Modeling Freeway Merging in a Weaving Section as a Sequential Decision-Making Process
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 143, Issue 5
Abstract
Vehicle merging is a tactical, dynamic optimizing process with a series of decision-making operations. Existing microscopic lane-changing simulation models have been criticized that they do not well capture the important sequential decision-making process during merging because of the lack of deeply investigating field data. This study first analyzes merging tactics based on noise-filtered next-generation simulation (NGSIM) data, and then a new combined sequential decision-making model was proposed for candidate gap generation, targeting gap selection, merge location choice, and acceleration decisions of the merging vehicles. This sequential decision-making model could dynamically simulate the merging vehicles’ choice of targeting gaps and merging tactics under the effects of changing traffic conditions. How the merging vehicles behave after rejecting their current adjacent gap and synchronize with the speed of the main-lane traffic during merging is embodied in this model. Such aspects were oversimplified and against reality in existing merging models. The proposed new merging model was calibrated and validated with a U.S. Highway 101 (U.S.101) data set. The superiority of this new framework is highlighted in comparison with other two merging models. The results demonstrate that the proposed model has an acceptable accuracy to reproduce the trajectories of merging vehicles. The simulated vehicles’ trajectories show that the gap-selection model and targeting gap approaching algorithm can well simulate the driving behavior of the merging vehicle, which carries gap-rejection experience. The empirical field data analysis and model calibration results in this study provide several useful thoughts on building merging models to capture more real-world freeway merging behaviors.
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References
Ahmed, K. I. (1991). “Modeling drivers’ acceleration and lane changing behavior.” Ph.D. thesis, Massachusetts Institute of Technology, Boston.
Choudhury, C., Ramanujam, V., and Ben-Akiva, M. (2009). “Modeling acceleration decisions for freeway merges.” Transp. Res. Rec., 2124, 45–57.
Colyar, J., and Halkias, J. (2007). “US highway 101 dataset.” Federal Highway Administration (FHWA), Washington, DC.
CORSIM [Computer software]. McTrans Center, Univ. of Florida, Gainesville, FL.
Daamen, W., and Loot, M., and Hoogendoorn, S. P. (2010). “Empirical analysis of merging behavior at freeway on-ramp.” Transp. Res. Rec., 2188, 108–118.
Daganzo, C. F. (1981). “Estimation of gap acceptance parameters within and across the population from direct roadside observation.” Transp. Res. Part B: Methodol., 15(1), 1–15.
Drew, D. R. (1967). “Gap acceptance characteristics for ramp-freeway surveillance and control and discussion.” Highway Res. Rec., 195(157), 108–143.
Hamdar, S., Treiber, M., Mahmassani, H., and Kesting, A. (2008). “Modeling driver behavior as sequential risk-taking task.” Transp. Res. Rec., 2088, 208–217.
Herman, R., and Weiss, G. (1961). “Comments on the highway-crossing problem.” Oper. Res., 9(6), 828–840.
Hidas, P. (2005). “Modelling vehicle interactions in microscopic simulation of merging and weaving.” Transp. Res. Part C: Emerging Technol., 13(1), 37–62.
Hidas, P., and Behbahanizadeh, K. (1998). “SITRAS: A simulation model for ITS applications.” Proc., 5th World Congress on Intelligent Transport Systems, Seoul.
Java version 7.0 [Computer software]. Oracle, Menlo Park, CA.
Jin, S., Wang, D., and Yang, Z. (2011). “Non-lane-based car-following model with visual angle information.” Transp. Res. Rec., 2249, 7–14.
Kim, J. T., Kim, J., and Chang, M. (2008). “Lane-changing gap acceptance model for freeway merging in simulation.” Can. J. Civ. Eng., 35(3), 301–311.
Kita, H. (1993). “Effects of merging lane length on the merging behavior at expressway on-ramps.” Int. Symp. on Theory of Traffic Flow and Transportation, Berkeley, CA, 37–51.
Kita, H., Tanimoto, K., and Fukuyama, K. (1999). “A merging-giveway interaction model of cars in a merging section: A game theoretic analysis.” Transp. Res. Part A: Policy Pract., 33(3–4), 305–312.
Kita, H., Tanimoto, K., and Fukuyama, K. (2002). “A game theoretic analysis of merging-giveway interaction: A joint estimation model.” Transportation and Traffic Theory in the 21st Century: Proc., 15th Int. Symp. on Transportation and Traffic Theory, Emerald Group Publishing Limited, Bingley, U.K., 503–518.
Laval, J. A., and Daganzo, C. F. (2006). “Lane-changing in traffic streams.” Transp. Res. Part B: Methodol., 40(3), 251–264.
Miller, A. J. (1974). “Nine estimators of gap-acceptance parameters.” Traffic flow and transportation, Univ. of Melbourne, Parkville, VIC, Australia, 215–235.
MITSIM version 7.3 [Computer software]. MIS ITS Lab, Cambridge, MA.
Moridpour, S., Sarvi, M., and Rose, G. (2010). “Modeling the lane-changing execution of multiclass vehicles under heavy traffic conditions.” Transp. Res. Rec., 2161, 11–19.
Moridpour, S., Sarvi, M., Rose, G., and Mazloumi, E. (2011). “Lane-changing decision model for heavy vehicle drivers.” J. Intell. Transp. Syst., 16(1), 24–35.
Punzo, V., Borzacchiello, MT., and Ciuffo, B. (2011). “On the assessment of vehicle trajectory data accuracy and application to the Next Generation SIMulation (NGSIM) program data.” Transp. Res. Part C, 19(6), 1243–1262.
Schakel, W. J., Knoop, V. L., and Arem, B. V. (2012). “Integrated lane change model with relaxation and synchronization.” Transp. Res. Rec., 2316, 47–57.
SPSS version 22 [Computer software]. IBM, Foster City, CA.
Sultan, B., Brackstone, M., Waterson, B., and Boer, E. (2002). “Modeling the dynamic cut-in situation.” Transp. Res. Rec., 1803, 45–51.
Sun, D., and Elefteriadou, L. (2014). “A driver behavior-based lane-changing model for urban arterial streets.” Transp. Sci., 48(2), 184–205.
Thiemann, C., Treiber, M., and Kesting, A. (2008). “Estimating acceleration and lane-changing dynamics based on NGSIM trajectory data.” Transp. Res. Rec., 2088, 90–101.
Toledo, T., Koutsopoulos, H. N., and Ben-Akiva, M. (2007). “Integrated driving behavior modeling.” Transp. Res. Part C: Emerging Technol., 15(2), 96–112.
VISSIM version 9 [Computer software]. PTV Vissim, Karlsruhe, Germany.
Wan, X., Jin, J., Yang, F., Zhang, J., and Ran, B. (2014). “Modeling vehicle interactions during merge in congested weaving section of freeway ramp.” Transp. Res. Rec., 4, 1–10.
Wan, X., Jin, J., Yang, F., Zhang, J., and Ran, B. (2016). “Merging preparation behavior of drivers: How they choose and approach their merge positions at a congested weaving area.” J. Transp. Eng., .
Wan, X., Jin, J., Zheng, L., Cheng, Y., and Ran, B. (2013). “Speed synchronization process of merging vehicles from the entrance ramp: Empirical analysis.” Transp. Res. Rec., 2391, 11–21.
Wang, J. (2005). “A simulation model for motorway merging behaviour.” Transp. Traffic Theory, 16, 281–301.
Wang, Q., Li, Z., and Li, L. (2014). “Investigation of discretionary lane-change characteristics using next-generation simulation data sets.” J. Intell. Transp. Syst., 18(3), 246–253.
Wisconsin Department of Transportation. (2016). “Motorists’ Handbook.” Madison, WI.
Yeo, H. (2008). Asymmetric microscopic driving behavior theory, Univ. of California, Berkeley, CA.
Zheng, Z. (2014). “Recent developments and research needs in modeling lane changing.” Transp. Res. Part B: Methodol., 60, 16–32.
Zheng, Z., Ahn, S., Chen, D., and Laval, J. (2013). “The effects of lane-changing on the immediate follower: Anticipation, relaxation, and change in driver characteristics.” Transp. Res. Part C: Emerging Technol., 26, 367–379.
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©2017 American Society of Civil Engineers.
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Received: Mar 9, 2016
Accepted: Dec 1, 2016
Published online: Feb 10, 2017
Published in print: May 1, 2017
Discussion open until: Jul 10, 2017
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