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Traffic incidents generate adverse impacts in many areas, including traffic flow, air pollution, fuel consumption, and secondary crashes; therefore, it is vital for traffic incident responders and operators to know how they can improve the efficiency of traffic incident management. This paper presents the results of an investigation of the effects of traffic accident characteristics on accident clearance time using fully parametric hazard-based duration models with emphasis on the accelerated failure time metric. Accident characteristics and clearance times were obtained from Abu Dhabi, the capital of the United Arab Emirates. The data were obtained from the Federal Traffic Statistics System and the records of the Abu Dhabi Collision Investigation Branch for the period from May 2009 to April 2010. For the purpose of this study, clearance time was defined as the length of time from the arrival of the collision investigator on the accident scene to the departure of the collision investigator from the scene. According to the goodness-of-fit test conducted in the study, the Weibull model without gamma heterogeneity was used. The estimation results show that various accident characteristics significantly affect clearance time; these characteristics include month, location, weather condition, accident type, number of causalities, and number of vehicles involved. These results highlight some weak points in the current practices of clearing accidents in Abu Dhabi. Accordingly, this paper suggests some mitigation measures.

A nested logit (NL) model is proposed to analyze household travel behavior in developing countries. There has been an increase in vehicle ownership and chronic congestion in urban areas of such countries. The investigation is focused mainly on household travel behavior variations relating to vehicle ownership, mode choice, and trip-chaining considerations; an NL approach is used. The nest structure consists of two levels: the upper level represents car ownership, motorcycle ownership, and no-vehicle ownership choices, and the lower level shows household-based mode choices. Because the sharing of a vehicle by family members for multiple destinations is very popular in developing countries, trip chaining by primary and secondary household members is one of the mode-choice options considered in the proposed model. The developed NL model is also applied for analyzing congestion-reduction policy using a “push and pull” strategy, in which a road-pricing scheme is considered for car and motorcycle travel in the central business district together with fare reduction in public transportation. The model and the policies are verified using the Bangkok metropolitan region as a case study.

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