One of the great endeavours taken by transportation engineers to alleviate congestion is the development of advanced transportation information systems (ATIS). By providing accurate traffic information drivers could economize on travel time promoting network wide savings and benefits. However, recent attempts to predict the expected effect of ATIS systems are based on the assumption that the behaviour of individual travellers can be approximated with the assertion that they maximize expected utility. That is, individual travellers are assumed to minimize expected trip costs (or trip disutility) choosing the most efficient routes between any given origin anddestination, with a system resulting in a stable network equilibrium. This modelling approach, although elegant and parsimonious, has been criticized for lacking a sound psychological basis ignoring drivers' cognitive limitations. Whereas almost all studies agree that people deviate from the normative maximization predictions, different generalizations (of previous behavioural research) imply deviations in different directions. This severely restricts the possibility of integrating behavioural insights into a travel behavior model with practical forecasting capabilities. Robust derivation of the implications of the behavioural research requires better understanding of behaviour under the conditions that characterize drivers routedecisions. To achieve this goal the current research examines experimentally choice behaviour in an environment in which the decision makers receive partial real time information about the ranges of travel times (i.e. variability), and can rely also on their personal experience through immediate feedback. The results of the study will be used to refine current transportation models with the addition of more robust assumptions concerning the behaviour of the human agents. A hypothetical example of a driver who faces information about average travel times and travel time ranges (deviation around the mean), regarding the choice between two routes from work to home in three traffic scenarios is presented. An experiment based on the hypothetical example investigates the combined effects of information and experience on route choice decisions in a simulated environment whereby theparticipants can rely on a description of travel time variability and at the same time can rely also on personal experience through feedback. The experiment consisted of a simple two route network, one route on average faster than the other with three traffic scenarios representing different travel time ranges. Respondents were divided to two groups: with real-time information and without. Both groups received feedback information of theiractual travel time. During the experiment, participants chose repeatedly between the routes and across scenarios. The results show that effect of information is positive and is more evident when participants lack long-term experience on the distributions of travel times. Furthermore, information seems to increase initial risk seeking behaviour, reduce initial exploration and contribute to differences in attitude to risk among participants.These findings have implications for cost-effective ATIS design especially in the conditions characterized by non recurrent congestion which are difficult to predict in advance. For the covering abstract see ITRD E137145.
Samenvatting