Calibration and Validation of Psychophysical Car-Following Model Using Driver’s Action Points and Perception Thresholds
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 145, Issue 9
Abstract
This study develops a method of calibrating and validating the Wiedemann car-following model using vehicle trajectory data. Unlike sensitivity analysis and optimization, this method conforms to the assumptions of the original Wiedemann 99 model related to drivers’ car-following behavior. Eight calibration constants (CCs) of the model were estimated using the vehicle trajectory data from a section of the US-101 freeway in Los Angeles, California. (desired time gap from lead vehicle) and (maximum change in spacing) were determined from the observed maximum and minimum spacing between the lead and following vehicles with similar speeds. and (minimum relative velocity at which the driver starts decelerating and accelerating, respectively, with short spacing of the lead vehicle or so-called action points) and (effect of spacing on these action points) were determined using a segmented linear regression model. This model provided the estimated relative velocities at which the speed of a following vehicle changed in response to a lead vehicle using constant acceleration/deceleration. It was found that the absolute values of and were not the same, which indicates that drivers are more sensitive to lead vehicles in the closing process than the opening process. was calculated as the mean difference in constant accelerations of lead and following vehicles. was calculated as the mean acceleration of all vehicles 1 s after the vehicles increased from slow speeds (). Moreover, was calculated as the mean acceleration for speeds between 79.5 and . The traffic simulation with the estimated CCs in this study better reflected the observed speed distributions and action points than simulations with CCs estimated in previous studies using the same trajectory data.
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Acknowledgments
The authors thank the Natural Sciences and Engineering Research Council of Canada for funding this research. The authors also thank Dr. Martin Treiber for his comments on the Wiedemann model.
References
Aghabayk, K., M. Sarvi, and W. Young. 2015. “A state-of-the-art review of car-following models with particular considerations of heavy vehicles.” Transp. Rev. 35 (1): 82–105. https://doi.org/10.1080/01441647.2014.997323.
Aghabayk, K., M. Sarvi, W. Young, and L. Kautzsch. 2013. “A novel methodology for evolutionary calibration of Vissim by multi-threading.” In Proc., Australasian Transport Research Forum 2013, 1–15. Brisbane, Australia: Australasian Transport Research Forum Incorporated.
Chandler, R. E., R. Herman, and E. W. Montroll. 1958. “Traffic dynamics: Studies in car following.” Oper. Res. 6 (2): 165–184. https://doi.org/10.1287/opre.6.2.165.
Durrani, U., C. Lee, and H. Maoh. 2016. “Calibrating the Wiedemann’s vehicle-following model using mixed vehicle-pair interactions.” Transp. Res. Part C Emerging Technol. 67 (Jun): 227–242. https://doi.org/10.1016/j.trc.2016.02.012.
FHWA. 2015. “Next generation simulation (NGSIM).” Accessed April 1, 2015. https://www.fhwa.dot.gov/publications/research/operations/07030/index.cfm.
Fritzsche, H. 1994. “A model for traffic simulation.” Traffic Eng. Control 35 (5): 317–321.
Gazis, D. C., R. Herman, and R. W. Rothery. 1961. “Nonlinear follow-the-leader of traffic flow.” Oper. Res. 9 (4): 545–567. https://doi.org/10.1287/opre.9.4.545.
Ge, Q, and M. Menendez. 2014. “An efficient sensitivity analysis approach for computationally expensive microscopic traffic simulation models.” Int. J. Transport. 2 (2): 49–64.
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.
Habtemichael, F. G., and L. Santos. 2012. “Safety evaluations of aggressive driving on motorways through microscopic traffic simulation and surrogate measures.” In Proc., 91st Transportation Research Board Annual Meeting. Washington, DC: Transportation Research Board.
Hoogendoorn, S., R. G. Hoogendoorn, and W. Daamen. 2011. “Wiedemann revisited: New trajectory filtering technique and its implications for car-following modeling.” Transp. Res. Rec. 2260 (1): 152–162. https://doi.org/10.3141/2260-17.
Jie, L., H. Van Zuylen, Y. Chen, F. Viti, and I. Wilmink. 2013. “Calibration of a microscopic simulation model for emission calculation.” Transp. Res. Part C: Emerging Technol. 31 (Jun): 172–184. https://doi.org/10.1016/j.trc.2012.04.008.
Kim, K., L. Nitz, J. Richardson, and L. Li. 1995. “Personal and behavioral predictors of automobile crash and injury severity.” Accid. Anal. Prev. 27 (4): 469–481. https://doi.org/10.1016/0001-4575(95)00001-G.
Kim, S. 2006. “Simultaneous calibration of a microscopic traffic simulation model and OD matrix.” Ph.D. dissertation, Dept. of Civil and Environmental Engineering, Texas A&M Univ.
Li, C., X. Jiang, W. Wang, Q. Cheng, and Y. Shen. 2016. “A simplified car-following model based on the artificial potential.” Procedia Eng. 137: 13–20. https://doi.org/10.1016/j.proeng.2016.01.229.
Liu, F., R. Cheng, H. Ge, and C. Yu. 2016. “A new car-following model with consideration of the velocity difference between the current speed and the historical speed of the leading car.” Physica A Stat. Mech. Appl. 464 (Dec): 267–277. https://doi.org/10.1016/j.physa.2016.06.059.
Lownes, N. E., and R. B. Machemehl. 2006. “VISSIM: A multi-parameter sensitivity analysis.” In Proc., 38th Conf. on Winter simulation, 1406–1413. San Diego, CA: Winter Simulation Conference (WSC) Foundation.
Manjunatha, P., and L. Elefteriadou. 2018. “Analysis of Wiedemann car following thresholds using driving simulator observations.” In Proc., 97th Transportation Research Board Annual Meeting. Washington, DC: Transportation Research Board.
Manjunatha, P., P. Vortisch, and T. Mathew. 2013. “Methodology for the calibration of VISSIM in mixed traffic.” In Proc., 92nd Transportation Research Board Annual Meeting. Washington, DC: Transportation Research Board.
Menneni, S., C. Sun, and P. Vortisch. 2008. “Microsimulation calibration using speed flow relationships.” Transp. Res. Rec. 2088 (1): 1–9. https://doi.org/10.3141/2088-01.
Menneni, S., C. Sun, and P. Vortisch. 2009. “An integrated microscopic and macroscopic calibration for psycho-physical car following models.” In Proc., 88th Transportation Research Board Annual Meeting. Washington, DC: Transportation Research Board.
Michaels, R. M. 1963. “Perceptual factors in car following.” In Proc., 2nd Int. Symp. on the Theory of Road Traffic Flow. London: San Diego, CA.
Muggeo, V. M. 2008. “Segmented: An R package to fit regression models with broken-line relationships.” R News 8 (1): 20–25.
Pariota, L., and G. N. Bifulco. 2015. “Experimental evidence supporting simpler Action Point paradigms for car-following.” Transp. Res. Part F Traffic Psychol. Behav. 35 (Nov): 1–15. https://doi.org/10.1016/j.trf.2015.08.002.
Park, B., and J. D. Schneeberger. 2003. “Microscopic simulation model calibration and validation: Case study of VISSIM simulation model for a coordinated actuated signal system.” Transp. Res. Rec. 1856: 185–192. https://doi.org/10.3141/1856-20.
Peng, G., H. He, and W. Lu. 2016. “A new car-following model with the consideration of incorporating timid and aggressive driving behaviors.” Phys. A Stat. Mech. Appl. 442: 197–202. https://doi.org/10.1016/j.physa.2015.09.009.
PVT AG (Planung Transport Verkehr Planung Transport Verkehr). 2011. VISSIM 5.40 user manual. Karlsruhe, Germany: PVT AG.
Rrecaj, A. A., and K. M. Bombol. 2015. “Calibration and validation of the VISSIM parameters: State of the art.” TEM J. -Technol. Educ. Manage. Inf. 4 (3): 255–269.
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: 379–403. https://doi.org/10.1016/j.trc.2014.09.008.
Thiemann, C., M. Treiber, and A. Kesting. 2008. “Estimating acceleration and lane-changing dynamics from next generation simulation trajectory data.” Transp. Res. Rec. 2088 (1): 90–101. https://doi.org/10.3141/2088-10.
Todosiev, E. P. 1963. “The action point model of the driver-vehicle system.” Ph.D. dissertation, Dept. of Electrical Engineering, Ohio State Univ.
Treiber, M., and A. Kesting. 2013. “Traffic flow dynamics.” In Traffic flow dynamics: Data, models and simulation. Berlin: Springer.
Vortisch, P. 2014. “History of VISSIM’s development.” In Traffic and transport simulation. Washington, DC: Transportation Research Board.
Vortisch, P. 2016. “Re: What does the perception threshold mean in Wiedemann model? [Online discussion].” Accessed March 23, 2017. https://www.researchgate.net/post/What_does_the_perception_threshold_mean_in_Wiedemann_model.
Wiedemann, R., and U. Reiter. 1992. Microscopic traffic simulation: The simulation system MISSION, background and actual state. Brussels, Belgium; CEC.
Woody, T. 2006. Calibrating freeway simulation models in VISSIM. Seattle: Univ. of Washington.
Yousif, S., and J. Al-Obaedi. 2011. “Close following behavior: Testing visual angle car following models using various sets of data.” Transp. Res. Part F Traffic Psychol. Behav. 14 (2): 96–110. https://doi.org/10.1016/j.trf.2010.11.001.
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©2019 American Society of Civil Engineers.
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Received: Aug 26, 2017
Accepted: Feb 11, 2019
Published online: Jul 10, 2019
Published in print: Sep 1, 2019
Discussion open until: Dec 10, 2019
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