Optimal location of lane-changing warning point in a two-lane road considering different traffic flows

Abstract The timely lane-changing (LC) warning information should be informed to vehicles upstream when some things (such as accident or vehicle breakdown) happen. To avoid secondary accidents or reduce traffic congestion, this paper investigates the optimal LC warning point in a two-lane road considering the different traffic condition. The Intelligent Driver car-following Model and MOBIL LC model are used to describe the vehicle’s longitudinal and lateral motion rules, and methods based on probability theory and numerical simulations are proposed to investigate the optimal warning point under different traffic scenarios. The numerical results show that: i) the successful LC probability is not monotone changing with velocity. ii) providing LC warning information can reduce the average travel time, especially in moderate or congested traffic conditions. iii) the appropriate LC warning point location range becomes smaller with the increase of flow rate. iv) the effective LC warning point is about 30–300 meters far from the event point under different traffic flows.

[1]  A G Bullen,et al.  AN ELEMENTARY STOCHASTIC MODEL OF LANE-CHANGING ON A MULTILANE HIGHWAY , 1970 .

[2]  Hai-Jun Huang,et al.  Influences of the driver’s bounded rationality on micro driving behavior, fuel consumption and emissions , 2015 .

[3]  Hongxia Ge,et al.  The theoretical analysis of the lattice hydrodynamic models for traffic flow theory , 2010 .

[4]  Dirk Helbing,et al.  GENERALIZED FORCE MODEL OF TRAFFIC DYNAMICS , 1998 .

[5]  T. Nagatani.  Traffic jam at adjustable tollgates controlled by line length , 2016 .

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

[7]  Hongxia Ge,et al.  An improved lattice hydrodynamic model accounting for the effect of “backward looking” and flow integral , 2019, Physica A: Statistical Mechanics and its Applications.

[8]  Kerner,et al.  Cluster effect in initially homogeneous traffic flow. , 1993, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[9]  Zhongke Shi,et al.  Consensus and optimal speed advisory model for mixed traffic at an isolated signalized intersection , 2019 .

[10]  Lily Elefteriadou,et al.  A Driver Behavior-Based Lane-Changing Model for Urban Arterial Streets , 2014, Transp. Sci..

[11]  Rongjun Cheng,et al.  An extended lattice hydrodynamic model considering the driver’s sensory memory and delayed-feedback control , 2019, Physica A: Statistical Mechanics and its Applications.

[12]  A. Gupta,et al.  Analyses of driver’s anticipation effect in sensing relative flux in a new lattice model for two-lane traffic system , 2013 .

[13]  Hai-Jun Huang,et al.  A new fundamental diagram theory with the individual difference of the driver’s perception ability , 2012 .

[14]  Yunpeng Wang,et al.  A new car-following model with consideration of inter-vehicle communication , 2014 .

[15]  Xiangfeng Ji,et al.  Cellular automaton simulation of pedestrian flow considering vision and multi-velocity , 2019, Physica A: Statistical Mechanics and its Applications.

[16]  Hussein Dia,et al.  Neural Agent Car-Following Models , 2007, IEEE Transactions on Intelligent Transportation Systems.

[17]  P Berg,et al.  On-ramp simulations and solitary waves of a car-following model. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[18]  Jia Lei,et al.  Nonlinear Analysis of a Synthesized Optimal Velocity Model for Traffic Flow , 2008 .

[19]  Ali Ghaffari,et al.  A Modified Car-Following Model Based on a Neural Network Model of the Human Driver Effects , 2012, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[20]  C. Zhai,et al.  Analysis of drivers' characteristics on continuum model with traffic jerk effect , 2018, Physics Letters A.

[21]  P. I. Richards.  Shock Waves on the Highway , 1956 .

[22]  Haijun Huang,et al.  An extended macro traffic flow model accounting for the driver’s bounded rationality and numerical tests , 2017 .

[23]  Zhongke Shi,et al.  An improved car-following model considering headway changes with memory , 2015 .

[24]  Tie-Qiao Tang,et al.  Social optimum for evening commute in a single-entry traffic corridor with no early departures , 2018, Physica A: Statistical Mechanics and its Applications.

[25]  George A. Bekey,et al.  Mathematical models of public systems , 1971 .

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

[27]  Mark B. Milam,et al.  Real-Time Optimal Trajectory Generation for Constrained Dynamical Systems , 2003 .

[28]  Hai-Jun Huang,et al.  Analysis of user equilibrium for staggered shifts in a single-entry traffic corridor with no late arrivals , 2017 .

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

[30]  G. Lu,et al.  Impact of heterogeneity of car-following behavior on rear-end crash risk. , 2019, Accident; analysis and prevention.

[31]  Rongjun Cheng,et al.  Nonlinear analysis for a modified continuum model considering driver’s memory and backward looking effect , 2018, Physica A: Statistical Mechanics and its Applications.

[32]  Tie-Qiao Tang,et al.  A car-following model accounting for the driver’s attribution , 2014 .

[33]  Peter Hidas,et al.  Modelling vehicle interactions in microscopic simulation of merging and weaving , 2005 .

[34]  Hai-Jun Huang,et al.  A route-based traffic flow model accounting for interruption factors , 2019, Physica A: Statistical Mechanics and its Applications.

[35]  Hu Huang,et al.  Simulating urban growth boundaries using a patch-based cellular automaton with economic and ecological constraints , 2018, Int. J. Geogr. Inf. Sci..

[36]  Lishan Liu,et al.  A modified lattice model of traffic flow with the consideration of the downstream traffic condition , 2019, Modern Physics Letters B.

[37]  Soyoung Ahn,et al.  Freeway traffic oscillations: Microscopic analysis of formations and propagations using Wavelet Transform , 2011 .

[38]  K. Ahmed.  Modeling drivers' acceleration and lane changing behavior , 1999 .

[39]  Liang Zheng,et al.  A simple nonparametric car-following model driven by field data , 2015 .

[40]  Henry X. Liu,et al.  Boundedly Rational User Equilibria (BRUE): Mathematical Formulation and Solution Sets , 2013 .

[41]  Liang Chen,et al.  Analysis of trip cost allowing late arrival in a traffic corridor with one entry and one exit under car-following model , 2019 .

[42]  Yu Guizhen,et al.  A Stochastic LWR Model with Consideration of the Driver's Individual Property , 2012 .

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

[44]  Du Jun,et al.  A compound compensation method for car-following model , 2016, Commun. Nonlinear Sci. Numer. Simul..

[45]  姜锐,et al.  ANALYSIS OF THE STRUCTURAL PROPERTIES OF THE SOLUTIONS TO SPEED GRADIENT TRAFFIC FLOW MODEL , 2004 .

[46]  H. M. Zhang,et al.  Analysis of mixed traffic flow with human-driving and autonomous cars based on car-following model , 2017 .

[47]  Boris S. Kerner,et al.  Local cluster effect in different traffic flow models , 1998 .

[48]  Changxi Ma,et al.  Developing a Coordinated Signal Control System for Urban Ring Road Under the Vehicle-Infrastructure Connected Environment , 2018, IEEE Access.

[49]  T. Nagatani.  Traffic Jam and Shock Formation in Stochastic Traffic-Flow Model of a Two-Lane Roadway , 1994 .

[50]  Harilaos N. Koutsopoulos,et al.  A microscopic traffic simulator for evaluation of dynamic traffic management systems , 1996 .

[51]  Hongxia Ge,et al.  Two velocity difference model for a car following theory , 2008 .

[52]  Jian Zhang,et al.  Modeling electric bicycle’s lane-changing and retrograde behaviors , 2018 .

[53]  G. H. Peng,et al.  A novel macro model of traffic flow with the consideration of anticipation optimal velocity , 2014 .

[54]  T. Nagatani.  Stabilization and enhancement of traffic flow by the next-nearest-neighbor interaction. , 1999, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[55]  Changxi Ma,et al.  Distribution path robust optimization of electric vehicle with multiple distribution centers , 2018, PloS one.

[56]  Samer H. Hamdar.  Modeling driver behavior as a stochastic hazard-based risk-taking process , 2009 .

[57]  Wen-Long Jin,et al.  A Multi-commodity Lighthill-Whitham-Richards Model of Lane-changing Traffic Flow☆ , 2013 .

[58]  Masayoshi Tomizuka,et al.  Lane change maneuver of automobiles for the intelligent vehicle and highway system (IVHS) , 1994, Proceedings of 1994 American Control Conference - ACC '94.

[59]  Wen-Long Jin.  A kinematic wave theory of lane-changing traffic flow , 2005 .

[60]  Soyoung Ahn,et al.  The effects of lane-changing on the immediate follower : anticipation, relaxation, and change in driver characteristics , 2013 .

[61]  Liang Chen,et al.  Modeling pedestrian flow accounting for collision avoidance during evacuation , 2018, Simul. Model. Pract. Theory.

[62]  Chao Wang,et al.  The Effect of Lane-Change Maneuvers on a Simplified Car-Following Theory , 2008, IEEE Transactions on Intelligent Transportation Systems.

[63]  T. Nagatani,et al.  Self-organization and phase transition in traffic-flow model of a two-lane roadway , 1993 .

[64]  R. Jiang,et al.  A new continuum model for traffic flow and numerical tests , 2002 .

[65]  H. Ge,et al.  Analysis of a novel lattice hydrodynamic model considering predictive effect and flow integral , 2019, Physica A: Statistical Mechanics and its Applications.

[66]  Rui Jiang,et al.  A behaviour based cellular automaton model for pedestrian counter flow , 2016 .

[67]  Gaetano Fusco,et al.  Artificial Neural Network Models for Car Following: Experimental Analysis and Calibration Issues , 2014, J. Intell. Transp. Syst..

[68]  Jian Zhang,et al.  A cellular automation model accounting for bicycle’s group behavior , 2018 .

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

[70]  Rongjun Cheng,et al.  An extended car-following model considering driver’s memory and average speed of preceding vehicles with control strategy , 2019, Physica A: Statistical Mechanics and its Applications.

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

[72]  Rongjun-Cheng,et al.  Mean-field flow difference model with consideration of on-ramp and off-ramp , 2019, Physica A: Statistical Mechanics and its Applications.

[73]  JiYe Zhang,et al.  Trajectory planning and yaw rate tracking control for lane changing of intelligent vehicle on curved road , 2011 .

[74]  Bin Jia,et al.  A data-driven lane-changing model based on deep learning , 2019, Transportation Research Part C: Emerging Technologies.

[75]  Hai-Jun Huang,et al.  Analysis of the equilibrium trip cost without late arrival and the corresponding traffic properties using a car-following model , 2016 .

[76]  Jian Zhang,et al.  A speed guidance strategy for multiple signalized intersections based on car-following model , 2018 .

[77]  Wen-Xing Zhu,et al.  Analysis of feedback control scheme on discrete car-following system , 2018, Physica A: Statistical Mechanics and its Applications.

[78]  Changxi Ma,et al.  Road screening and distribution route multi-objective robust optimization for hazardous materials based on neural network and genetic algorithm , 2018, PloS one.

[79]  S. Dai,et al.  Stabilization effect of traffic flow in an extended car-following model based on an intelligent transportation system application. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[80]  Cheng Deng,et al.  Electric vehicle’s energy consumption of car-following models , 2013 .

[81]  Hongzhuan Zhao,et al.  Nonlinear analysis of a new lattice hydrodynamic model with the consideration of honk effect on flux for two-lane highway , 2019, Physica A: Statistical Mechanics and its Applications.

[82]  Rongjun Cheng,et al.  Nonlinear analysis of an improved continuum model considering mean-field velocity difference , 2019, Physics Letters A.

[83]  Tomer Toledo,et al.  Modeling Duration of Lane Changes , 2007 .

[84]  Kun Cao,et al.  A dynamic automated lane change maneuver based on vehicle-to-vehicle communication , 2016 .

[85]  V. K. Katiyar,et al.  A new anisotropic continuum model for traffic flow , 2006 .

[86]  Myoungho Sunwoo,et al.  Local Path Planning for Off-Road Autonomous Driving With Avoidance of Static Obstacles , 2012, IEEE Transactions on Intelligent Transportation Systems.

[87]  Rongjun Cheng,et al.  An extended lattice hydrodynamic model considering the delayed feedback control on a curved road , 2019, Physica A: Statistical Mechanics and its Applications.

[88]  Keqiang Li,et al.  Lane changing intention recognition based on speech recognition models , 2016 .

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

[90]  Hongliang Yuan,et al.  Autonomous vehicle collision avoidance system using path planning and model-predictive-control-based active front steering and wheel torque control , 2012 .

[91]  Bin Ran,et al.  A dynamic lane-changing trajectory planning model for automated vehicles , 2018, Transportation Research Part C: Emerging Technologies.

[92]  Ge Hong-Xia,et al.  An extended continuum model considering optimal velocity change with memory and numerical tests , 2018 .

[93]  Tie-Qiao Tang,et al.  A speed guidance model accounting for the driver’s bounded rationality at a signalized intersection , 2017 .

[94]  Hongchao Liu,et al.  Analysis of asymmetric driving behavior using a self-learning approach , 2013 .

[95]  Tie-Qiao Tang,et al.  An improved car-following model accounting for the preceding car’s taillight , 2018 .

[96]  Rongjun Cheng,et al.  KdV–Burgers equation in a new continuum model based on full velocity difference model considering anticipation effect , 2017 .

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

[98]  Xin Lin,et al.  Quantitative cellular automaton model and simulations of dendritic and anomalous eutectic growth , 2019, Computational Materials Science.

[99]  A. Gupta,et al.  Jamming transitions and the effect of interruption probability in a lattice traffic flow model with passing , 2015 .

[100]  Fuqiang Liu,et al.  A DYNAMICAL MODEL WITH NEXT-NEAREST-NEIGHBOR INTERACTION IN RELATIVE VELOCITY , 2007 .

[101]  Ge Hong-Xia,et al.  The nonlinear analysis for a new continuum model considering anticipation and traffic jerk effect , 2018 .

[102]  Taixiong Zheng,et al.  An extended continuum model incorporating the electronic throttle dynamics for traffic flow , 2018 .

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

[104]  Rongjun Cheng,et al.  An extended macro traffic flow model accounting for multiple optimal velocity functions with different probabilities , 2017 .

[105]  Wen-Xing Zhu,et al.  Analysis of car-following model with cascade compensation strategy , 2016 .

[106]  Henry X. Liu,et al.  Bounded rationality and irreversible network change , 2011 .