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The uncertainty-based work zone capacity model is formulated as a mixed linear regression function of explanatory variables where capacity is a random variable following a lognormal distribution. Model parameters are calibrated using a Bayesian approach. Results show that the proposed work zone capacity distribution model can accurately predict the mean and prediction interval of work zone capacity at any given confidence level. It is found that work zones located in urban roads, with a larger number of open lanes or with long-term work duration have a larger mean work zone capacity. A short prediction interval (i.e. low uncertainty) for work zone capacity is found to be associated with the following situations: (a) a bigger number of open lanes; (b) rural work zone; (c) short-term work duration; (d) left lane closure; (e) daytime work and (f) a smaller percentage of heavy vehicles. The predicted interval length for the medium level of work intensity is increased, although the corresponding mean work zone capacity is reduced, as compared with the light level of work intensity. There will be a bigger measured work zone capacity on average if the measurement method is adopted in which work zone capacity is taken as the mean queue-discharge rate. [ABSTRACT FROM AUTHOR]

The aim of this study is to examine whether the effects of factors contributing to the severity of driver injuries vary between long-term and short-term work zones. Multinomial logistic regression analysis is adopted to model the relationship between the influencing factors and drivers' injury and fatality risks. A case study is created using drivers' injury severity data from the NASS general estimate system, and two separate multinomial logistic regression models are developed. By comparing the model results, it is found that the light conditions, day of the week, age, gender, airbag availability, restraint use, vehicle age and most harmful event show homogeneous effects on the drivers' injury and fatality risks in the two work zone types. However, the weather, speed limit, traffic control device and number of lanes exhibit opposing effects on the drivers' injury and fatality risks in the two work zone types. [ABSTRACT FROM AUTHOR]

The travel time reliability of buses has become increasingly important for public transit companies. In this study, a novel approach is proposed to evaluate and analyse the travel time reliability of bus services provided by TransLink in Queensland, Australia. In view of their stochastic features, the two components of travel time - dwell time and driving time - are represented by discrete distributed and normally distributed random variables respectively. Accordingly, the travel time could be described by Gaussian mixture models. Based on the proposed model, impact analysis shows that bus line reliability would increase by around 15% if onboard top-up for 'go cards' (electronic tickets) was not offered by TransLink. It was found that not providing this top-up method would not significantly harm the benefit of go card users, but it would substantially increase the total social benefit thanks to improved bus line reliability. [ABSTRACT FROM AUTHOR]