Transactions on Transport Sciences 2025, 16(2):33-41 | DOI: 10.5507/tots.2025.001
Determinants Behind the Taste Variation in Discretionary Lane Changing Behavior of Drivers Facing Downstream Queues
- Department of Civil Engineering, Faculty of Technical and Engineering, Imam Khomeini International University, Qazvin, Iran
Lane-changing behavior can significantly affect many aspects of traffic flow including capacity, shock waves, and safety. Therefore, it is imperative to understand the determinants behind lane change behavior. This paper investigates the determinants of lane-changing in congested traffic using video-recording as well as a survey approach. A mixed logit model was estimated to account for unobserved heterogeneity in lane-changing behavior across drivers. Estimation results show that all categories of explanatory variables including socioeconomic, driving style, and road environment have a significant effect on lane changing behavior. Besides, unobserved heterogeneity and taste variation among drivers with regards to the lateral distance of the target vehicle from the left car has been observed. Among the non-random parameters, speed of target vehicle, being a law-evading driver, disregarding yellow traffic signals at intersections, lateral distance of target vehicle from right/left cars, and experiencing at least two accidents are positively associated with a higher likelihood of lane changing when a driver encounters a downstream queue. The aforementioned interesting findings can significantly help to improve the performance of traffic flow models for the purpose of replicating and predicting traffic flow.
Keywords: Discretionary Lane Changing; Mixed Logit Model; Taste Variation; Congestion; Heterogenous Drivers
Received: January 23, 2024; Revised: December 11, 2024; Accepted: January 13, 2025; Prepublished online: April 29, 2025; Published: September 15, 2025 Show citation
ACS | AIP | APA | ASA | Harvard | Chicago | Chicago Notes | IEEE | ISO690 | MLA | NLM | Turabian | Vancouver |
References
- Abbasi, M., Mamdoohi, A. R., Sierpiński, G., & Ciari, F. (2023). Usage Intention of Shared Autonomous Vehicles with Dynamic Ride Sharing on Long-Distance Trips. Sustainability, 15(2), 1649.
Go to original source...
- Abbasi, M., Piccioni, C., Sierpiński, G., & Farzin, I. (2022). Analysis of Crash Severity of Texas Two Lane Rural Roads Using Solar Altitude Angle Based Lighting Condition. Sustainability, 14(3), 1692.
Go to original source...
- Ali, Y., Bliemer, M. C., Zheng, Z., & Haque, M. M. (2020). Comparing the usefulness of real-time driving aids in a connected environment during mandatory and discretionary lane-changing manoeuvres. Transportation research part C: emerging technologies, 121, 102871.
Go to original source...
- Alshehri, A., & Abdul Aziz, H. (2022). Analysis of Factors Affecting Discretionary Lane Change. International Conference on Transportation and Development 2022.
Go to original source...
- Bagheri, M., Bartin, B., & Ozbay, K. (2023). Implementing Artificial Neural Network-Based Gap Acceptance Models in the Simulation Model of a Traffic Circle in SUMO. Transportation Research Record, 2677(7), 573-584, 03611981231167420.
Go to original source...
- Balal, E., Cheu, R. L., Gyan-Sarkodie, T., & Miramontes, J. (2014). Analysis of discretionary lane changing parameters on freeways. International journal of transportation science and technology, 3(3), 277-296.
Go to original source...
- Ben-Akiva, M. E., & Lerman, S. R. (1985). Discrete choice analysis: theory and application to travel demand (Vol. 9). MIT press.
- Cassidy, M. J., & Rudjanakanoknad, J. (2005). Increasing the capacity of an isolated merge by metering its on-ramp. Transportation Research Part B: Methodological, 39(10), 896-913.
Go to original source...
- Daganzo, C. F. (2002). A behavioral theory of multi-lane traffic flow. Part I: Long homogeneous freeway sections. Transportation Research Part B: Methodological, 36(2), 131-158.
Go to original source...
- Dilipan, T., Das Vivek, R., & Parthan, K. (2022). Study of Driver's Behavior for Lateral Moving Vehicles. Proceedings of the Fifth International Conference of Transportation Research Group of India: 5th CTRG Volume 2.
Go to original source...
- Farah, H., Bekhor, S., Polus, A., & Toledo, T. (2009). A passing gap acceptance model for two-lane rural highways. Transportmetrica, 5(3), 159-172.
Go to original source...
- Farooq, D., Moslem, S., Jamal, A., Butt, F. M., Almarhabi, Y., Faisal Tufail, R., & Almoshaogeh, M. (2021). Assessment of significant factors affecting frequent lane-changing related to road safety: An integrated approach of the AHP-BWM model. International journal of environmental research and public health, 18(20), 10628.
Go to original source...
- Guo, M., Wu, Z., & Zhu, H. (2018). Empirical study of lane-changing behavior on three Chinese freeways. PloS one, 13(1), e0191466.
Go to original source...
- Hensher, D. A., Rose, J. M., & Greene, W. H. (2005). Applied choice analysis: a primer. Cambridge university press.
Go to original source...
- Jamal, A., Rahman, M. T., Al-Ahmadi, H. M., & Mansoor, U. (2020). The dilemma of road safety in the eastern province of Saudi Arabia: Consequences and prevention strategies. International journal of environmental research and public health, 17(1), 157.
Go to original source...
- Jin, W.-L. (2010). A kinematic wave theory of lane-changing traffic flow. Transportation Research Part B: Methodological, 44(8-9), 1001-1021.
Go to original source...
- Jin, W.-L. (2013). A multi-commodity Lighthill-Whitham-Richards model of lane-changing traffic flow. Transportation Research Part B: Methodological, 57, 361-377.
Go to original source...
- Knoop, V., Hoogendoorn, S., & Van Lint, J. (2012). Routing strategies based on macroscopic fundamental diagram. Transportation Research Record, 2315(1), 1-10.
Go to original source...
- Laval, J. A., & Daganzo, C. F. (2006). Lane-changing in traffic streams. Transportation Research Part B: Methodological, 40(3), 251-264.
Go to original source...
- Laval, J. A., & Leclercq, L. (2008). Microscopic modeling of the relaxation phenomenon using a macroscopic lane-changing model. Transportation Research Part B: Methodological, 42(6), 511-522.
Go to original source...
- Lavallière, M., Donmez, B., Reimer, B., Mehler, B., Klauber, K., Orszulak, J., Coughlin, J. F., & Teasdale, N. (2010). Effects of age and cognitive workload on lane choice and lane changing behavior. 20th Canadian Multidisciplinary Road Safety Conference.
- Leclercq, L., Chiabaut, N., Laval, J., & Buisson, C. (2007). Relaxation phenomenon after lane changing: Experimental validation with NGSIM data set. Transportation Research Record, 1999(1), 79-85.
Go to original source...
- Lee, J., Park, M., & Yeo, H. (2016). A probability model for discretionary lane changes in highways. KSCE Journal of Civil Engineering, 20, 2938-2946.
Go to original source...
- Li, Y., Gu, R., Lee, J., Yang, M., Chen, Q., & Zhang, Y. (2021). The dynamic tradeoff between safety and efficiency in discretionary lane-changing behavior: A random parameters logit approach with heterogeneity in means and variances. Accident Analysis & Prevention, 153, 106036.
Go to original source...
- Ma, C., & Li, D. (2023). A review of vehicle lane change research. Physica A: Statistical Mechanics and its Applications, 615, 129060.
Go to original source...
- Ma, Y., Yin, B., Jiang, X., Du, J., & Chan, C. (2020). Psychological and environmental factors affecting driver's frequent lane-changing behaviour: A national sample of drivers in China. IET Intelligent Transport Systems, 14(8), 825-833.
Go to original source...
- Mullakkal-Babu, F. A., Wang, M., van Arem, B., & Happee, R. (2020). Empirics and models of fragmented lane changes. IEEE Open Journal of Intelligent Transportation Systems, 1, 187-200.
Go to original source...
- Park, M., Jang, K., Lee, J., & Yeo, H. (2015). Logistic regression model for discretionary lane changing under congested traffic. Transportmetrica A: transport science, 11(4), 333-344.
Go to original source...
- Paz, A., Arteaga, C., & Cobos, C. (2019). Specification of mixed logit models assisted by an optimization framework. Journal of choice modelling, 30, 50-60.
Go to original source...
- Rezaei, A., Puckett, S. M., & Nassiri, H. (2011). Heterogeneity in preferences of air travel itinerary in a low-frequency market. Transportation Research Record, 2214(1), 10-19.
Go to original source...
- Schmidt, M., Wissing, C., Nattermann, T., & Bertram, T. (2021). A probabilistic model for discretionary lane change proposals in highway driving situations. Forschung im Ingenieurwesen 85(2).
Go to original source...
- Sun, D., & Elefteriadou, L. (2010). Research and implementation of lane-changing model based on driver behavior. Transportation Research Record, 2161(1), 1-10.
Go to original source...
- Sun, D., & Elefteriadou, L. (2012). Lane-changing behavior on urban streets: An "in-vehicle" field experiment-based study. Computer-Aided Civil and Infrastructure Engineering, 27(7), 525-542.
Go to original source...
- Tang, T. Q., Wong, S., Huang, H. J., & Zhang, P. (2009). Macroscopic modeling of lane-changing for two-lane traffic flow. Journal of advanced transportation, 43(3), 245-273.
Go to original source...
- Toledo, T., Koutsopoulos, H. N., & Ben-Akiva, M. (2009). Estimation of an integrated driving behavior model. Transportation research part C: emerging technologies, 17(4), 365-380.
Go to original source...
- Toth, C., Guensler, R., & Laval, J. (2015). An Empirical Data-Driven Macroscopic Lane Changing Model. Proceedings of the Transportation Research Board 94th Annual Meeting.
- Train, K. E. (2009). Discrete choice methods with simulation. Cambridge university press.
- Vechione, M., Balal, E., & Cheu, R. L. (2018). Comparisons of mandatory and discretionary lane changing behavior on freeways. International journal of transportation science and technology, 7(2), 124-136.
Go to original source...
- Wei, S., Zou, Y., Zhang, X., Zhang, T., & Li, X. (2019). An integrated longitudinal and lateral vehicle following control system with radar and vehicle-to-vehicle communication. IEEE Transactions on Vehicular Technology, 68(2), 1116-1127.
Go to original source...
- Ye, M., Li, P., Yang, Z., & Liu, Y. (2022). Research on lane changing game and behavioral decision making based on driving styles and micro-interaction behaviors. Sensors, 22(18), 6729.
Go to original source...
- Zhang, Y. (2004). Scalability of car-following and lane-changing models in microscopic traffic simulation systems. Louisiana State University and Agricultural & Mechanical College.
- Zhang, Y., Zou, Y., Xie, Y., & Chen, L. (2024). Identifying dynamic interaction patterns in mandatory and discretionary lane changes using graph structure. Computer-Aided Civil and Infrastructure Engineering, 39(5), 638-655.
Go to original source...
- Zheng, J., Suzuki, K., & Fujita, M. (2014). Predicting driver's lane-changing decisions using a neural network model. Simulation Modelling Practice and Theory, 42, 73-83.
Go to original source...
- Zheng, Z., Ahn, S., Chen, D., & Laval, J. (2011). Freeway traffic oscillations: microscopic analysis of formations and propagations using wavelet transform. Procedia-Social and Behavioral Sciences, 17, 702-716.
Go to original source...
- Zhou, H., Sun, Y., Qin, X., Xu, X., & Yao, R. (2020). Modeling discretionary lane-changing behavior on urban streets considering drivers' heterogeneity. Transportation Letters, 12(3), 213-222.
Go to original source...
- Zhu, M., Wang, X., & Wang, X. (2016). Car-following headways in different driving situations: A naturalistic driving study. In CICTP 2016: Green and Multimodal Transportation and Logistics (pp. 1419-1428). American Society of Civil Engineers.
Go to original source...
This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, distribution, and reproduction in any medium, provided the original publication is properly cited. No use, distribution or reproduction is permitted which does not comply with these terms.