Safety analysis of passing maneuvers using extreme value theory

The increased availability of detailed trajectory data sets from naturalistic, observational and simulation-based studies are a key source for potential improvements in the development of detailed safety models that explicitly account for vehicle conflict interactions and the various driving maneuvers. Despite the well-recognized research findings on both crash frequency estimation and traffic conflicts analysis carried out over the last decades, only recently researchers have started to study and model the link between the two. This link is typically made by statistical association between aggregated conflicts and crashes, which still relies on crash data and ignores heterogeneity in the estimation procedure. More recently, an Extreme Value (EV) approach has been used to link the probability of crash occurrence to the frequency of conflicts estimated from observed variability of crash proximity, using a probabilistic framework and without using crash records. In this on-going study the Generalized Extreme Value (GEV) distribution and the Generalized Pareto Distribution (GPD)-based estimation, in the peak over threshold approach, are tested and compared as EV methods using the minimum time-to-collision with the opposing vehicle during passing maneuvers. Detailed trajectory data of the passing, passed and opposite vehicles from a fixed-based driving simulator experiment was used in this study. One hundred experienced drivers from different demographic strata participated in this experiment on a voluntary base. Several two-lane rural highway layouts and traffic conditions were also considered in the design of the simulator environment. Raw data was collected at a resolution of 0.1 s and included the longitudinal and lateral position, speed and acceleration of all vehicles in the scenario. From this raw data, the minimum time-to-collision with the opposing vehicle at the end of the passing, maneuver was calculated. GEV distributions based on the Block Maxima approach and GPD distributions under the POT approach were tested for the estimation of head-on collision probabilities in passing maneuvers with different results. While the GEV approach achieved satisfactory fitting results, the tested POT underestimated the expected number of head-on collisions. Finally, the estimated GEV distributions were validated using a second set of data extracted from an additional driving simulator experiment. The results indicate that this is a promising approach for safety evaluation. On-going work of the authors will attempt to generalize this method to other safety measures related to passing maneuvers, test it for the detailed analysis of the effect of demographic factors on passing maneuvers’ crash probability and for its usefulness in a traffic simulation environment

[1]  Daniela Jarušková,et al.  Peaks over threshold method in comparison with block-maxima method for estimating high return levels of several Northern Moravia precipitation and discharges series , 2006 .

[2]  M M Minderhoud,et al.  Extended time-to-collision measures for road traffic safety assessment. , 2001, Accident; analysis and prevention.

[3]  Christian J. Jerome,et al.  Time-to-Collision Judgments Under Realistic Driving Conditions , 2006, Hum. Factors.

[4]  Geertje Hegeman,et al.  Assisted overtaking: An assessment of overtaking on two-lane rural roads , 2008 .

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

[6]  R. Fisher,et al.  Limiting forms of the frequency distribution of the largest or smallest member of a sample , 1928, Mathematical Proceedings of the Cambridge Philosophical Society.

[7]  Carlos Llorca,et al.  Evaluation of Passing Process on Two-Lane Rural Highways in Spain with New Methodology Based on Video Data , 2011 .

[8]  C. Ireland Fundamental concepts in the design of experiments , 1964 .

[9]  Tarek Sayed,et al.  Traffic conflict standards for intersections , 1999 .

[10]  John C Hayward,et al.  NEAR-MISS DETERMINATION THROUGH USE OF A SCALE OF DANGER , 1972 .

[11]  Praprut Songchitruksa,et al.  The extreme value theory approach to safety estimation. , 2006, Accident; analysis and prevention.

[12]  L. Haan,et al.  On the block maxima method in extreme value theory: PWM estimators , 2013, 1310.3222.

[13]  Sofia Caires,et al.  A comparative simulation study of the annual maxima and the peaks-over-threshold methods , 2009 .

[14]  Afshin Shariat-Mohaymany,et al.  Identifying Significant Predictors of Head-on Conflicts on Two-Lane Rural Roads Using Inductive Loop Detectors Data , 2011, Traffic injury prevention.

[15]  Tomer Toledo,et al.  Passing Behavior on Two-Lane Highways , 2010 .

[16]  C. Hydén THE DEVELOPMENT OF A METHOD FOR TRAFFIC SAFETY EVALUATION: THE SWEDISH TRAFFIC CONFLICTS TECHNIQUE , 1987 .

[17]  Tarek Sayed,et al.  Surrogate Safety Assessment Model and Validation: Final Report , 2008 .

[18]  Leonie Kohl,et al.  Fundamental Concepts in the Design of Experiments , 2000 .

[19]  Holger Rootzén,et al.  Accident Analysis and Prevention , 2013 .

[20]  Larry Head,et al.  Surrogate Safety Measures from Traffic Simulation Models , 2003 .

[21]  Richard L. Smith Maximum likelihood estimation in a class of nonregular cases , 1985 .

[22]  Eric Gilleland,et al.  New Software to Analyze How Extremes Change Over Time , 2011 .

[23]  Serge P. Hoogendoorn,et al.  Overtaking Assistant Assessment Using Traffic Simulation , 2009 .

[24]  Shlomo Bekhor,et al.  Risk evaluation by modeling of passing behavior on two-lane rural highways. , 2009, Accident; analysis and prevention.

[25]  Eric P. Smith,et al.  An Introduction to Statistical Modeling of Extreme Values , 2002, Technometrics.

[26]  Karim Ismail,et al.  Freeway safety estimation using extreme value theory approaches: a comparative study. , 2014, Accident; analysis and prevention.

[27]  Christer Hydén,et al.  Estimating the severity of safety related behaviour. , 2006, Accident; analysis and prevention.

[28]  Andrew P Tarko,et al.  Use of crash surrogates and exceedance statistics to estimate road safety. , 2012, Accident; analysis and prevention.