A new car-following model considering driver’s characteristics and traffic jerk

In this paper, we propose an extension of the optimal velocity car-following model to consider explicitly the timid and aggressive driving behavior as well as the traffic jerk. The linear stability condition of the new model is derived, where the effect of traffic jerk and intensity of influence of drivers’ behavior on the traffic flow stability is investigated. By applying the reductive perturbation method, we derive a modified Korteweg–de Vries equation near the critical point to describe the evolution properties of traffic density waves via nonlinear stability analysis. The results show that the provision of aggressive drivers is a greater contributor to improving the stability of traffic flow compared to the timid ones in the context of traffic jerk, and that the stability of traffic flow can be improved by the provision of well-experienced drivers.

[1]  Isha Dhiman,et al.  Phase diagram of a continuum traffic flow model with a static bottleneck , 2015 .

[2]  Tie-Qiao Tang,et al.  Effects of signal light on the fuel consumption and emissions under car-following model , 2017 .

[3]  Sapna Sharma,et al.  Lattice hydrodynamic modeling of two-lane traffic flow with timid and aggressive driving behavior , 2015 .

[4]  Hai-Jun Huang,et al.  A new car-following model with consideration of roadside memorial , 2011 .

[5]  Tie-Qiao Tang,et al.  Analysis of the traditional vehicle’s running cost and the electric vehicle’s running cost under car-following model , 2016 .

[6]  Hongxia Ge,et al.  TDGL and mKdV equations for car-following model considering traffic jerk , 2016 .

[7]  Minjie Chen,et al.  A study of step calculations in traffic cellular automaton models , 2010, 13th International IEEE Conference on Intelligent Transportation Systems.

[8]  R. Jiang,et al.  Full velocity difference model for a car-following theory. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[9]  Da Yang,et al.  Modeling and simulation of the car-truck heterogeneous traffic flow based on a nonlinear car-following model , 2016, Appl. Math. Comput..

[10]  Li Lei,et al.  The influence of the non-motor vehicles for the car-following model considering traffic jerk☆ , 2016 .

[11]  Geng Zhang,et al.  Analysis of two-lane lattice hydrodynamic model with consideration of drivers’ characteristics , 2015 .

[12]  Simon Washington,et al.  Impact of mobile phone use on car-following behaviour of young drivers. , 2015, Accident; analysis and prevention.

[13]  Ziyou Gao,et al.  A new car-following model: full velocity and acceleration difference model , 2005 .

[14]  Ramanpreet Kaur,et al.  Analysis of driver’s characteristics on a curved road in a lattice model , 2017 .

[15]  Wei-Zhen Lu,et al.  A new car-following model with the consideration of incorporating timid and aggressive driving behaviors , 2016 .

[16]  H. Ge,et al.  The car following model considering traffic jerk , 2015 .

[17]  Dihua Sun,et al.  A novel car following model considering average speed of preceding vehicles group , 2015 .

[18]  Dirk Helbing,et al.  Numerical simulation of macroscopic traffic equations , 1999, Comput. Sci. Eng..

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

[20]  Zhong-ke Shi,et al.  An improved car-following model considering velocity fluctuation of the immediately ahead car , 2016 .

[21]  Dirk M. Reichardt,et al.  CarTALK 2000: safe and comfortable driving based upon inter-vehicle-communication , 2002, Intelligent Vehicle Symposium, 2002. IEEE.

[22]  S.L. Klenov,et al.  Testbed for wireless vehicle communication: a simulation approach based on three-phase traffic theory , 2008, 2008 IEEE Intelligent Vehicles Symposium.

[23]  A. Gupta,et al.  Effect of multi-phase optimal velocity function on jamming transition in a lattice hydrodynamic model with passing , 2015 .

[24]  B. van Arem,et al.  Gas-Kinetic Traffic Flow Modeling Including Continuous Driver Behavior Models , 2002 .

[25]  Shuo Yang,et al.  Cellular automata model for urban road traffic flow considering pedestrian crossing street , 2016 .

[26]  Jie Min,et al.  A cellular automata traffic flow model considering the heterogeneity of acceleration and delay probability , 2016 .

[27]  Morteza Dardel,et al.  Vibration control of a nonlinear beam with a nonlinear energy sink , 2016 .

[28]  Xiangmo Zhao,et al.  An improved car-following model with multiple preceding cars’ velocity fluctuation feedback , 2017 .

[29]  Rongjun Cheng,et al.  An extended continuum model accounting for the driver's timid and aggressive attributions , 2017 .

[30]  A. Gupta,et al.  Analyses of the driver’s anticipation effect in a new lattice hydrodynamic traffic flow model with passing , 2014 .

[31]  Poonam Redhu,et al.  Effect of forward looking sites on a multi-phase lattice hydrodynamic model , 2016 .

[32]  Tie-Qiao Tang,et al.  A new car-following model accounting for varying road condition , 2012 .

[33]  Min Zhao,et al.  Stabilization effect of multiple drivers’ desired velocities in car-following theory , 2016 .

[34]  K. Jetto,et al.  The investigation of the reentrance phenomenon in cellular automaton traffic flow model , 2017 .

[35]  Hai-Jun Huang,et al.  A new car-following model with the consideration of the driver's forecast effect , 2010 .

[36]  Yunpeng Wang,et al.  An extended car-following model with consideration of the reliability of inter-vehicle communication , 2014 .