Integrated Lane Change Model with Relaxation and Synchronization

A proposed lane change model can be integrated with a car-following model to form a complete microscopic driver model. The model resembles traffic better at a macroscopic level, especially regarding the amount of traffic volume per lane, the traffic speeds in different lanes, and the onset of congestion. In a new approach, lane change incentives are combined for determining a lane change desire. Included incentives are to follow a route, to gain speed, and to keep right. Classification of lane changes is based on behavior that depends on the level of lane change desire. Integration with a car-following model is achieved by influencing car-following behavior for relaxation and synchronization, that is, following vehicles in adjacent lanes. Other improvements of the model are trade-offs between lane change incentives and the use of anticipation speed for the speed gain incentive. Although all these effects are captured, the lane change model has only seven parameters. Loop detector data were used to validate and calibrate the model, and an accurate representation of lane distribution and the onset of congestion was shown.

[1]  Dirk Helbing,et al.  An Adaptive Smoothing Method for Traffic State Identification from Incomplete Information , 2003 .

[2]  Bart van Arem,et al.  Effects of Cooperative Adaptive Cruise Control on traffic flow stability , 2010, 13th International IEEE Conference on Intelligent Transportation Systems.

[3]  Dirk Helbing,et al.  General Lane-Changing Model MOBIL for Car-Following Models , 2007 .

[4]  Helbing,et al.  Congested traffic states in empirical observations and microscopic simulations , 2000, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[5]  Jorge A. Laval,et al.  Microscopic modeling of the relaxation phenomenon using a macroscopic lane-changing model , 2008 .

[6]  Carlos F. Daganzo,et al.  A BEHAVIORAL THEORY OF MULTI-LANE TRAFFIC FLOW. PART I, LONG HOMOGENEOUS FREEWAY SECTIONS , 1999 .

[7]  Serge P. Hoogendoorn,et al.  Empirical Analysis of Merging Behavior at Freeway On-Ramp , 2010 .

[8]  Peter Hidas,et al.  MODELLING LANE CHANGING AND MERGING IN MICROSCOPIC TRAFFIC SIMULATION , 2002 .

[9]  Steven A. Smith,et al.  Freeway data collection for studying vehicle interactions : technical report , 1985 .

[10]  S. P. Hoogendoorn,et al.  Microscopic Traffic Data Collection by Remote Sensing , 2003 .

[11]  Jiao Wang.  A Simulation Model for Motorway Merging Behaviour , 2005 .

[12]  Haris N. Koutsopoulos,et al.  Integrated driving behavior modeling , 2007 .

[13]  S L Cohen.  Application of Relaxation Procedure for Lane Changing in Microscopic Simulation Models , 2004 .

[14]  Serge P. Hoogendoorn,et al.  Reliability of Parameter Values Estimated Using Trajectory Observations , 2009 .

[15]  P. G. Gipps,et al.  A behavioural car-following model for computer simulation , 1981 .

[16]  Alexander Skabardonis,et al.  Oversaturated Freeway Flow Algorithm for Use in Next Generation Simulation , 2008 .

[17]  P. G. Gipps,et al.  A MODEL FOR THE STRUCTURE OF LANE-CHANGING DECISIONS , 1986 .

[18]  Carlos F. Daganzo,et al.  Lane-changing in traffic streams , 2006 .

[19]  Ben Waterson,et al.  Modeling the Dynamic Cut-In Situation , 2002 .

[20]  M. Ben-Akiva,et al.  Modeling Cooperative Lane Changing and Forced Merging Behavior , 2007 .

[21]  Nakayama,et al.  Dynamical model of traffic congestion and numerical simulation. , 1995, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.