Abstract

Adelaide, South Australia is a city with a long tradition of state of the art planning of its urban development and transport systems. As a planned ‘new world’ city it has largely escaped many of the traffic and environmental problems that beset other cities. An ongoing feature of its transport planning has been a readiness to adopt, adapt and attempt innovative solutions that are arguably ‘world’s firsts’. This chapter describes two such solutions from the last quarter of the twentieth century: a guided busway and a fully reversible one-way road. Further developments using Intelligent Transport Systems (ITS) technologies to meet community goals for improved public transport operations are also described. Document type: Part of book or chapter of book

Abstract

The ultimate purpose of the transport system is to serve the needs and expectations of the end users, who in turn shape the system by their own behaviour, actions and investments. This paper examines, within the framework of the Large Technological Systems theory the possibility to categorise users of the transport system into homogeneous segments on the basis of their differences in daily mobility and transportation of goods. Furthermore, the potential to deepen this segmentation to describe the needs of, but later in the policy process also the social acceptance by, different user groups for new transport technology or policy, is examined.

Abstract

Much of earlier work on predictive models for accidents has been focused on rural traffic or urban intersections. This work has aimed at identifying and investigating possible improvements to predictive models for accidents on urban links. A special focus has been on the accidents of vulnerable road users."br /" "br /" The possible improvements investigated have been: a) the use of exposure data for vulnerable road users, b) the use of actual vehicle speeds, c) to separate vehicle accidents into single vehicle and multiple vehicle accidents and model each type separately."br /" "br /" The study involved eight Swedish cities, of which six were included in the development of accident models. In addition to police-reported traffic accidents, data for the models were collected in specific field studies and partly from the cities."br /" "br /" The study shows that the inclusion of exposure data for vulnerable road users in the models for vulnerable road users? accidents greatly improves the predictive ability of the models. Vehicle speeds were found to be very difficult to use in the models as vehicle speeds are highly correlated with most of the other variables and make the model coefficients unstable. The separate modelling of single and multiple vehicle accidents failed partly as the single vehicle accidents were too few for constructing sound models. The models for multiple vehicle accidents developed, however, had a better predictive ability than models for all vehicle accidents. Land use was the next important explanatory variable for most accident types after the exposure variables."br /" "br /" Accident models were developed with one data set and validated with another data set. The models performed very well in prediction by explaining between 71% and 81% of the systematic variation in the validation data. The validation indicated that exponents were 0.5 for both the flows of pedestrians and motor vehicles in models for accidents involving vulnerable road users, and 1.0 for the motor vehicle flow exponent in the models for motor vehicle accidents. For bicyclist accidents the correct exponent for bicyclist flows is likely to be somewhat lower than 0.5, close to 0.35."br /" "br /" The study also recommended practical uses for the models, listed the lessons learned from the modelling as well as proposed a number of topics for further research.