Identifying Lane-Change Maneuvers with Probe Vehicle Data and an Observed Asymmetry in Driver Accommodation
Publication: Journal of Transportation Engineering
Volume 138, Issue 8
Abstract
This paper uses an instrumented probe vehicle to monitor ambient traffic and overcome many challenges of observing traffic flow phenomena that occur over extended distances. One contribution of this paper is a general methodology to identify the probe vehicle’s lane of travel without a priori knowledge of where the lanes are. This knowledge is used to find the probe’s lane-change maneuvers (LCMs), to differentiate these LCMs from GPS errors, and, in conjunction with a ranging sensor, to identify which lanes the ambient vehicles are in to find their LCMs. The second contribution of this paper comes from the identified LCMS. The data are used to provide an independent validation of earlier studies, and thus yield further evidence of how LCMs contribute to the formation of disturbances within freeway queues. In particular, it is found that vehicles following an entering vehicle generally complete their response and return to steady state quicker than those following an exiting vehicle. As discussed herein, this asymmetry in the lane-change maneuver accommodation time effectively induces a ripple in the traffic state that propagates upstream. The resulting disturbances provide a possible mechanism to explain the fact that congested traffic tends to fluctuate, e.g., stop-and-go traffic, rather than remain at a single, relatively stable congested state.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
The authors would like to thank the numerous individuals who contributed to this work in one form or another, from the undergraduate student drivers to the anonymous reviewers who provided valuable and constructive input to this paper.
This material is based upon work supported in part by the National Science Foundation under Grant No. 0133278.
References
Ahmed, K. I., Ben-Akiva, M., Koutsopoulos, H. N., and Mishalani, R. G. (1996). “Models of freeway lane changing and gap acceptance behavior.” Proc., 13th Int. Symp. on Transportation and Traffic Theory, Elsevier, Oxford, UK, 501–515.
Ahn, S., and Cassidy, M. J. (2007). “Freeway traffic oscillations and vehicle lane-change maneuvers.” Proc., 17th Int. Symp. of Transportation and Traffic Theory, Elsevier, Oxford, UK, 691–710.
BPR. (1950). Highway capacity manual, Bureau of Public Roads, Washington, DC.
Coifman, B., and Dhoorjaty, S. (2004). “Event data-based traffic detector validation tests.” J. Transp. Eng., 130(3), 313–321.JTPEDI
Coifman, B., Mishalani, R., Wang, C., and Krishnamurthy, S. (2006). “Impact of lane-change maneuvers on congested freeway segment delays: Pilot study.” Transportation Research Record 1965, Transportation Research Board, Washington, DC.
FHWA. (2006a). “Interstate 80 freeway dataset.” U.S. Federal Highway Administration, FHWA-HRT-06-137 〈http://www.fhwa.dot.gov/publications/research/operations/06137/index.cfm〉 (May 24, 2012).
FHWA. (2006b). “NGSIM overview.” U.S. Federal Highway Administration, FHWA-HRT-06-135 〈http://www.fhwa.dot.gov/publications/research/operations/its/06135/index.cfm〉 (May 24, 2012).
Gao, B., and Coifman, B. (2006). “Vehicle identification and GPS error detection from a LIDAR equipped probe vehicle.” Proc., 9th IEEE Int. Conf. on Intelligent Transportation Systems, IEEE, Piscataway, NJ.
Gao, B., and Coifman, B. (2007). “Extracting traffic flow characteristics with an instrumented probe vehicle.” Proc., Traffic and Granular Flow 2005, Springer, Berlin, 675–685.
Gipps, P. G. (1986). “A model for the structure of lane-changing decisions.” Trans. Res. B, 20(5), 403–414.
Hidas, P. (2002). “Modelling lane changing and merging in microscopic traffic simulation.” Trans. Res. C, 10(5–6), 351–371.
Hidas, P. (2005). “Modelling vehicle interactions in microscopic simulation of merging and weaving.” Trans. Res. C, 13(1), 37–62.
Kang, K. P., and Chang, G. L. (2004). “Observations of macroscopic non-mandatory lane-changing behaviors on the Capital Beltway.” Proc., 7th Int. IEEE Conf. on Intelligent Transportation Systems, IEEE, Piscataway, NJ, 441–446.
Laval, J. A., and Daganzo, C. F. (2006). “Lane-changing in traffic streams.” Trans. Res. B, 40(3), 251–264.
Lighthill, M. J., and Whitham, G. B. (1955). “On kinematic waves. II. A theory of traffic flow on long crowded roads.” Proc. Roy. Soc. London, A, 229(1178), 317–345.
Nakatsuji, T., Ranjitkar, P., and Suzuki, H. (2006). “Investigating lane-changing behavior of drivers based on test track experiments.” Proc., Transportation Research Board 85th Annual Meeting, TRB, Washington, DC.
Richards, P. I. (1956). “Shock waves on the highway.” Oper. Res., 4(1), 42–51.OPREAI
Rothery, R. W. (2001). “Car following models.” Revised Traffic Flow Theory Monograph, Transportation Research Board. 〈http://www.tft.pdx.edu/docs.htm〉 (Nov. 12, 2011).
Sheu, J.-B. (1999). “A stochastic modeling approach to dynamic prediction of section-wide inter-lane and intra-lane traffic variables using point detector data.” Trans. Res. A, 33(2), 79–100.
Sheu, J.-B., and Ritchie, S. G. (2001). “Stochastic modeling and real-time prediction of vehicular lane-changing behavior.” Trans. Res. B, 35(7), 695–716.
Smith, S. A. (1985). “Freeway data collection for studying vehicle interactions.” U.S. Federal Highway Administration, FHWA/RD-85/108, Federal Highway Administration, Reston, VA.
Smith, S. A., and Mark, E. R. (1985). “Creation of data sets to study microscopic traffic flow in freeway bottleneck sections.” Transportation Research Record 1005, Transportation Research Board, Washington, DC.
Toledo, T., Koutsopoulos, H. N., and Ben-Akiva, M. E. (2003). “Modeling integrated lane-changing behavior.” Transportation Research Record, 1857, Transportation Research Board, Washington, DC.
Wang, C., and Coifman, B. (2008). “The effect of lane-change maneuvers on a simplified car-following theory.” IEEE Trans. on Intelligent Transportation Systems, 9(3), 523–535.
Yang, Q., and Koutsopoulos, H. N. (1996). “A microscopic traffic simulator for evaluation of dynamic traffic management systems.” Trans. Res. C, 4(3), 113–129.
Zhang, Y., Owen, L. E., and Clark, J. E. (1998). “Multiregime approach for microscopic traffic simulation.” Transportation Research Record, 1644, Transportation Research Board, Washington, DC.
Information & Authors
Information
Published In
Journal of Transportation Engineering
Volume 138 • Issue 8 • August 2012
Pages: 1051 - 1061
Copyright
© 2012. American Society of Civil Engineers.
History
Received: May 13, 2010
Accepted: Dec 29, 2011
Published online: Jul 16, 2012
Published in print: Aug 1, 2012
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.