Impacts of Metering-Based Dynamic Priority Schemes

Several works published over the last two decades have shown for a stylized set-up with homogeneous users that metering-based priority (MBP) schemes may generate Pareto improving departure time adjustments similar to those induced by congestion pricing, but without any financial transaction. We investigate whether MBP (i) still generates significant savings and (ii) remains Pareto-improving, with various sources of heterogeneity (in schedule flexibility, desired arrival time, and capacity usage). We consider two types of schemes: one where the priority status is allocated randomly (R-MBP) and another (HOV-MBP), which only prioritizes users with small capacity usage (e.g., carpoolers). We find that the relative total cost savings of R-MBP decrease with heterogeneity in flexibility, but may increase with heterogeneity in desired arrival time. It fails however to be Pareto-improving, as nonprioritized users are almost systematically worse-off. HOV-MBP circumvents this issue by generating an ordering effect and a modal shift, which both contribute to a better distribution of benefits among users. Under favorable circumstances, they may even restore a Pareto improvement. Overall, MBP appears as a realistic way to alleviate congestion, scoring well both in terms of efficiency and social acceptability.

Analysis of Bus Fare Structure to Observe Modal Shift, Operator Profit, and Land-Use Choices through Combined Unified Transport Model

In order to design sustainable urban transport systems, the inclusion of the behaviors of different stakeholders is imperative. In this study, we formulated the interactions of behaviors between transport operator, landowner, workplace, residence, route and mode choices, and location of firms and businesses through a combined unified model of land-use and transport system. The commuters have two mode choices for traveling: private car and public bus. They are inclined to choose a transit mode with minimum traveling costs. We combined two models, maximization of operator profit constrained by bus frequency, while maintaining the formulation of other stakeholders through an assignment sub-model. The resulting formulation is bi-level, which is optimally solved for a small-sized instance containing two zones. The findings suggest that if the bus fare is reduced, the demand of public bus is increased. However, the operators’ profit is optimized within a certain range of fares and is lowered when the fare is too low or too high. It is determined that maximum bus frequency does not guarantee maximum profit to the service operator. The impacts of traveling costs on residence choice behavior suggest that if link fares are more, many of people opt not to travel between different zones. The analysis results presented in this paper are calculated for two types of link fares: a fixed fare (30 currency), and a range of link fare (5 to 100 currency). Different variants of the same formulation can be applied for real settings to better comprehend the nature of the model and its applications.

Estimation of Travel Demand for Bangkok–Chiang Mai Hyperloop Using Traveler Surveys

Hyperloop, projected as fast and efficient, and envisaged as the future of high-speed transportation, does not have much published information about its demand estimation. This paper aims to estimate the willingness of air and car passengers to shift to hyperloop. A nested logit model was used to analyze stated preference data gathered from the air and car travelers along the Bangkok–Chiang Mai sector in Thailand. The variables contributing the most to the modal shift towards hyperloop are total travel cost, total travel time, monthly income, gender, education level, bearer of trip expenses, and number of trips in the last 6 months and duration of stay at the destination. The highest value of elasticity for hyperloop is obtained for the total travel cost followed by total travel time and monthly income. It is concluded that hyperloop will be the predominant mode of transportation between the Bangkok–Chiang Mai sectors with a modal share of almost 50% by the year 2025. Survey results also revealed that the preferences of the passengers in order of priorities for long distance travel are comfort, low travel cost, less travel time, safety, high frequency of travel mode and low CO2 emission. The main contribution of this paper is to provide an insight on factors that may contribute towards a possible shift in mode from car and air to hyperloop. The study will be beneficial to policy makers in developing a strategy for a more efficient mass transportation system using new and emerging technologies.

Effective measures in Sustainable urban mobility plans (SUMPs): Analysis of 10 (successful) European cities

The paper presents results of an analysis of measures implemented in various European cities that have been effective in reducing the share of trips by car and increasing the shares of active mobility and public transportation. Ten cities with a significant modal shift from cars to public transportation and/or active mobility in a period of several years were analysed. For each city, an interview was conducted with a local expert. The questions focused on the reasons for successful changes in travel habits and the existence and relevance of the SUMP in bringing about these changes. The results show that all cities analysed have some form of SUMP, and many have additional, more specific documents. Most cities have been developing these documents and implementing the measures in them for many years. Furthermore, the modal shift was always the result of a combination of several push and pull measures. Cities implemented restrictive measures for cars as well as improved conditions for alternative modes of mobility and often focused on road space transformation.

Effective measures in Sustainable urban mobility plans (SUMPs): Analysis of 10 (successful) European cities

The paper presents results of an analysis of measures implemented in various European cities that have been effective in reducing the share of trips by car and increasing the shares of active mobility and public transportation. Ten cities with a significant modal shift from cars to public transportation and/or active mobility in a period of several years were analysed. For each city, an interview was conducted with a local expert. The questions focused on the reasons for successful changes in travel habits and the existence and relevance of the SUMP in bringing about these changes. The results show that all cities analysed have some form of SUMP, and many have additional, more specific documents. Most cities have been developing these documents and implementing the measures in them for many years. Furthermore, the modal shift was always the result of a combination of several push and pull measures. Cities implemented restrictive measures for cars as well as improved conditions for alternative modes of mobility and often focused on road space transformation.

Scenarios of Automated Mobility in Austria: Implications for Future Transport Policy

Developments in the field of automated mobility will greatly change our mobility and the possibilities to get from one place to another. This paper presents different scenarios for personal mobility in Austria, anticipating the possibilities and developments in the field of automated vehicles (AVs). The scenarios were developed using a systematically formalized scenario technique and expand the social and political discourse on automated mobility, which is currently characterized by a lack of experience and visibility as an established transport service. Using system dynamics modeling techniques, i.e., the Metropolitan Activity Relocation Simulator (MARS), impacts of the scenarios on the Austrian transportation system are estimated. The simulations show that, without suitable transport policy measures, automated mobility will lead to a significant increase in the volume of individual traffic and to modal shift effects with lower traffic volumes for public transport, walking and cycling. In addition, without a link between AVs and post-fossil propulsion systems, increases in pollutant emissions can also be expected. In contrast, the simulation results of an increased use of AVs in public transport show positive effects for the support of a more sustainable mobility. Hence, transport policy measures accompanying the introduction and development of automated vehicles will be needed in the future to reach a sustainable development.

Life Cycle Assessment of Free-Floating Bike Sharing on Greenhouse Gas Emissions: A Case Study in Nanjing, China

The free-floating bike sharing (FFBS) system appears in the form of low-carbon transport mode. Life cycle assessment (LCA) is a method to analyze the environmental impact of FFBS but has rarely considered the trip chain if the intermodal transport modes were employed. This paper proposes a mathematical formalization of LCA in response to the trip chain. The environmental benefit of FFBS was analyzed by this method considering the production, use, operation, and disposal phases in Nanjing. An online survey was conducted to analyze the mechanism of modal shift influenced by FFBS. The results showed that most respondents only use FFBS in the trip, with savings of 63.726 g CO2-eq/p·km, mainly shifting from lower-emission modes (28.30% from bus, 14.86% from metro, and 33.97% from non-motorized modes), while the trip mode of connecting public transport with FFBS could better replace the motorized transport trip and generate better low-carbon benefits with savings of 300.718 g CO2-eq/p·km. One FFBS should be used for at least 227 days to generate positive environmental benefits based on the current number of FFBS and the assumption of the utilization of each bike, which is once a day on average. The research results can effectively support the environmental benefit analysis of FFBS, the subsequent planning based on the low-carbon concept, and the implementation of relevant incentive policies.

Are We Satisfying the Right Conditions for the Mobility Transition? A Review and Evaluation of the Dutch Urban Mobility Policies

Global climate agreements call for action and an integrated perspective on mobility, energy and overall consumption. Municipalities in dense, urban areas are challenged with facilitating this transition with limited space and energy resources, and with future uncertainties. One important aspect of the transition is the adoption of electric vehicles, which includes the adequate design of charging infrastructure. Another important goal is a modal shift in transportation. This study investigated over 80 urban mobility policy measures that are in the policy roadmap of two of the largest municipalities of the Netherlands. This analysis consists of an inventory of policy measures, an evaluation of their environmental effects and conceptualizations of the policy objectives and conditions within the mobility transitions. The findings reveal that the two municipalities have similarities in means, there is still little anticipation of future technology and policy conditions could be further satisfied by introducing tailored measures for specific user groups.

Where are the low-hanging fruits? Strategic mapping of potential consumers of shared e-mobility to help decarbonise mobility of our cities.

In marketing research, the concept of ‘low-hanging fruits’ refers to those consumers who are easiest to attract to a business. Focusing efforts on this group maximizes the effectiveness of a marketing campaign. In mobility planning, this concept could be adopted by city planners more often to achieve sustainability goals.Imagine that a start-up just launched a new model of shared e-scooter in a busy town like Rotterdam. It is natural to expect that, for the sake of financial sustainability, a significant part of the revenue should come from neighbourhoods that cluster factors of success for potential usage (e.g. commercial activities, jobs, good infrastructure). However, if shared e-mobility is meant to cause significant and positive impact on sustainability, helping cities achieve their goals, further structural changes in travel habits are certainly necessary. In short, part of the ‘unnecessary’ car trips should be more often replaced by more sustainable modes, like shared e-mobility. ‘Unnecessary’ is interpreted in this study as a car trip that has a similar profile (e.g. length, travel time, socioeconomics) of a shared e-mobility trip, and therefore could be ‘avoided’ or ‘replaced’ by more sustainable alternatives. The individuals making those trips are called ‘low-hanging fruits’, but are ‘not yet consuming the product’. How to map low-hanging fruits? In this study, an approach is proposed to help providers and cities strategically map them. The approach is operationalised in the context of the Netherlands, a country where shared e-mobility is spreading quickly. The approach can be divided in 3 major phases: 1) Characterising a typical ‘avoidable’ car trip in the context of a given population (city, region, country), through the investigation of how current users of shared mobility travel (e.g. trip distance, duration) and their characteristics (e.g. age, gender, income); 2) Mapping where the avoidable car trips are generated, since countries like the Netherlands keep their Household Travel Surveys up to date so that city planners can use that information to extract insights of travel habits (desire lines, purpose, mode, etc); 3) Labelling locations in regard to their likelihood of having more or less low-hanging fruits, through the application of unsupervised learning (k-means) to find probable clusters of low-hanging fruits. In order to achieve (1), we used an anonymous, ‘privately acquired’ shared mobility OD travel matrix produced in 2020 by a third party mobility company. This OD refers to trips done by e-scooter users of Rotterdam during the summer of 2020. For (2), we explored the latest Dutch Household Travel Survey (2020) and combined it with (1). This type of survey provided annual information about daily travel patterns of more than 60.000 people. The Dutch HTS can also be expanded to mitigate negative impacts of data collection biases and be a reasonable representation of how the whole population travels on a daily basis. In (3), we combined insights extracted from (2) with Census information to perform the unsupervised classification of locations. We propose and operationalise a pragmatic approach to help cities and mobility providers identify potential users of shared mobility. If shared mobility could seduce more low-hanging fruits, significant environmental impacts from modal shift could be achieved. Some use cases of this exercise can be applied to:(i) size potential market for expansions (e.g. deployment of vehicles or installation of facilities); (ii) size potential impacts of modal shift on city-wide Co2 emissions; (iii) design subsidies that encourage providers to deploy assets in certain areas; (iv) change fees depending on the potential to attract former private vehicle users; (v) investigate reasons behind the existence of avoidable car trips.