Modeling Car-Following Behavior on Freeways Considering Driving Style
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 147, Issue 12
Abstract
To build more accurate and realistic freeway car-following models, driving characteristics specific to freeway car following should be considered. This study, therefore, analyzed three car-following models calibrated for different driving styles. A total of 5,900 freeway car-following events were extracted from 161,055 km of driving data collected in the Shanghai Naturalistic Driving Study (SH-NDS) database. Based on the fuzzy inference system built in this study, these car-following events were categorized as representing one of two styles: nonaggressive or aggressive. The two driving styles were visualized by using the t-distributed stochastic neighbor embedding (t-SNE) algorithm. The Gipps, Wiedemann, and intelligent driver model (IDM) car-following models were calibrated and validated for each driving style group. Using a genetic algorithm to analyze the calibrated parameters of the investigated car-following models, it was found that the model parameter values were related to driving style. When their performances were evaluated, results showed that the IDM performed best. The nonaggressive IDM and the aggressive IDM were used to simulate the car-following scenarios based on the same leading vehicle trajectories. The t-test and the F-test results showed that regarding both time gap and spacing gap, the differences of mean and variance are significant between aggressive and nonaggressive styles in nearly all of the simulated car-following scenarios. The mean spacing gap (nonaggressive: 38 m; aggressive: 30 m) and time gap (nonaggressive: 1.7 s; aggressive: 1.4 s) obtained from modeled car-following scenarios could be used directly in simulation software to show the characteristics of different driving styles.
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Data Availability Statement
Some or all data, models, or code generated or used during the study are proprietary or confidential in nature and may only be provided with restrictions.
Informed consent form templates were signed with experiment participants, clearly stating that the data of the participants collected in the experiment was only used within the research team to protect the participants’ privacy.
Acknowledgments
This study was jointly sponsored by the Chinese National Science Foundation (51878498), the Science and Technology Commission of Shanghai Municipality (18DZ1200200), and the 111 Project (B17032). The authors are very grateful to Omar Hassanin for his help in revising the paper.
References
Aljaafreh, A., N. Alshabatat, and M. S. N. Al-Din. 2012. “Driving style recognition using fuzzy logic.” In Proc., 2012 IEEE Int. Conf. on Vehicular Electronics and Safety (ICVES 2012), 460–463. New York: IEEE.
Bär, T., D. Nienhüser, R. Kohlhaas, and J. M. Zöllner. 2011. “Probabilistic driving style determination by means of a situation based analysis of the vehicle data.” In Proc., 2011 14th Int. IEEE Conf. on Intelligent Transportation Systems (ITSC), 1698–1703. New York: IEEE.
Berthaume, A. L., R. M. James, B. E. Hammit, C. Foreman, and C. L. Melson. 2018. “Variations in driver behavior: An analysis of car-following behavior heterogeneity as a function of road type and traffic condition.” Transp. Res. Rec. 2672 (37): 31–44. https://doi.org/10.1177/0361198118798713.
Brackstone, M., and M. McDonald. 1999. “Car-following: A historical review.” Transp. Res. Part F: Traffic Psychol. Behav. 2 (4): 181–196. https://doi.org/10.1016/S1369-8478(00)00005-X.
Chen, S.-W., C.-Y. Fang, and C.-T. Tien. 2013. “Driving behaviour modelling system based on graph construction.” Transp. Res. Part C: Emerging Technol. 26 (Sep): 314–330. https://doi.org/10.1016/j.trc.2012.10.004.
Constantinescu, Z., C. Marinoiu, and M. Vladoiu. 2010. “Driving style analysis using data mining techniques.” Int. J. Comput. Commun. Control 5 (5): 654–663. https://doi.org/10.15837/ijccc.2010.5.2221.
Dingus, T. A., S. G. Klauer, V. L. Neale, A. Petersen, S. E. Lee, J. Sudweeks, M. A. Perez, J. Hankey, D. Ramsey, and S. Gupta. 2006. The 100-car naturalistic driving study phase II—Results of the 100-car field experiment. Washington, DC: Dept. of Transportation.
Guo, H.-F., X. L. Yuan, and D. W. Xu. 2017. “Selection of measures of performance on calibrating parameters in car following models.” China J. Highway Transp. 30 (1): 103–110.
Higgs, B., and M. Abbas. 2013. “A two-step segmentation algorithm for behavioral clustering of naturalistic driving styles.” In Proc., 16th Int. IEEE Conf. on Intelligent Transportation Systems (ITSC 2013), 857–862. New York: IEEE.
Huang, Y.-H., W. Zhang, M. Roetting, and D. Melton. 2006. “Experiences from dual-country drivers: Driving safely in China and the US.” Saf. Sci. 44 (9): 785–795. https://doi.org/10.1016/j.ssci.2006.05.002.
Ishibashi, M., M. Okuwa, S. I. Doi, and M. Akamatsu. 2007. “Indices for characterizing driving style and their relevance to car following behavior.” In Proc., SICE Annual Conf. 2007, 1132–1137. New York: IEEE.
Johnson, D. A., and M. M. Trivedi. 2011. “Driving style recognition using a smartphone as a sensor platform.” In Proc., 14th Int. IEEE Conf. on Intelligent Transportation Systems (ITSC), 1609–1615. New York: IEEE.
Karginova, N., S. Byttner, and M. Svensson. 2012. Data-driven methods for classification of driving styles in buses. SAE Technical Paper. Warrendale, PA: SAE International.
Kesting, A., and M. Treiber. 2008. “Calibrating car-following models by using trajectory data: Methodological study.” Transp. Res. Rec. 2088 (1): 148–156. https://doi.org/10.3141/2088-16.
Kometani, E. 1959. “Dynamic behavior of traffic with a nonlinear spacing-speed relationship.” Theory Traffic Flow 1959 (1): 105–119.
Meiring, G. A. M., and H. C. Myburgh. 2015. “A review of intelligent driving style analysis systems and related artificial intelligence algorithms.” Sensors 15 (12): 30653–30682. https://doi.org/10.3390/s151229822.
Michaels, R. 1963. “Perceptual factors in car-following.” In Proc., 2nd ISTTF, 44–59. Cambridge, MA: Berkman Klein Center for Internet and Society.
Mitchell, M. 1998. An introduction to genetic algorithms. London: MIT Press.
Murphey, Y. L., R. Milton, and L. Kiliaris. 2009. “Driver’s style classification using jerk analysis.” In Proc., 2009 IEEE Workshop on Computational Intelligence in Vehicles and Vehicular Systems, 23–28. New York: IEEE.
Pipes, L. A. 1953. “An operational analysis of traffic dynamics.” J. Appl. Phys. 24 (3): 274–281. https://doi.org/10.1063/1.1721265.
Punzo, V., and M. Montanino. 2016. “Speed or spacing? Cumulative variables, and convolution of model errors and time in traffic flow models validation and calibration.” Transp. Res. Part B: Methodol. 91 (8): 21–33. https://doi.org/10.1016/j.trb.2016.04.012.
Qi, G., J. Wu, Y. Zhou, Y. Du, Y. Jia, N. Hounsell, and N. A. Stanton. 2019. “Recognizing driving styles based on topic models.” Transp. Res. Part D: Transp. Environ. 66 (Jan): 13–22. https://doi.org/10.1016/j.trd.2018.05.002.
Ranjitkar, P., T. Nakatsuji, and A. Kawamua. 2005. “Car-following models: An experiment based benchmarking.” J. Eastern Asia Soc. Transp. Stud. 6 (Jan): 1582–1596. https://doi.org/10.11175/easts.6.1582.
Sagberg, F. S., G. F. Bianchi Piccinini, and J. Engström. 2015. “A review of research on driving styles and road safety.” Hum. Factors 57 (7): 1248–1275. https://doi.org/10.1177/0018720815591313.
Saifuzzaman, M., and Z. Zheng. 2014. “Incorporating human-factors in car-following models: A review of recent developments and research needs.” Transp. Res. Part C: Emerging Technol. 48 (Nov): 379–403. https://doi.org/10.1016/j.trc.2014.09.008.
Sangster, J., H. Rakha, and J. Du. 2013. “Application of naturalistic driving data to modeling of driver car-following behavior.” Transp. Res. Rec. 2390 (1): 20–33. https://doi.org/10.3141/2390-03.
SH-NDS. 2015. Shanghai naturalistic driving study database. Shanghai, China: Tonji Univ.
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.
Treiber, M., and A. Kesting. 2013. Traffic flow dynamics: Data, models and simulation. Berlin: Springer.
van der Maaten, L. 2014. “Accelerating t-SNE using tree-based algorithms.” J. Mach. Learn. Res. 15 (1): 3221–3245.
van der Maaten, L., and G. Hinton. 2008. “Visualizing data using t-SNE.” J. Mach. Learn. Res. 9 (Nov): 2579–2605.
Van Ly, M., S. Martin, and M. M. Trivedi. 2013. “Driver classification and driving style recognition using inertial sensors.” In Proc., 2013 IEEE Intelligent Vehicles Symp. (IV), 1040–1045. New York: IEEE.
Wang, R., and S. M. Lukic. 2011. “Review of driving conditions prediction and driving style recognition based control algorithms for hybrid electric vehicles.” In Proc., 2011 IEEE Vehicle Power and Propulsion Conf., 1–7. New York: IEEE.
Wiedemann, R. 1974. “Simulation des Strassenverkehrsflusses. Kalsruhe.” In Traffic engineering. Karlsruhe, Germany: Univ. of Karlsruhe.
Woody, T. 2006. Calibrating freeway simulation models in VISSIM. Washington, DC: Univ. of Washington.
Wu, F., J. Lu, and J. Jiang. 2011. “Estimation of car-following model parameters distribution using bootstrap method.” In Proc., 3rd Int. Conf. on Road Safety and Simulation. Washington, DC: Transportation Research Board.
Zhu, M., X. Wang, and A. Tarko. 2018. “Modeling car-following behavior on urban expressways in Shanghai: A naturalistic driving study.” Transp. Res. Part C: Emerging Technol. 93 (25): 425–445. https://doi.org/10.1016/j.trc.2018.06.009.
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Journal of Transportation Engineering, Part A: Systems
Volume 147 • Issue 12 • December 2021
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© 2021 American Society of Civil Engineers.
History
Received: Dec 1, 2020
Accepted: May 24, 2021
Published online: Sep 21, 2021
Published in print: Dec 1, 2021
Discussion open until: Feb 21, 2022
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