Four car-following models with artificial neural network (ANN) structure were developed with various input variables in the car-following behavior. A four-layer ANN structure was set up and a genetic algorithm (GA) and back-propagation methodology were utilized for determining the synaptic weights in the models, however the models sometimes had a difficulty in learning such enormous number of r...

In times when reduction and changes in private car use is on the political agenda in urban areas, there is a need to better understand and forecast the process of change in car use. Traditional conceptualizations of travel choice in equilibrium may be insufficient to this end and need to be complemented. An alternative theoretical framework is therefore proposed based on goal setting and self-r...

This research-in-progress paper examines how to facilitate in-car use of multi-context mobile services such as mobile telephone calls, e-mail, news, and SMS. Because the car is a mobile context with specific convenience and safety problems, it is important to identify and explore seamless ways to use in-car resources such as dashboard control buttons, in-car audio systems, and in-car displays f...

Buckling and certain contact situations cause scattering results of numerical crash simulation: For a BMW model differences between the position of a node in two simulation runs of up to 10 cm were observed, just as a result of round-off differences in the case of parallel computing. An engineer has to measure this scatter, to check whether important parts of the car show such indeterministic b...

Encouraging people out of their cars and into other modes of transport, which has major advantages for health, the environment and urban development, has proved difficult. Greater understanding of the influences that lead people to use the car, particularly for shorter journeys, may help to achieve this. This paper examines the predictors of car use compared with the bicycle to explore how it m...