Modeling and Analysis of Merging Behavior at Expressway On-Ramp Bottlenecks

Abstract

Merging behavior is inevitable for drivers at on-ramp bottlenecks and a significant factor in triggering a traffic breakdown. Empirical data were collected by extracting trajectories from merging vehicles and adjacent vehicles at two on-ramp bottlenecks in Shanghai, China. These data included 58 normal (free-flow) lane changes (NLCs), 36 cooperative lane changes (CLCs), 135 forced lane changes (FLCs), and 188 unsuccessful lane changes (USLCs). The objective was to develop and compare five discrete choice models (two multinomial logit and three nested logit) to understand merging behavior at on-ramp bottlenecks better. Estimation results showed that the two-level nested logit model considering three merging types (NLC, CLC, and FLC) provided the best fit. The traffic flow condition (bottleneck), the time gap and the space gap of the lag vehicle, and the speed of the merging vehicle were key factors when choosing merging types. The resulting quantitative models can be used to perform a microscopic analysis of the breakdown mechanism and develop a traffic simulation model.

References

Bierlaire

Discrete Choice Models. NATO ASI Series F Computer and Systems Sciences, Vol. 166, 1998, pp. 203–227.

Cassidy

M. J.

, and Bertini

R. L.

Some Traffic Features at Freeway Bottlenecks. Transportation Research Part B, Vol. 33, No. 1, 1999, pp. 25–42.

Bierlaire

BIOGEME: A Free Package for the Estimation of Discrete Choice Models. Presented at 3rd Swiss Transport Research Conference, Monte Verità, Ascona, Switzerland, March 2003.

Hwang

S. Y.

, and Park

C. H.

Modeling of the Gap Acceptance Behavior at a Merging Section of Urban Freeway. Proceedings of the Eastern Asia Society for Transportation Studies, Vol. 5, 2005, pp. 1641–1656.

Wang

A Simulation Model for Motorway Merging Behavior. Proc., 16th International Symposium on Transportation and Traffic Theory, College Park, Md., Emerald Group, Bingley, United Kingdom, 2005.

Chevallier

, and Leclercq

Do Microscopic Merging Models Reproduce the Observed Priority Sharing Ratio in Congestion?

Transportation Research Part C, Vol. 17, No. 3, 2009, pp. 328–336.

Kesting

, Treiber

, and Helbing

General Lane-Changing Model MOBIL for Car-Following Models. In Transportation Research Record: Journal of the Transportation Research Board, No. 1999, Transportation Research Board of the National Academies, Washington, D.C., 2007, pp. 86–94.

Daamen

, Loot

, and Hoogendoorn

S. P.

Empirical Analysis of Merging Behavior at Freeway On-Ramp. In Transportation Research Record: Journal of the Transportation Research Board, No. 2188, Transportation Research Board of the National Academies, Washington, D.C., 2010, pp. 108–118.

Laval

J. A.

, and Leclercq

Microscopic Modeling of the Relaxation Phenomenon Using a Macroscopic Lane-Changing Model. Transportation Research Part B, Vol. 42, No. 6, 2008, pp. 511–522.

10.

Duncan

Paramics Technical Report: Car Following, Lane Changing and Junction Modeling. Quadstone Paramics, Edinburgh, Scotland, United Kingdom, 1997.

11.

Hidas

Modelling Lane Changing and Merging in Microscopic Traffic Simulation. Transportation Research Part C, Vol. 10, No. 6, 2002, pp. 351–371.

12.

Schakel

W. J.

, Knoop

V. L.

, and van Arem

Integrated Lane Change Model with Relaxation and Synchronization. In Transportation Research Record: Journal of the Transportation Research Board, No. 2316, Transportation Research Board of the National Academies, Washington, D.C., 2012, pp. 47–57.

13.

Kita

A Merging-Giveway Interaction Model of Cars in a Merging Section: A Game Theoretic Analysis. Transportation Research Part A, Vol. 33, No. 4, 1999, pp. 305–312.

14.

Hidas

Modelling Vehicle Interactions in Microscopic Simulation of Merging and Weaving. Transportation Research Part C, Vol. 13, No. 1, 2005, pp. 37–62.

15.

Fang

F. C.

Some Guidelines for Selecting Micro Simulation Models for Interchange Traffic Operational Analysis. Presented at 84th Annual Meeting of the Transportation Research Board, Washington, D.C., 2005.

16.

Gipps

P. G.

A Model for the Structure of Lane-Changing Decisions. Transportation Research Part B, Vol. 20, No. 5, 1986, pp. 403–414.

17.

Hidas

Modelling Individual Behaviour in Microsimulation Models. University of New South Wales, Kensington, Australia, 2005.

18.

Sun

, and Elefteriadou

Information Categorization Based on Driver Behavior for Urban Lane-Changing Maneuvers. In Transportation Research Record: Journal of the Transportation Research Board, No. 2249, Transportation Research Board of the National Academies, Washington, D.C., 2011, pp. 86–94.

19.

Choudhury

C. F.

, Ben-Akiva

M. E.

, Toledo

, Lee

, and Rao

Modeling Cooperative Lane Changing and Forced Merging Behavior. Presented at 86th Annual Meeting of the Transportation Research Board, Washington, D.C., 2007.

20.

Dekking

F. M.

, Kraaikamp

, Lopuhaä

H. P.

, and Meester

L. E.

Confidence Intervals for the Mean. In A Modern Introduction to Probability and Statistics. Springer, London, 2005, pp. 341–359.

21.

Sun

, Zhao

, and Zhang

H. M.

Mechanism of Early-Onset Breakdown at On-Ramp Bottlenecks on Shanghai, China, Expressways. In Transportation Research Record: Journal of the Transportation Research Board, No. 2421, Transportation Research Board of the National Academies, Washington, D.C., 2014, pp. 64–73.