Travelers interact with a large number and variety of products and services during their journeys. The quality of a travel experience depends on a whole urban mobility system considered in space and time. This paper outlines the relevant concepts to be considered in designing urban mobility. The goal is to provide a language and insights for the early stages of a design process. A literature review sheds light on the complexity of urban mobility from technical, sociotechnical, and user experience perspectives. Observations of experiences in urban areas provide data for describing and understanding travel experience patterns and issues. The paper proposes a conceptual model to describe and analyze different facets of traveler experience and categorizes problems that travelers face when they interact with an urban mobility system. A case study is reported illustrating the use of the conceptual model in identifying travel problems for a demand-responsive transport service.

Information is at the heart of the smooth running of a public transport network and the satisfaction of its users, particularly in disrupted situations. Information is a central element for users to continue to use this mode contributing to sustainable mobility and even attracting new users. Therefore, it is essential to understand how travellers use passenger information to adjust the way it is disseminated to actual usage. This article aims to identify the sources of information used by travellers and at what moments they consult them in order to categorise passengers according to these activities. We conducted an online questionnaire on 258 regular suburban train users of a specific branch of one particular line (with the same information material in the stations). In addition to univariate descriptive analyses, the results were analysed using Multiple Correspondence Analysis and Ascending Hierarchical Clustering to construct six information-seeking profiles named: Improvisers, Monitors, Planners, Circumscribed, Ultra-connected and Routinized. Based on clustering, we were able to link sociodemographic or travel characteristics to information-seeking behaviour. Differences in information acquisition and use were identified. These results suggest great information-seeking behaviour disparities and can provide interesting information to passenger transport stakeholders. The results could be further integrated into a multi-agent simulation.

Massive data are surrounding us in our daily lives. Urban mobility generates a very high number of complex data reflecting the mobility of people, vehicles and objects. Transport operators are primary users who strive to discover the meaning of phenomena behind traffic data, aiming at regulation and transport planning. This paper tackles the question "How to design a supportive tool for visual exploration of digital mobility data to help a transport analyst in decision making?” The objective is to support an analyst to conduct an ex post analysis of train circulation and passenger flows, notably in disrupted situations. We propose a problem-solution process combined with data visualisation. It relies on the observation of operational agents, creativity sessions and the development of user scenarios. The process is illustrated for a case study on one of the commuter line of the Paris metropolitan area. Results encompass three different layers and multiple interlinked views to explore spatial patterns, spatio-temporal clusters and passenger flows. We join several transport network indicators whether are measured, forecasted, or estimated. A user scenario is developed to investigate disrupted situations in public transport.