Modeling a Car-Following Model with Comprehensive Safety Field in Freeway Tunnels
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 148, Issue 7
Abstract
Car following is the most common driving behavior in tunnels. However, current car-following models are not completely suitable for tunnels because they do not take into account the environmental factors affecting vehicles in tunnels. In this paper, we present a comprehensive risk-based car-following model to describe car-following behavior in freeway tunnels. Considering the key factors influencing driving behavior in freeway tunnels, we develop a comprehensive safety field (CSF), which consists of the potential, kinetic, and environment fields to estimate the effect of speed limit signs, leading vehicles, and lighting conditions on driving risks. Then, a car-following model based on comprehensive safety field (CF-CSF) was established to determine a vehicular driving strategy in tunnels. The field force is introduced as a quantitative indicator to assess the current driving risk of vehicles and whose increase causes a greater deceleration of vehicles. Furthermore, considering the effect of low-risk levels on driving behavior is generally insignificant, we develop the risk margin (RM) as a safety indicator to determine whether current driving risk affects the driving behavior, and the driving strategy under a free condition is proposed as well. Finally, the proposed CF-CSF model is validated using a real vehicle test trajectory dataset. The comparison with real driving data and some classic car-following models indicate that our proposed CF-CSF model can more accurately predict actual driving behavior in tunnels. It is expected that the findings in this study could be valuable in modeling, understanding, and replicating features of driving behavior in freeway tunnels.
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 generated or used during the study are available from the corresponding author upon reasonable request.
Acknowledgments
This work was funded by the National Natural Science Foundation of China (Grant Nos. 52172345 and 61863019). The authors are very grateful to the authors of cited papers.
References
Ali, Y., Z. Zheng, and M. M. Haque. 2021. “Modelling lane-changing execution behaviour in a connected environment: A grouped random parameters with heterogeneity-in-means approach.” Commun. Transp. Res. 1 (Sep): 100009. https://doi.org/10.1016/j.commtr.2021.100009.
Almqvist, S., C. Hyden, and R. Risser. 1991. “Use of speed limiters in cars for increased safety and a better environment.” Transp. Res. Rec. 1318 (1): 91.
Amundsen, F. H., and G. Ranes. 2000. “Studies on traffic accidents in Norwegian road tunnels.” Tunnelling Underground Space Technol. 15 (1): 3–11. https://doi.org/10.1016/S0886-7798(00)00024-9.
Andersen, G. J., and C. W. Sauer. 2007. “Optical information for car following: The driving by visual angle (DVA) model.” Hum. Factors 49 (5): 878–896. https://doi.org/10.1518/001872007X230235.
Arias, A. V., S. M. Lopez, I. Fernandez, J. L. Martinez-Rubio, and A. Magallares. 2008. “Psychosocial factors, perceived risk and driving in a hostile environment: Driving through tunnels.” Int. J. Global Environ. Issues 8 (1–2): 165–181. https://doi.org/10.1504/IJGENVI.2008.017266.
Bassan, S. 2016. “Overview of traffic safety aspects and design in road tunnels.” IATSS Res. 40 (1): 35–46. https://doi.org/10.1016/j.iatssr.2016.02.002.
Beard, A., and R. Carvel. 2012. Handbook of tunnel fire safety. London: ICE Publishing.
Bellouquid, A., and M. Delitala. 2011. “Asymptotic limits of a discrete kinetic theory model of vehicular traffic.” Appl. Math. Lett. 24 (5): 672–678. https://doi.org/10.1016/j.aml.2010.12.004.
Benekohal, R. F., and J. Treiterer. 1988. “CARSIM: Car-following model for simulation of traffic in normal and stop-and-go conditions.” Transp. Res. Rec. 1194 (1): 99–111.
Broughton, K. L., F. Switzer, and D. Scott. 2007. “Car following decisions under three visibility conditions and two speeds tested with a driving simulator.” Accid. Anal. Prev. 39 (1): 106–116. https://doi.org/10.1016/j.aap.2006.06.009.
Chen, T., X. Shi, and Y. D. Wong. 2019. “Key feature selection and risk prediction for lane-changing behaviors based on vehicles’ trajectory data.” Accid. Anal. Prev. 129 (Aug): 156–169. https://doi.org/10.1016/j.aap.2019.05.017.
Du, Z., Z. Zheng, M. Zheng, B. Ran, and X. Zhao. 2014. “Drivers’ visual comfort at highway tunnel portals: A quantitative analysis based on visual oscillation.” Transp. Res. Part D Transp. Environ. 31 (Aug): 37–47. https://doi.org/10.1016/j.trd.2014.05.012.
Gazis, D. C., R. Herman, and R. W. Rothery. 1961. “Nonlinear follow-the-leader models of traffic flow.” Oper. Res. 9 (4): 545–567. https://doi.org/10.1287/opre.9.4.545.
Gipps, P. G. 1981. “A behavioural car-following model for computer simulation.” Transp. Res. Part B Methodol. 15 (2): 105–111. https://doi.org/10.1016/0191-2615(81)90037-0.
Gong, H., H. Liu, and B.-H. Wang. 2008. “An asymmetric full velocity difference car-following model.” Physica A 387 (11): 2595–2602. https://doi.org/10.1016/j.physa.2008.01.038.
Gressai, M., B. Varga, T. Tettamanti, and I. Varga. 2021. “Investigating the impacts of urban speed limit reduction through microscopic traffic simulation.” Commun. Transp. Res. 1 (Feb): 100018. https://doi.org/10.1016/j.commtr.2021.100018.
He, S., B. Liang, G. Pan, F. Wang, and L. Cui. 2017. “Influence of dynamic highway tunnel lighting environment on driving safety based on eye movement parameters of the driver.” Tunnelling Underground Space Technol. 67 (Aug): 52–60. https://doi.org/10.1016/j.tust.2017.04.020.
Jin, W.-L. 2018. “Kinematic wave models of sag and tunnel bottlenecks.” Transp. Res. Part B Methodol. 107 (Jan): 41–56. https://doi.org/10.1016/j.trb.2017.11.006.
Kim, S., C. Carello, and M. T. Turvey. 2016. “Size and distance are perceived independently in an optical tunnel: Evidence for direct perception.” Visual Res. 125 (Aug): 1–11. https://doi.org/10.1016/j.visres.2016.04.007.
Kircher, K., and C. Ahlstrom. 2012. “The impact of tunnel design and lighting on the performance of attentive and visually distracted drivers.” Accid. Anal. Prev. 47 (Sep): 153–161. https://doi.org/10.1016/j.aap.2012.01.019.
Koshi, M., M. Kuwahara, and H. Akahane. 1992. “Capacity of sags and tunnels on Japanese motorways.” ITE J. 62 (5): 17–22.
Leitao, S., E. S. Pires, and P. de Moura Oliveira. 2009. “Road tunnels lighting using genetic algorithms.” In Proc., 15th Int. Conf. on Intelligent System Applications to Power Systems, 1–6. New York: IEEE.
Lemke, K. 2000. “Road safety in tunnels.” Transp. Res. Rec. 1740 (1): 170–174. https://doi.org/10.3141/1740-22.
Li, L., J. Gan, X. Qu, W. Lu, P. Mao, and B. Ran. 2021. “A dynamic control method for cavs platoon based on the MPC framework and safety potential field model.” KSCE J. Civ. Eng. 25 (5): 1874–1886. https://doi.org/10.1007/s12205-021-1585-5.
Li, L., J. Gan, Z. Yi, X. Qu, and B. Ran. 2020. “Risk perception and the warning strategy based on safety potential field theory.” Accid. Anal. Prev. 148 (Dec): 105805. https://doi.org/10.1016/j.aap.2020.105805.
Li, M., X. Song, H. Cao, J. Wang, Y. Huang, C. Hu, and H. Wang. 2019. “Shared control with a novel dynamic authority allocation strategy based on game theory and driving safety field.” Mech. Syst. Sig. Process. 124 (Jun): 199–216. https://doi.org/10.1016/j.ymssp.2019.01.040.
Liang, G.-H., D. Zhang, S.-B. Du, Y.-J. Yin, R. Li, and B.-R. Shi. 2018. “Effects of the installation angle of raised pavement markers on a horizontal curve section on the line of sight induction performance.” Math. Probl. Eng. 2018 (Jan): 1–9. https://doi.org/10.1155/2018/3541784.
Lin, Y., S. Fotios, M. Wei, Y. Liu, W. Guo, and Y. Sun. 2015. “Eye movement and pupil size constriction under discomfort glare.” Invest Ophthalmol. Visual Sci. 56 (3): 1649–1656. https://doi.org/10.1167/iovs.14-15963.
Lu, G., B. Cheng, Q. Lin, and Y. Wang. 2012. “Quantitative indicator of homeostatic risk perception in car following.” Saf. Sci. 50 (9): 1898–1905. https://doi.org/10.1016/j.ssci.2012.05.007.
Lu, G., B. Cheng, Y. Wang, and Q. Lin. 2013. “A car-following model based on quantified homeostatic risk perception.” Math. Probl. Eng. 2013 (1): 1–13. https://doi.org/10.1155/2013/408756.
Ma, Z.-L., C.-F. Shao, and S.-R. Zhang. 2009. “Characteristics of traffic accidents in Chinese freeway tunnels.” Tunnelling Underground Space Technol. 24 (3): 350–355. https://doi.org/10.1016/j.tust.2008.08.004.
Mahmud, S. S., L. Ferreira, M. S. Hoque, and A. Tavassoli. 2017. “Application of proximal surrogate indicators for safety evaluation: A review of recent developments and research needs.” IATSS Res. 41 (4): 153–163. https://doi.org/10.1016/j.iatssr.2017.02.001.
Mehri, A., J. Sajedifar, M. Abbasi, A. Naimabadi, A. A. Mohammadi, G. H. Teimori, and S. A. Zakerian. 2019. “Safety evaluation of lighting at very long tunnels on the basis of visual adaptation.” Saf. Sci. 116 (Apr): 196–207. https://doi.org/10.1016/j.ssci.2019.03.018.
Meng, Q., and X. Qu. 2012. “Estimation of rear-end vehicle crash frequencies in urban road tunnels.” Accid. Anal. Prev. 48 (Sep): 254–263. https://doi.org/10.1016/j.aap.2012.01.025.
Newell, G. F. 1961. “Nonlinear effects in the dynamics of car following.” Oper. Res. 9 (2): 209–229. https://doi.org/10.1287/opre.9.2.209.
Ni, D. 2011. “A unified perspective on traffic flow theory, part I: The field theory.” In Proc., ICCTP 2011: Towards Sustainable Transportation Systems, 4227–4243. Red Hook, NY: Curran Associates.
Onaygil, S., Ö. Güler, and E. Erkin. 2003. “Determination of the effects of structural properties on tunnel lighting with examples from Turkey.” Tunnelling Underground Space Technol. 18 (1): 85–91. https://doi.org/10.1016/S0886-7798(02)00097-4.
Papathanasopoulou, V., and C. Antoniou. 2015. “Towards data-driven car-following models.” Transp. Res. Part C Emerging Technol. 55 (Apr): 496–509. https://doi.org/10.1016/j.trc.2015.02.016.
Peña-García, A., R. Escribano, L. Gil-Martín, and A. Espín-Estrella. 2012. “Computational optimization of semi-transparent tension structures for the use of solar light in road tunnels.” Tunnelling Underground Space Technol. 32 (Nov): 127–131. https://doi.org/10.1016/j.tust.2012.06.004.
Pervez, A., H. Huang, C. Han, J. Wang, and Y. Li. 2020. “Revisiting freeway single tunnel crash characteristics analysis: A six-zone analytic approach.” Accid. Anal. Prev. 142 (Jul): 105542. https://doi.org/10.1016/j.aap.2020.105542.
Pritchard, S. J., and S. T. Hammett. 2012. “The effect of luminance on simulated driving speed.” Visual Res. 52 (1): 54–60. https://doi.org/10.1016/j.visres.2011.10.014.
Shi, X., D. Zhao, H. Yao, X. Li, D. K. Hale, and A. Ghiasi. 2021. “Video-based trajectory extraction with deep learning for high-granularity highway simulation (HIGH-SIM).” Commun. Transp. Res. 1 (Sep): 100014. https://doi.org/10.1016/j.commtr.2021.100014.
Soori, H., E. Ainy, F. Zayeri, and M. Mehmandar. 2013. “Comparison of road traffic death occurrence within urban and metropolitan roads focusing on environmental factors.” Hakim Res. J. 15 (4): 339–345.
TAC (Transportation Association of Canada). 1999. Geometric design guide for Canadian roads. Ottawa: TAC.
Transportation Research Board. 2000. Highway capacity manual. Washington, DC: National Research Council.
Treiber, M., A. Hennecke, and D. Helbing. 2000. “Congested traffic states in empirical observations and microscopic simulations.” Phys. Rev. E 62 (2): 1805. https://doi.org/10.1103/PhysRevE.62.1805.
Van Winsum, W. 1999. “The human element in car following models.” Transp. Res. Part F Traffic Psychol. Behav. 2 (4): 207–211. https://doi.org/10.1016/S1369-8478(00)00008-5.
Wada, K., I. Martínez, and W.-L. Jin. 2020. “Continuum car-following model of capacity drop at sag and tunnel bottlenecks.” Transp. Res. Part C Emerging Technol. 113 (3): 260–276. https://doi.org/10.1016/j.trc.2019.05.012.
Wang, J., J. Wu, and Y. Li. 2015. “The driving safety field based on driver–vehicle–road interactions.” IEEE Trans. Intell. Transp. Syst. 16 (4): 2203–2214. https://doi.org/10.1109/TITS.2015.2401837.
Wang, J., J. Wu, X. Zheng, D. Ni, and K. Li. 2016. “Driving safety field theory modeling and its application in pre-collision warning system.” Transp. Res. Part C Emerging Technol. 72 (Nov): 306–324. https://doi.org/10.1016/j.trc.2016.10.003.
Wang, X., R. Jiang, L. Li, Y. Lin, X. Zheng, and F.-Y. Wang. 2017. “Capturing car-following behaviors by deep learning.” IEEE Trans. Intell. Transp. Syst. 19 (3): 910–920. https://doi.org/10.1109/TITS.2017.2706963.
Yeung, J. S., and Y. D. Wong. 2013. “Road traffic accidents in Singapore expressway tunnels.” Tunnelling Underground Space Technol. 38 (Jan): 534–541. https://doi.org/10.1016/j.tust.2013.09.002.
Yeung, J. S., and Y. D. Wong. 2014. “The effect of road tunnel environment on car following behaviour.” Accid. Anal. Prev. 70 (Sep): 100–109. https://doi.org/10.1016/j.aap.2014.03.014.
Zheng, Z. 2021. “Reasons, challenges, and some tools for doing reproducible transportation research.” Commun. Transp. Res. 1 (4): 100004. https://doi.org/10.1016/j.commtr.2021.100004.
Information & Authors
Information
Published In
Journal of Transportation Engineering, Part A: Systems
Volume 148 • Issue 7 • July 2022
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Sep 25, 2021
Accepted: Feb 2, 2022
Published online: Apr 27, 2022
Published in print: Jul 1, 2022
Discussion open until: Sep 27, 2022
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
- Ting Shang, Jiaxin Lu, Ying Luo, Song Wang, Zhengyu He, Aobo Wang, Understanding the traffic flow in different types of freeway tunnels based on car-following behaviors analysis, Tunnelling and Underground Space Technology, 10.1016/j.tust.2023.105494, 143, (105494), (2024).
- Ruyang Yin, Nan Zheng, Zhen Zhou, Bimodal Traffic Evacuation Management for Road Tunnels Considering Social Fairness: CTM-Based Model, Journal of Transportation Engineering, Part A: Systems, 10.1061/JTEPBS.TEENG-7899, 149, 7, (2023).
- Paul J. Ossenbruggen, An Example of Establishing a Plan to Mitigate Traffic Delay with Microscale Computer Simulated Data, Journal of Transportation Engineering, Part A: Systems, 10.1061/JTEPBS.TEENG-7377, 149, 8, (2023).
- Ting Zhang, Feng Chen, Yadi Huang, Mingtao Song, Xiao Hu, Analysis of Car-Following Behaviors under Different Conditions on the Entrance Section of Cross-River and Cross-Sea Tunnels: A Case Study of Shanghai Yangtze River Tunnel, International Journal of Environmental Research and Public Health, 10.3390/ijerph191911975, 19, 19, (11975), (2022).
- Yiqun Xia, Daniel Silber, Zhengnan Ma, Oliver Voßen, Lutz Eckstein, Designing a Methodology to Calibrate and Validate Virtual Test Driving in a Large-Scale Network with Multisource Data, Journal of Transportation Engineering, Part A: Systems, 10.1061/JTEPBS.0000743, 148, 10, (2022).