Giselle de Moraes Ramos’s research while affiliated with Delft University of Technology and other places

Travel information has the potential to influence travellers choices, in order to steer travellers to less congested routes and alleviate congestion. This paper investigates, on the one hand, how travel information affects route choice behaviour, and on the other hand, the impact of the travel time representation on the interpretation of parameter estimates and prediction accuracy. To this end, we estimate recursive models using data from an innovative data collection effort consisting of route choice observation data from GPS trackers, travel diaries and link travel times on the overall network. Though such combined data sets exist, these have not yet been used to investigate route choice behaviour. A dynamic network in which travel times change over time has been used for the estimation of both recursive logit and nested models. Prediction and estimation results are compared to those obtained for a static network. The interpretation of parameter estimates and prediction accuracy differ substantially between dynamic and static networks as well as between models with correlated and uncorrelated utilities. Contrary to the static results, for the dynamic, where travel times are modelled more accurately, travel information does not have a significant impact on route choice behaviour. However, having travel information increases the travel comfort, as interviews with participants have shown.

Despite the wide use of utility theory to model travellers' behaviour, the interest in non-expected utility theories has increased due to their potential to capture more realistic behaviour. A main question raised is whether travellers are better described as utility maximizers or should be qualified differently.This paper presents a literature review on the use of expected utility theory (EUT), prospect theory (PT) and regret theory (RT) to model travellers' behaviour. Gaps in the literature are identified and a discussion about advantages and disadvantages of each theory is presented. A case study illustrates the differences between the theories.Under certain conditions, PT and RT restrict themselves to EUT. Their added value, however, is the possibility of capturing loss aversion, risk aversion and risk-seeking (PT) and regret aversion (RT). On the practical level, the use of EUT is well established, while contributions of PT and RT are marginal. On the theoretical level, however, RT seems to be (marginally) more suitable to model travellers' behaviour, while EUT and PT are equally suitable. This suggests that the large use of EUT is highly influenced by its very tractable framework. We do not claim the superiority of any theory, but propose to compare them through a systematic review.

The use of Prospect Theory to model route choice has increased in the past decades. The main application issue is how to define the reference point, i.e., the value that travellers use as a reference to distinguish gains and losses in the experienced travel times. Moreover, the question can be asked whether all travellers have the same reference point or whether heterogeneity in their behaviour plays an important role.This paper aims to (i) provide a behavioural interpretation of the reference point, (ii) investigate the role of heterogeneity in the reference point and (iii) discuss how to take heterogeneity into account. These aspects are discussed with the aid of an empirical route choice experiment and a model specification in which travel time is the main variable. Two model frameworks are proposed, one accounting for heterogeneity and another considering no heterogeneity in travellers' behaviour, and their outcomes are compared.Results show improvements in the ability of Prospect Theory to predict route choice behaviour by accounting for heterogeneity in the reference point. This is particularly the case when the reference point reflects travelers' route preferences. Statistical analyses show the significance of accounting for heterogeneity in travellers' behaviour. Thus, we cannot reject the hypothesis that heterogeneity leads to improvements in the prediction ability of Prospect Theory.

The past decades have seen an increased interest in the role of information as a tool to alleviate congestion. However, because the relationship between travelers' behavior and information provision is not clear yet, the need for more experiments has been claimed in literature. From May 9th, 2011 to July 12th, 2011 a revealed route choice experiment was conducted in The Netherlands. With the aid of GPS devices and travel diaries, the experiment consisted of investigating the behavior of 32 commuters with similar origins and destinations in reaction to different sources and conditions of information provision. In addition, the real traffic condition during the period of the experiment is known, thus allowing us to know the traffic conditions on alternative routes. This paper presents the setup of this unique revealed preference (RP) study of route choice behavior of car travelers driving in a congested network and a comprehensive descriptive analysis of the data set(s). To our knowledge a study on route choice behavior under provision of real time information in which GPS traces, travel diaries, interviews and traffic conditions in a real congested network is available has not yet been shown in the literature. The descriptive analyses presented in this paper focus on perception of route reliability, use of information and adaptive behavior. They are carried out by means of comparisons between GPS traces and traffic conditions in the network with travel diaries and interviews. Descriptive analysis of the data set combining the different data sources suggest that travelers' perception of the routes' characteristics is biased in favor of the preferred routes, i.e., preferred routes are usually considered to be reliable when in reality they are among the most unreliable; travelers, commuters in particular, do not tend to use information to plan better departure times but instead use it to anticipate expectations regarding traffic conditions. Besides this, habit appears to have a very strong influence on travelers' behavior and even after experiencing long delays they are willing to stick to their preferred routes.

Various decision theories have been used to explain travelers' behavior. This paper presents a comparative analysis from the points of view of theory and application of the expected utility theory, prospect theory, and regret theory. The application was based on an empirical data set on route choice behavior with and without information provision. Results show that despite the widespread use of expected utility theory to model travelers' behavior, the use of prospect theory is quite appropriate and promising, especially when information is provided. The reference point plays an important role in the prediction ability of prospect theory. The greatest prediction ability occurs when the reference point is aligned with the observed behavior and thus reinforces the necessity of establishing appropriate and meaningful values. This study empirically shows the potential of alternatives to expected utility theory to capture travelers' behavior better, as in the case of prospect theory under the proposed model specification, but this is not necessarily true, as demonstrated by the results obtained by use of regret theory.