The last decade has witnessed very active development in two broad, but separate fields, both involving understanding and modeling of how individuals move in time and space (hereafter called “travel behavior analysis” or “human mobility analysis”). One field comprises transportation researchers who have been working in the field for decades and the other involves new comers from a wide range of disciplines, but primarily computer scientists and physicists. Researchers in these two fields work with different datasets, apply different methodologies, and answer different but overlapping questions. It is our view that there is much, hidden synergy between the two fields that needs to be brought out. It is thus the purpose of this paper to introduce datasets, concepts, knowledge and methods used in these two fields, and most importantly raise cross-discipline ideas for conversations and collaborations between the two. It is our hope that this paper will stimulate many future cross-cutting studies that involve researchers from both fields.

Battery electric vehicles (BEVs) have been slow to diffuse on the international as well as the Swedish market. Previous studies have indicated situational factors such as economic factors, size and performance to be of major importance for vehicle purchasers in their choice of vehicle. In this paper, the authors explore a consumer centric total cost of ownership (TCO) model to investigate the possible discrepancy between purchase price and the TCO between internal combustion engine vehicles (ICEVs), hybrid electric vehicles (HEVs) and BEVs. The creation and testing of the TCO model reveals that computation could be a challenging task for consumers due to bounded access of relevant data and the prediction of future conditions. The application of the model to the vehicle sample found that BEVs could be cheaper compared to ICEVs and HEVs. The findings in this paper could prove to be of importance for policy and marketing alike in designing the most appropriate business models and information campaigns based on consumer conditions in order to further promoting the diffusion of BEVs in society

The subsidy level of public transport systems varies considerably among systems worldwide. While limited-scale free-fare public transport (FFPT) services such as limited campaigns and fare evasion for special groups or specific services are prevalent, there is only limited evidence on the consequences of introducing a full-fledged FFPT. The case of Tallinn, Estonia offers a full-scale experiment that provides a unique opportunity to investigate the impacts of FFPT. This study examines travel pattern changes based on individual travel habit survey shortly before and almost 1 year after the introduction of FFPT policy in Tallinn based on interviews and travel diaries of a random sample of 1500 household. We analyse modal shift effects and whether they are driven by trip generation or trip substitution, travel attitudes and satisfactions as well as impacts on equity, employment prospects, and trip destination choices. Almost a year after the introduction of FFPT, public transport usage increased by 14 % and there is evidence that the mobility of low-income residents has improved. The effect of FFPT on ridership is substantially lower than those reported in previous studies due to the good level of service provision, high public transport usage and low public transport fees that existed already prior to the FFPT.