Travel information continues to receive significant attention in the field of travel behaviour research, as it is expected to help reduce congestion by directing the network state from a user equilibrium towards a more efficient system optimum. This literature review contributes to the existing literature in at least two ways. First, it considers both the individual perspective and the network perspective when assessing the potential effects of travel information, in contrast to earlier studies. Secondly, it highlights the role of bounded rationality as well as that of non-selfish behaviour in route choice and in response to information, complementing earlier reviews that mostly focused on bounded rationality only. It is concluded that information strategies should be tailor-made to an individual's level of rationality as well as level of selfishness in order to approach system-optimal conditions on the network level. Moreover, initial ideas and future research directions are provided for assessing the potential of travel information in order to improve network efficiency of existing road networks. ARTICLE HISTORY

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Incorporation of externalities in the Multi-Objective Network Design Problem (MO NDP) as objectives is an important step in designing sustainable networks. In this research the problem is defined as a bi-level optimization problem in which minimizing externalities are the objectives and link types which are associated with certain link characteristics are the discrete decision variables. Two distinct solution approaches for this multi-objective optimization problem are compared. The first heuristic is the non-dominated sorting genetic algorithm II (NSGA-II) and the second heuristic is the dominance based multi objective simulated annealing (DBMO-SA). Both heuristics have been applied on a small hypothetical test network as well as a realistic case of the city of Almelo in the Netherlands. The results show that both heuristics are capable of solving the MO NDP. However, the NSGA-II outperforms DBMO-SA, because it is more efficient in finding more non-dominated optimal solutions within the same computation time and maximum number of assessed solutions.

Although travel time is probably one of the most important attributes in route choice, the shortest time route is often not the preferred route, according to several studies in the literature. This study tries to explain this finding by testing the hypothesis that choice makers may be able to estimate travel times correctly for routes that they prefer but are biased against alternatives even if these are faster. For a few choice sets of routes in the city of Enschede, Netherlands, respondents were asked to choose a route and provide their estimated travel times for both the preferred and the alternative routes. These travel times were then compared with actual travel times from a license plate study. The comparison confirmed the hypothesis. For chosen routes, perceived travel times correspond quite well with actual travel times on average, whereas for routes not chosen, perceived travel times are overestimated by 3 to 4 min on average. These results show that drivers are not able or do not want to evaluate routes objectively. This finding implies that within an indifference band of route delay or travel time inequality of on average 3 to 4 min, drivers are probably not willing to alter their route choice, even if the traffic situation, induced, for example, by traffic management measures, changes in a negative way for their preferred route.