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Car ownership and use in the Kingdom of Saudi Arabia (KSA) are very high due to the high income, the low fuel prices and the near absence of public transportation in the Kingdom. Currently, the Kingdom is going through a massive transformation and entering a new era of national reforms. One of the main aims of the national reforms is to reduce car dependency and enhance more sustainable options of travel such as public transportation in the KSA. In order to achieve such an aim, there are two hurdles: Firstly, there must be a provision of decent public transportation options, and secondly, there is a need to influence travel behaviour and encourage the shift from private cars to public transportation. For example, in Riyadh city, an impressive metro system is being constructed and will start operation in 2023. To influence travel behaviour, travel demand management measures (TDM), in particular pricing measures, can be adopted and implemented, in order to help and support achieving the target. The main aim of this paper, therefore, is to assess the attitudes of Saudi nationals towards—and willingness to accept—pricing measures and their possible impacts on their travel behaviour in the city of Riyadh. The methodology includes collecting data using an online survey on travel behaviour and attitudes in Riyadh and calibrating multinomial logit modal choice models. The participants in the survey were asked to report their support of the pricing measures for the objective of reducing congestion in the city, improving road safety or reducing travel time. The results show the highest support towards pricing measures for improving road safety, reducing travel times and, lastly, reducing congestion in the city. [ABSTRACT FROM AUTHOR]

The introduction of autonomous vehicles has been considered as a possible option for reducing traffic congestion in many transport studies. Many types of models, in particular car-following microsimulation models have been adopted in most studies. The impacts of autonomous vehicles (AVs) on congestion, however, have not yet been concluded. This could be because different researchers use different forms of car-following models to assess these impacts, or because the utilised modelling approaches and their parameters are different in different studies. In particular, two of the important parameters that are associated with car-following models are the used values for maximum acceleration and the average desired time gaps. While the values of these parameters can be adjusted and controlled by the ACC controllers in the AV, they can also be controlled by the users. Therefore, assigning unrealistic values to these parameters could well result in unrealistic conclusions. This paper investigated the impacts of the maximum acceleration and the average desired time gaps on congestion levels using the loss-time indicator. The analysis was carried out on the Hanshin expressway in Japan and was tested and assessed using the Helly (FACC) car-following microsimulation model. This includes estimating the values of the desired time gap from real traffic time-gap distributions. The Hanshin expressway is an urban toll highway of 273 km that extends from Osaka to Kobe, representing the Hanshin area in Japan. The Hanshin highway serves a huge traffic volume that consists of private and freight vehicles that operate within the Hanshin area. This area represents one of three major municipal areas in Japan including Tokyo and Nagoya. A total of 740,000 vehicles per day travel on the expressway. As a result, there is significant congestion on the Hanshin expressway. There have been various plans put in place to ease congestion ranging from building new roads to the implementation of traffic-demand-management measures. However, the predictions of the impacts of such measures do not provide any evidence that they would ease traffic congestion. Other possible measures that could be investigated for easing traffic congestion include technology-based solutions such as autonomous vehicles. The modelling results recommend that the results obtained from microsimulation models should be taken with care, and good attention should be paid to the parameters used and their values in the model. The values assigned to driving-behaviour parameters, the maximum values of acceleration, and the time-gap settings, for example, control the final outcomes of the models. [ABSTRACT FROM AUTHOR]

This paper examines pedestrian anatomical injuries and crash characteristics in back-to-traffic and facing-traffic crashes. Pedestrian crashes involving pedestrians walking along streets (i.e. with their backs to traffic or facing traffic) have been overlooked in literature. Although this is not the most frequent type of crash, the crash consequence to pedestrians is a safety concern. Combining Taiwan A1A2 police-reported accident data and data from the National Health Insurance Database from years 2003-2013, this paper examines anatomical injuries and crash characteristics in back-to-traffic and facing-traffic crashes. There were a total of 830 and 2267 pedestrian casualties in back-to-traffic and facing-traffic crashes respectively. The injuries sustained by pedestrians and crash characteristics of these two crash types were compared with those of other crossing types of crashes (nearside crash, nearside dart-out crash, offside crash, and offside dart-out crash). Odds of various injuries to body regions were estimated using logistic regressions. Key findings include that the percentage of fatalities in back-to-traffic crashes is the highest; logistic models reveal that pedestrians in back-to-traffic crashes sustained more head, neck, and spinal injuries than did pedestrians in other crash types, and unlit darkness and non-built-up roadways were associated with an increased risk of pedestrian head injuries. Several crash features (e.g. unlit darkness, overtaking manoeuvres, phone use by pedestrians and drivers, and intoxicated drivers) are more frequently evident in back-to-traffic crashes than in other types of crashes. The current research suggests that in terms of crash consequence, facing traffic is safer than back to traffic. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents an investigation into the impacts of the introduction of congestion charges on shopping trips in Edinburgh. Other transport policies such as parking costs, public transport costs and petrol fees have also been investigated, using logistic regression analysis. The results indicate a potential reduction in car shopping trips to the City Centre as a result of introducing congestion charging and a possible increase in shopping trips by other modes. Traffic congestion does not seem to be the main barrier for people to shop at the City Centre; rather access to and availability of parking spaces most affect the accessibility of the City Centre. Moreover, the introduction of congestion charges may result in the improvement of accessibility of public transport as well as reductions in traffic congestion allowing better access into the City Centre. [Copyright &y& Elsevier]