Editorial: A better tomorrow: towards human-oriented, sustainable transportation systems

In a rapidly changing world, transportation is a big determinant of quality of life, financial growth and progress. New challenges (such as the emergence of the COVID-19 pandemic) and opportunities (such as the three revolutions of shared, electric and automated mobility) are expected to drastically change the future mobility landscape. Researchers, policy makers and practitioners are working hard to prepare for and shape the future of mobility that will maximize benefits. Adopting a human perspective as a guiding principle in this endeavor is expected to help prioritize the “right” needs as requirements. In this special issue, eight research papers outline ways in which transportation research can contribute to a better tomorrow. In this editorial, we position the research within the state-of-the-art, identify the needs for future research, and then outline how the included contributions fit in this puzzle. Naturally, the problem of sustainable future transportation systems is way too complicated to be covered with a single special issue. We thus conclude this editorial with a discussion about open questions and future research topics

Embedding risk attitudes in a scheduling model: Application to the study of commuting departure time

Traditionally, the value of travel time savings (VTTS) and the value of reliability (or reduced variability) are estimated within a linear utility functional form, which assumes risk-neutral attitudes for decision makers. In this paper, we develop non-linear scheduling models to address both risk attitude and preference in the context of a stated choice experiment of car commuters facing risky choices where the risk is associated with the trip time. We also investigate unobserved between-individual heterogeneity in time-related parameters and risk attitudes using a mixed multinomial logit (MMNL) model. More importantly, we calculate the willingness to pay values for reducing the mean travel time and variability (earlier/later than the preferred arrival time) within the non-linear scheduling framework. This model is then used to estimate preferred departure times for commuters, assuming that random link capacities are the source of travel time variability. Results show that the more variable travel times are, the earlier commuters depart, and that the non-linear scheduling model predicts earlier optimal departure times than the traditional linear scheduling model. Some important issues related to modelling non-linearity are also discussed

The sustainability of shared mobility: Can a platform for shared rides reduce motorized traffic in cities?

Studies in several cities indicate that ridesourcing (ride-hailing) may increase traffic and congestion, given the substitution of more sustainable modes and the addition of empty kilometers. On the other hand, there is little evidence if smartphone apps that target shared rides have any influence on reducing traffic levels. We study the effects of a shared-mobility service offered by a start-up in Mexico City, Jetty, which is used by travelers to book a shared ride in a car, van or bus. A large-scale user survey was conducted to study trip characteristics, reasons for using the platform and the general travel choices of Jetty users. We calculate travel distance per trip leg, for the current choices and for the modes that riders would have chosen if the platform was not available. We find that the effect of the platform on vehicle kilometers traveled (VKT) depends on the rate of empty kilometers introduced by the fleet of vehicles, the substitution of public versus private transport modes, the occupancy rate of Jetty vehicles and assumptions on the occupancy rate of substituted modes. Following a sensitivity analysis approach for variables with unavailable data, we estimate that shared rides in cars increase VKT (in the range of 7 to 10 km/passenger), shared vans are able to decrease VKT (around −0.2 to −1.1 km/passenger), whereas buses are estimated to increase VKT (0.4 to 1.1 km/passenger), in our preferred scenarios. These results stem from the tradeoff between the effects of the occupancy rates per vehicle (larger vehicles are shared by more people) and the attractiveness of the service for car users (shared vans attract more car drivers than buses booked through Jetty). Our findings point to the relevance of shared rides in bigger vehicles such as vans as competitors to low occupancy car services for the future of mobility in cities, and to the improvement of public transportation services through the inclusion of quality attributes as provided by new shared-mobility services

Estimation of crowding discomfort in public transport: results from Santiago de Chile

The relationship between train occupancy, comfort and perceived security is analysed, using data from a survey and stated choice (SC) study of users of Santiago's Metro (subway) system. Mode choice models where crowding is one of the main explanatory variables are estimated and crowding multipliers to measure its relevance on travel time disutility for sitting and standing are computed. An international comparison with previous studies from London, Paris, Singapore and Sweden is presented. The type of estimated models include Multinomial Logit, Mixed Logit, and Latent Class models. Results show that there is significant heterogeneity in crowding perception across the population. Users classes with low and high crowding multipliers are identified, in which gender, age and income play a role. In the SC survey, occupancy levels were shown with three alternative forms of representation (text, 2D diagram or photo), however we did not find relevant influences of the different forms of representation on crowding perception

Multimodal pricing and optimal design of urban public transport: the interplay between traffic congestion and bus crowding

The interplay between congestion and crowding externalities in the design of urban bus systems is identified and analysed. A multimodal social welfare maximisation model with spatially disaggregated demand is developed, in which users choose between travelling by bus, car or walking in a transport corridor. Optimisation variables are bus fare, congestion toll, bus frequency, bus size, fare collection system, bus boarding policy and the number of seats inside buses. We find that optimal bus frequency results from a trade‐off between the level of congestion inside buses, i.e., passengers’ crowding, and the level of congestion outside buses, i.e., the effect of frequency on slowing down both buses and cars in mixed‐traffic roads. A numerical application shows that optimal frequency is quite sensitive to the assumptions on crowding costs, impact of buses on traffic congestion, and overall congestion level. If crowding matters to users, buses should have as many seats as possible, up to a minimum area that must be left free of seats. If for any other reason planners decide to have buses with fewer seats than optimal (e.g., to increase bus capacity), frequency should be increased to compensate for the discomfort imposed on public transport users. Finally, the consideration of crowding externalities (on both seating and standing) imposes a sizeable increase in the optimal bus fare, and consequently, a reduction of the optimal bus subsidy.Australian Research Council Discovery Progra

A review of public transport economics

Public transport provision requires substantial organisational efforts, careful planning, financial contributions from the public, and coordination between millions of passengers and staff members in large systems. Efficient resource allocation is critical in its daily operations. Therefore, public transport has been among the most popular subjects in transport economics since the infancy of this discipline. This paper presents an overview of the literature developed over the past half century, including more than 300 important contributions. With a strong methodological orientation, it collects, classifies, and compares the frequently used analytical modelling techniques, thus providing a cookbook for future research and learning efforts. We discuss key findings on optimal capacity provision, pricing, cost recovery and subsidies, externalities, private operations, public service regulation, and cross-cutting subjects, such as interlinks with urban economics, political economy, and emerging mobility technologies