Use of crash surrogates and exceedance statistics to estimate road safety

Tarko, Andrew P.

doi:10.1016/j.aap.2011.07.008

Cited by 154 publications

(58 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…High-fidelity simulators can realistically replicate studied scenarios at much lower risk to the participating subjects and at higher efficiency levels than real-world studies (Yang et al, 2011). A few driving simulator studies have investigated relationships between road alignment and driver behavior (Godley et al, 2002;Bella, 2005;Tarko, 2011;Easa and Ganguly, 2005;Furtado et al, 2002). Godley et al (2002) found a close correlation between driving speeds in an advanced simulator and on roads.…”

Section: Surrogate Measures and Driving Performancementioning

confidence: 97%

The influence of combined alignments on lateral acceleration on mountainous freeways: a driving simulator study

Wang

Tarko³

et al. 2015

Accident Analysis & Prevention

View full text Add to dashboard Cite

Section: Surrogate Measures and Driving Performancementioning

confidence: 97%

The influence of combined alignments on lateral acceleration on mountainous freeways: a driving simulator study

Wang

Tarko³

et al. 2015

Accident Analysis & Prevention

View full text Add to dashboard Cite

“…Automatic tracing of trajectories from video recordings is a recent and promising technology that addresses these questions (5,6), but the problem of predicting the safety benefit of a new geometry or circulation scheme remains. Some functions linking simulated conflicts and crash predictions were obtained (7)(8)(9), but the connection between surrogates and crashes is still relatively unknown.…”

mentioning

confidence: 99%

Validation of the Surrogate Safety Assessment Model for Assessment of Intersection Safety

Vasconcelos

Neto

Seco

et al. 2014

Transportation Research Record

View full text Add to dashboard Cite

The surrogate safety assessment model (SSAM) is a software application that reads trajectory files generated by microscopic simulation programs and calculates surrogate measures of safety. This approach eliminates the subjectivity associated with the conventional conflict analysis technique and allows assessment of the safety of a facility under a controlled environment before accidents occur. The specific goal of this research was to validate SSAM as a tool for accident prediction at urban intersections. Two methods were used for validation. The first method compared the simulated number of conflicts from the use of SSAM and the predicted number of injury accidents from analytic models in three reference intersection layouts (four-leg priority intersection, four-leg staggered intersection, and single-lane roundabout). The second method compared SSAM results with conflicts observed on site in four real intersections: two priority ones and two roundabouts. The results indicate that, despite some limitations related to the nature of current traffic microsimulation models, SSAM analysis is an extremely promising approach to assessing the safety of new facilities or innovative layouts.In urban areas, traffic accidents are usually concentrated at intersections. Traditional approaches to estimating the potential risk of traffic accidents at intersections, which are based on historical crash data, include before-and-after analyses and accident prediction models. Both approaches have important limitations related to the complexity of safety factors and the poor quality of data, thus (a) compared with other traffic events, accidents are quite exceptional in that they result from a series of unhappy improbable actions and situations; (b) accidents are rare events, so it is troublesome to base traffic safety analyses at individual sites on accidents alone; (c) not all accidents are reported, and the level of underreporting depends on the accident's severity and types of road users involved; and (d) information on the circumstances preceding an accident is seldom available (1). In addition, the fact that accidents must occur before one can determine the risk of locations is, from an ethical point of view, a dis advantage (2). Therefore, specific evaluation techniques are required to take into account changes in traffic regulations or in the geometrical design of infrastructure so as to estimate the true effects of safety improvements. Moreover, regression models may not be transferable because they implicitly reflect road users' behavior, the vehicle fleet, and driving rules, which vary from country to country and even from site to site.The traffic conflict technique is an approach that overcomes the lack of good, reliable accident records, relying instead on observations of conflicts. A "conflict" is defined as a situation in which two or more road users approach each other in time and space such that they risk colliding if their movements remain unchanged (3). The necessary evasive action is usually braking but may also b...

show abstract

“…These data limitations motivate the development of surrogate measures of safety and non-crash-based safety estimation approaches. The recently proposed non-crash-based approaches include extreme value theory (EVT) approach (Songchitruksa & Tarko, 2006;Tarko, 2012), probabilistic framework for automated road safety analysis (Saunier & Sayed, 2008), and causal model (Davis et al, 2011). The EVT is of interest in this study because of its capability to estimate the probability of extreme rare events from relatively short time period observations, and this is in line with Threshold Approach for Road Safety Estimation 77 the objective of surrogate measures of safety, which is to use more observable traffic events to predict less frequent crashes.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Peak Over Threshold Approach for Road Safety Estimation

Zheng

Ismail

Meng

2014

Journal of Transportation Safety & Security

View full text Add to dashboard Cite

Development of non-crash-based safety estimation approaches has drawn considerable research interest, and the application of extreme value theory is one of them. This study proposes the use of extreme value theory based peak over threshold (POT) approach for road safety estimation and compares the POT with the crash-based negative binomial regression approach. The traffic data is from videos recorded at 29 directional segments with time duration of approximately 3 h each. The results show that the best fitted model comes from regression model with R 2 of 0.65, in which the covariate is return levels estimated from POT approach. Meanwhile, the POT estimated crashes also have relatively high R 2 value but with large variances. Both of these imply that POT estimations from short observation time carry useful safety information. Moreover, the POT estimated return levels can be employed as a covariate for building better regression models.

show abstract

Use of crash surrogates and exceedance statistics to estimate road safety

Cited by 154 publications

References 29 publications

The influence of combined alignments on lateral acceleration on mountainous freeways: a driving simulator study

The influence of combined alignments on lateral acceleration on mountainous freeways: a driving simulator study

Validation of the Surrogate Safety Assessment Model for Assessment of Intersection Safety

Evaluation of Peak Over Threshold Approach for Road Safety Estimation

Contact Info

Product

Resources

About