Understanding the mechanism of traffic hysteresis and traffic oscillations through the change in task difficulty level

This paper provides a detailed understanding of the mechanism of traffic hysteresis and traffic oscillations from the driver behavior perspective. Microscopic evaluation of trajectories inside seven selected oscillations is performed to obtain a comprehensive picture of these puzzling phenomena. A new method based on driver’s task difficulty (TD) profile is proposed to capture changes in driver behavior in response to the disturbance caused by traffic oscillations. A close connection between the TD profile and evolution (such as formation and growth) of the stop- and -go traffic oscillations is found. Furthermore, driver behaviors inside the oscillations are identified based on driver’s TD profile, and their connection with hysteresis magnitudes is established. Finally, a generalized linear model suggests that variables related to traffic flow and driver characteristics are significant predictors of hysteresis magnitude. One noteworthy finding is that, the bigger the difference between the average TD levels between deceleration and acceleration phases of a vehicle trajectory, the larger the hysteresis magnitude becomes.

[1]  David Herrero-Fernández Psychometric adaptation of the Driving Anger Expression Inventory in a Spanish sample: Differences by age and gender , 2011 .

[2]  G. F. Newell THEORIES OF INSTABILITY IN DENSE HIGHWAY TRAFFIC , 1962 .

[3]  A. Skabardonis,et al.  Understanding stop-and-go traffic in view of asymmetric traffic theory , 2009 .

[4]  Hui Deng,et al.  On Traffic Relaxation, Anticipation, and Hysteresis , 2015 .

[5]  Vikash V. Gayah,et al.  Clockwise Hysteresis Loops in the Macroscopic Fundamental Diagram , 2010 .

[6]  Soyoung Ahn,et al.  A behavioural car-following model that captures traffic oscillations , 2012 .

[7]  Zuduo Zhenga,et al.  Empirical Analysis on Relationship between Traffic Conditions and Crash Occurrences , 2013 .

[8]  R. S. Lynch,et al.  Anger, aggression, and risky behavior: a comparison of high and low anger drivers. , 2003, Behaviour research and therapy.

[9]  Paul Sârbescu,et al.  Aggressive driving in Romania: Psychometric properties of the Driving Anger Expression Inventory , 2012 .

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

[11]  R. S. Lynch,et al.  The driving anger expression inventory: a measure of how people express their anger on the road. , 2002, Behaviour research and therapy.

[12]  Gordon F. Newell,et al.  INSTABILITY IN DENSE HIGHWAY TRAFFIC: A REVIEW. , 1965 .

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

[14]  Danjue Chen Studies of traffic oscillations: A behavioral perspective , 2012 .

[15]  Simon Washington,et al.  Revisiting the Task-Capability interface model for incorporating human factors into car-following models , 2015 .

[16]  Ludovic Leclercq,et al.  A mechanism to describe the formation and propagation of stop-and-go waves in congested freeway traffic , 2010, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[17]  M. Treiber,et al.  Estimating Acceleration and Lane-Changing Dynamics from Next Generation Simulation Trajectory Data , 2008, 0804.0108.

[18]  R. Fuller Towards a general theory of driver behaviour. , 2005, Accident; analysis and prevention.

[19]  Soyoung Ahn,et al.  A method to account for non-steady state conditions in measuring traffic hysteresis , 2013 .

[20]  Zuduo Zheng,et al.  Recent developments and research needs in modeling lane changing , 2014 .

[21]  Soyoung Ahn,et al.  Applications of wavelet transform for analysis of freeway traffic : bottlenecks, transient traffic, and traffic oscillations , 2011 .

[22]  Zuduo Zheng,et al.  Incorporating human-factors in car-following models : a review of recent developments and research needs , 2014 .

[23]  Ray Fuller,et al.  Driver Control Theory , 2011 .

[24]  H. M. Zhang,et al.  A Car-Following Theory for Multiphase Vehicular Traffic Flow , 2003 .

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

[26]  Alexander M. Millkey The Black Swan: The Impact of the Highly Improbable , 2009 .

[27]  H. M. Zhang A mathematical theory of traffic hysteresis , 1999 .

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

[29]  Simon Washington,et al.  A parametric duration model of the reaction times of drivers distracted by mobile phone conversations. , 2014, Accident; analysis and prevention.

[30]  J Fuller PSYCHOLOGY AND THE HIGHWAY ENGINEER , 2002 .

[31]  Jorge A. Laval Hysteresis in traffic flow revisited: An improved measurement method , 2011 .

[32]  Soyoung Ahn,et al.  Impact of traffic oscillations on freeway crash occurrences. , 2010, Accident; analysis and prevention.

[33]  Eugene R. Oetting,et al.  Further Evidence of Reliability and Validity for the Driving Anger Expression Inventory , 2001, Psychological reports.

[34]  Soyoung Ahn,et al.  On the periodicity of traffic oscillations and capacity drop : the role of driver characteristics , 2014 .

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

[36]  Nancy Rhodes,et al.  Age and gender differences in risky driving: the roles of positive affect and risk perception. , 2011, Accident; analysis and prevention.

[37]  P. McCullagh,et al.  Generalized Linear Models , 1984 .

[38]  Javier Bilbao-Ubillos,et al.  The costs of urban congestion: Estimation of welfare losses arising from congestion on cross-town link roads , 2008 .