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In recent years, sustainable mobility policy analysis has used Hybrid Choice Models (HCM) by incorporating latent variables in the mode choice models. However, the impact on policy analysis outcomes has not yet been determined with certainty. This paper aims to measure the effect of HCM on sustainable mobility policy analysis compared to traditional models without latent variables. To this end, we performed mode choice research in the city of Santander, Spain. We identified two latent variables—Safety and Comfort—and incorporated them as explanatory variables in the HCM. Later, we conducted a sensitivity study for sustainable mobility policy analysis by simulating different policy scenarios. We found that the HCM amplified the impact of sustainable mobility policies on the modal shares, and provided an excessive reaction in the individuals’ travel behavior. Thus, the HCM overrated the impact of sustainable mobility policies on the modal switch. Likewise, for all of the mode choice models, policies that promoted public transportation were more effective in increasing bus modal shares than those that penalized private vehicles. In short, we concluded that sustainable mobility policy analysis should use HCM prudently, and should not set them as the best models beforehand.

In this work, the management of a high circulation road connecting two mainstream cities in Chile is tackled. The cities are connected through a coastal road and is permanently under congestion effects. This situation leads to much discontent in the users and negatively impacts both economically and environmentally as well. This problem setting arises in many other countries and is subject of a relevant body of research. To minimize the impact of congestion in this problem setting, a micro-simulation is performed in VISSIM. This model, incorporates the road and its users and represents their driving behavior and its impact on congestion. Throughout the experiments conducted, the emissions of CO2 are calculated; this allowed to define a set of congestion minimization strategies that also reduce emissions. These strategies were validated under a set of real-world scenarios and were able to solve a set of specific road management problems and optimize average travel time for users. The model, the strategies and a case study are introduced and discussed, also, future research directions are given.

The objective is to study the distribution of passengers inside urban trains for different levels of crowding. The study is carried out through the observation of videos made by laboratory experiments in which a mock-up of a carriage represented the boarding and alighting process. The Fruin’s Level of Service (LOS) was adopted, but with a different approach, in which the train is divided into five zones (central hall, central aisle, side aisle, central seats and side seats). The experiments are based on the behavior of passengers in the London Underground; however, this study could be expanded to any conventional rail or LRT system. For the laboratory experiments, it is proposed to build a metro carriage and a corresponding platform section, and the scenarios will include different levels of crowding of passengers boarding and alighting to produce a variation in the density on the platform. According to the crowding level, the results allow obtaining the distribution and movements generated by passengers in the five zones for different instants of time during the process of boarding and alighting. It is observed that passengers are distributed according to safety and efficiency conditions. For example, passengers tried to avoid contact with each other unless it is inevitable. In relation to comfort, the seats of the carriage are always used even if there is a low level of crowding. If the crowding level increases, the boarding and alighting time go up. In addition, passengers will spend one or two seconds more if the “let’s get off before getting on the carriage” behavior is breached. This kind of experiment can be used in further research as a way to test “what-if” scenarios using this new method of discretization of the space inside the train, which cannot be tested in existing stations due to restrictions such as the weather, variability of the train frequency, current design of the trains, among others. New experiments are necessary for future research to include other types of passengers such as people with disabilities or reduced mobility.