Examination of factors affecting freeway incident clearance times: a comparison of the generalized <i>F</i> model and several alternative nested models

Ghosh, Indrajit; Savolainen, Peter T.; Gates, Timothy J.

doi:10.1002/atr.1189

Cited by 39 publications

(36 citation statements)

References 39 publications

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“…For the travel time, the hazard function is a monotonically increasing function, which suggests that the likelihood that the stage will end increases only with the length of time that has already occurred; similar results have been obtained with regard to the hazard function of crash durations or traffic hazard-related accidents [23]. With regard to clearance time, the estimated hazard function is initially shown to decrease up to the minimum at an inflection point, is reached, then increases over time, which indicates that the probability of an accident being cleared quickly is highest during the period after the police first arrives on the scene, which coincides with the findings of other studies [22]. Table 2 lists the results of the coefficient estimation analysis for various accident duration stages.…”

Section: Study Resultssupporting

confidence: 63%

“…With regard to distribution, Ghosh et al [22] found that the generalized F distribution is the best fit for the incident clearance time data from the southeastern Michigan freeway network. In this study, longer clearance times were observed during the winter months on road segments with horizontal curves when accidents required the closure of travel lanes, affected adjacent traffic, or exit ramps were unavailable for motorists or FCP responders.…”

Section: Literature Reviewmentioning

confidence: 98%

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Analysis of the Different Duration Stages of Accidents with Hazard-Based Model

Guo²,

2015

Int. J. ITS Res.

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This study investigates and identifies significant contributing variables that affect the duration of three traffic accident stages, namely, preparation, travel, and clearance as well as the total duration of the accident. Accelerated failure time (AFT) hazard-based models were developed with different underlying probability distributions for the hazard function, including models with gamma heterogeneity and models with time-varying covariates. The results indicate that the gamma distribution model with a time variable is the best model for the four different duration stages, and different parameters and variables were appropriate for modeling the different duration stages of traffic accidents. The findings of this study provide an important demonstration of method and an empirical basis for accident management programs.

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Section: Study Resultssupporting

confidence: 63%

Section: Literature Reviewmentioning

confidence: 98%

Analysis of the Different Duration Stages of Accidents with Hazard-Based Model

Guo²,

2015

Int. J. ITS Res.

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“…Their analysis suggested the random parameter Weibull structure to be suitable for incident duration resulting from crashes and hazards, and the fixed parameter Weibull structure with Gamma heterogeneity to be suitable for modelling incident duration resulting from stationary vehicles. As a further instance, Ghosh et al introduced the application of generalized F distribution for freeway incident clearance time AFT modelling and found this structure to outperform five other nested parametric structures.…”

Section: Literature Reviewmentioning

confidence: 99%

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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“…Ghosh et al found that the generalized F distribution was the best‐fit distribution compared with other distributions. They based their study on the incident clearance data from southeastern Michigan freeway network.…”

Section: Literature Reviewmentioning

confidence: 99%

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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Examination of factors affecting freeway incident clearance times: a comparison of the generalized F model and several alternative nested models

Cited by 39 publications

References 39 publications

Analysis of the Different Duration Stages of Accidents with Hazard-Based Model

Analysis of the Different Duration Stages of Accidents with Hazard-Based Model

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

Competing risks analysis on traffic accident duration time

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