Hazard based models for freeway traffic incident duration

Hojati, Ahmad Tavassoli; Ferreira, Luis; Washington, Simon; Charles, Phil

doi:10.1016/j.aap.2012.12.037

Cited by 150 publications

(50 citation statements)

References 22 publications

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“…Diversion is normally required in case of a high extent of closure incurred on a road, which leads to 71.57% increase in the durations. Results of previous similar studies also highlight the significant impact of this variable of motorway crash durations. It should be pointed out that diversion requirement is decided upon by the Traffic Response Unit team members, based on the severity of incidents and the adjacent traffic conditions and is therefore exogenous with respect to crash duration in these models.…”

Section: Modelling Results and Discussionsupporting

confidence: 57%

“…Tavassoli Hojati et al also applied fixed and random parameter AFT models to examine incident duration along a set of urban motorways in Australia. Common incident types such as crash, hazard and stationary vehicles were tested through their models.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In light of the previously mentioned literature review, there still remain some fundamental research gaps. First, previous comprehensive hazard‐based duration studies and other incident data modelling techniques have applied their models on integrated datasets obtained from a number of motorways. While these studies provide in‐depth insights into the incident duration modelling problem, the stability of these models over time and their transferability to other locations is a significant research question.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Because incident duration is a major decisive factor in the estimation of total incident‐incurred delay , establishing methodologies to associate this duration with the incident‐specific characteristics, traffic‐related characteristics and temporal and infrastructural specifications becomes very crucial. In the literature , incident duration has been defined as the time difference between the detection of an incident and the moment that the response vehicles depart the incident scene. The same definition has been adopted in this study.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Motorway crash duration and its determinants: do durations vary across motorways?

Tajtehranifard

Bhaskar

Boyle

et al. 2016

J of Advced Transportation

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SUMMARYTraffic congestion has been a growing issue in many metropolitan areas during recent years, which necessitates the identification of its key contributors and development of sustainable strategies to help decrease its adverse impacts on traffic networks. Road incidents generally and crashes specifically have been acknowledged as the cause of a large proportion of travel delays in urban areas and account for 25% to 60% of traffic congestion on motorways.Identifying the critical determinants of travel delays has been of significant importance to the incident management systems, which constantly collect and store the incident duration data. This study investigates the individual and simultaneous differential effects of the relevant determinants on motorway crash duration probabilities. In particular, it applies parametric Accelerated Failure Time (AFT) hazard-based models to develop in-depth insights into how the crash-specific characteristic and the associated temporal and infrastructural determinants impact the duration. AFT models with both fixed and random parameters have been calibrated on one year of traffic crash records from two major Australian motorways in South East Queensland, and the differential effects of determinants on crash survival functions have been studied on these two motorways individually.A comprehensive spectrum of commonly used parametric fixed parameter AFT models, including generalized gamma and generalized F families, has been compared with random parameter AFT structures in terms of goodness of fit to the duration data, and as a result, the random parameter Weibull AFT model has been selected as the most appropriate model. Significant determinants of motorway crash duration included traffic diversion requirement, crash injury type, number and type of vehicles involved in a crash, day of week and time of day, towing support requirement and damage to the infrastructure. A major finding of this research is that the motorways under study are significantly different in terms of crash durations; such that motorway 1 exhibits durations that are on average 19% shorter compared with the durations on motorway 2. The differential effects of explanatory variables on crash durations are also different on the two motorways. The detailed presented analysis confirms that looking at the motorway network as a whole, neglecting the individual differences between roads, can lead to erroneous interpretations of duration and inefficient strategies for mitigating travel delays along a particular motorway.

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Section: Modelling Results and Discussionsupporting

confidence: 57%

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Motorway crash duration and its determinants: do durations vary across motorways?

Tajtehranifard

Bhaskar

Boyle

et al. 2016

J of Advced Transportation

View full text Add to dashboard Cite

show abstract

“…Although the model had large prediction error, statistical test results indicated that this model was stable over time. Tavassoli et al [24] developed parametric accelerated failure time survival models of incident duration. They found that the duration of each type of incident is uniquely different and responds to different factors.…”

Section: Literature Reviewmentioning

confidence: 99%

Traffic Incident Clearance Time and Arrival Time Prediction Based on Hazard Models

Jiang

et al. 2014

Mathematical Problems in Engineering

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Accurate prediction of incident duration is not only important information of Traffic Incident Management System, but also an effective input for travel time prediction. In this paper, the hazard based prediction models are developed for both incident clearance time and arrival time. The data are obtained from the Queensland Department of Transport and Main Roads' STREAMS Incident Management System (SIMS) for one year ending in November 2010. The best fitting distributions are drawn for both clearance and arrival time for 3 types of incident: crash, stationary vehicle, and hazard. The results show that Gamma, Log-logistic, and Weibull are the best fit for crash, stationary vehicle, and hazard incident, respectively. The obvious impact factors are given for crash clearance time and arrival time. The quantitative influences for crash and hazard incident are presented for both clearance and arrival. The model accuracy is analyzed at the end.

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Competing risks analysis on traffic accident duration time

Guo²

2014

J of Advced Transportation

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SUMMARYDifferent clearance methods in traffic accident management lead to varied duration distributions. Apart from investigating the influence of various factors associated with accidents on the duration of such accidents using different clearance methods, this study also examines the cumulative incidence probability. We used traffic accident data obtained for 12 months from the Fourth Ring Expressway main line in Beijing to develop a subdistribution hazard regression model, which can assess the risk factors of two clearance methods. The regression results show that the different factors have statistically significant effects on the duration of two accident groups with different clearance methods; furthermore, opposite effects occur even for some factors that have a strong effect on both accident groups. For example, an accident involving a taxi extends the duration time with clearance method 1; in comparison, the accident is shorter with clearance method 2. The predicted cumulative incidence curves of the two types of clearance methods are shown as examples, with stratification based on the influence factors (taxi involved, season). Finally, the Gray test of the cumulative incidence functions and the log-rank test of the Kaplan-Meier estimates of the survival functions are compared, in order to demonstrate the importance of using proper methods for analyses.

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Hazard based models for freeway traffic incident duration

Cited by 150 publications

References 22 publications

Motorway crash duration and its determinants: do durations vary across motorways?

Motorway crash duration and its determinants: do durations vary across motorways?

Traffic Incident Clearance Time and Arrival Time Prediction Based on Hazard Models

Competing risks analysis on traffic accident duration time

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