volume warrant for urban stop signs. Washington, DC: Eno Foundation for Highway Traffic Control.
Razmi Rad, S., H. Farah, H. Taale, B. Van Arem, and S. P. Hoogendoorn. 2021. “The impact of a dedicated lane for connected and automated vehicles on the behaviour of drivers of manual vehicles.” Transp. Res. Part F Traffic Psychol. Behav. 82 (Oct): 141–153. https://doi.org/10.1016/j.trf.2021.08.010.
Serag, M. S. 2015. “Gap-acceptance behavior at uncontrolled intersections in developing countries.” Malaysian J. Civ. Eng. 27 (1): 80–93.
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.
Stanek, D., R. T. Milam, E. Huang, and Y. A. Wang. 2018. Measuring autonomous vehicle impacts on congested networks using simulation. Washington, DC: Transportation Research Board.
Sukennik, P., and P. Group. 2018. “Micro-simulation guide for automated vehicles.” In COEXIST. Washington, DC: CoEXist.
Talebpour, A., and H. S. Mahmassani. 2016. “Influence of connected and autonomous vehicles on traffic flow stability and throughput.” Transp. Res. Part C Emerging Technol. 71 (Oct): 143–163. https://doi.org/10.1016/j.trc.2016.07.007.
Tibshirani, R. 1996. “Regression shrinkage and selection via the Lasso.” J. R. Stat. Soc. B 58 (1): 267–288. https://doi.org/10.1111/j.2517-6161.1996.tb02080.x.
Virdi, N., H. Grzybowska, S. T. Waller, and V. Dixit. 2019. “A safety assessment of mixed fleets with connected and autonomous vehicles using the surrogate safety assessment module.” Accid. Anal. Prev. 131 (Oct): 95–111. https://doi.org/10.1016/j.aap.2019.06.001.
Wang, T., J. Zhao, and P. Li. 2018. “An extended car-following model at un-signalized intersections under V2V communication environment.” PLoS One 13 (2): e0192787. https://doi.org/10.1371/journal.pone.0192787.
Yang, S., M. Du, and Q. Chen. 2021. “Impact of connected and autonomous vehicles on traffic efficiency and safety of an on-ramp.” Simul. Modell. Pract. Theory 113 (Dec): 102374. https://doi.org/10.1016/j.simpat.2021.102374.
Ye, L., and T. Yamamoto. 2019. “Evaluating the impact of connected and autonomous vehicles on traffic safety.” Phys. A 526 (Jul): 121009. https://doi.org/10.1016/j.physa.2019.04.245.
Zhang, G., Y. Qi, and J. Chen. 2016. “Exploring factors impacting paths of left-turning vehicles from minor road approach at unsignalized intersections.” Math. Probl. Eng. 2016 (Jan): e1305890. https://doi.org/10.1155/2016/1305890.
Zhong, Z., L. Cordova, M. Halverson, and B. Leonard. 2021a. Field tests on DSRC and C-V2X range of reception on Utah roadways. Taylorsville, UT: Utah Department of Transportation.
Zhong, Z., J. Lee, and L. Zhao. 2021b. “traffic flow characteristics and lane use strategies for connected and automated vehicles in mixed traffic conditions.” J. Adv. Transp. 2021 (Jan): e8816540. https://doi.org/10.1155/2021/8816540.
Information & Authors
Information
Published In
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Oct 29, 2021
Accepted: Aug 9, 2022
Published online: Dec 23, 2022
Published in print: Mar 1, 2023
Discussion open until: May 23, 2023
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.
Cited by
- Lubna Obaid, Sara A. Alattieh, Mohamed Abdallah, Khaled Hamad, Environmental impacts of the transition to automated vehicles: A life cycle perspective, Sustainable Materials and Technologies, 10.1016/j.susmat.2023.e00725, 38, (e00725), (2023).