Transportation for an Aging Population: Promoting Mobility and Equity for Low-Income Seniors

This study explores the travel patterns, needs, and mobility problems faced by diverse low-income, inner-city older adults in Los Angeles in order to identify solutions to their mobility challenges. The study draws information from: (1) a systematic literature review of the travel patterns of older adults; (2) a review of municipal policies and services geared toward older adult mobility in six cities; (3) a quantitative analysis of the mobility patterns of older adults in California using the California Household Travel Survey; and (4) empirical work with 81 older adults residing in and around Los Angeles’ inner-city Westlake neighborhood, who participated in focus groups, interviews, and walkabouts around their neighborhood

Chapter 13 - Sharing strategies: carsharing, shared micromobility (bikesharing and scooter sharing), transportation network companies, microtransit, and other innovative mobility modes

Shared mobility—the shared use of a vehicle, bicycle, or other mode—is an innovative transportation strategy that enables users to gain short-term access to transportation modes on an “as-needed” basis. It includes various forms of carsharing, bikesharing, scooter sharing, ridesharing (carpooling and vanpooling), transportation network companies (TNCs), and microtransit. Included in this ecosystem are smartphone “apps” that aggregate and optimize these mobility options, as well as “courier network services” that provide last mile package and food delivery. This chapter describes different models that have emerged in shared mobility and reviews research that has quantified the environmental, social, and transportation-related impacts of these services

Using mobility information to perform a feasibility study and the evaluation of spatio-temporal energy demanded by an electric taxi fleet

Half of the global population already lives in urban areas, facing to the problem of air pollution mainly caused by the transportation system. The recently worsening of urban air quality has a direct impact on the human health. Replacing today’s internal combustion engine vehicles with electric ones in public fleets could provide a deep impact on the air quality in the cities. In this paper, real mobility information is used as decision support for the taxi fleet manager to promote the adoption of electric taxi cabs in the city of San Francisco, USA. Firstly, mobility characteristics and energy requirements of a single taxi are analyzed. Then, the results are generalized to all vehicles from the taxi fleet. An electrificability rate of the taxi fleet is generated, providing information about the number of current trips that could be performed by electric taxis without modifying the current driver mobility patterns. The analysis results reveal that 75.2% of the current taxis could be replaced by electric vehicles, considering a current standard battery capacity (24–30 kWh). This value can increase significantly (to 100%), taking into account the evolution of the price and capacity of the batteries installed in the last models of electric vehicles that are coming to the market. The economic analysis shows that the purchasing costs of an electric taxi are bigger than conventional one. However, fuel, maintenance and repair costs are much lower. Using the expected energy consumption information evaluated in this study, the total spatio-temporal demand of electric energy required to recharge the electric fleet is also calculated, allowing identifying optimal location of charging infrastructure based on realistic routing patterns. This information could also be used by the distribution system operator to identify possible reinforcement actions in the electric grid in order to promote introducing electric vehicles

Measuring Motorists’ Choice Behaviour and Responses to Long-Term Changes in Transport Conditions.

This paper reports on the Gnding from an in-depth survey into the choice of travel mode by a small group of respondents in Nottingham. The purpose of this study was to identify the range of factors which affect current choice of travel mode and to develop a survey method which lead to better observation and predictions of future travel choice decisions under worsening conditions for car travel or improving conditions for public transport. The first section of the paper describes the background to the project. Section 2 describes the rationale and features of the survey method used in the study. Section 3 outlines the survey design. Section 4 discusses the findings from the survey and discusses the policy relevance of the findings. Section 5 discusses the implications of the work for the design of larger stated preference and revealed preference surveys

Generalized Costs of Travel by Solo and Pooled Ridesourcing vs. Privately Owned Vehicles, and Policy Implications

The emergence of “3 Revolutions” in transportation (automation, electrification and shared mobility) presents a range of questions regarding how consumers will travel in the future, and under what conditions there may be rapid adoption of various services. These include individual on-demand taxi-style services, shared mobility in pooled services, and use of public transit, all with or without drivers. There is now enough data and estimates on the costs of these service combinations, and in some cases ridership data, to consider how consumers are making choices and could do so in the future as things evolve. This project involved: (a) reviewing existing literature and data on consumer mode and vehicle choice; (b) developing new “generalized cost” estimates that combine monetary and non-monetary (e.g., hedonic) components of travel choice, notably incorporating value of time; and (c) conducting a comparison of monetary and generalized trip cost for a range of trip types across travel options in the near term (2020) and longer term (2030-35). Three main travel options were considered: privately owned vehicles, ridesourced solo trips, and ridesourced pooled trips. Consideration of internal combustion vs. battery electric and, in the longer term, automated technology was also core to the analysis. The trips considered include urban and suburban types in the San Francisco metro area, using actual trip characteristics. The results suggest that in the near-term, solo ridesourcing is likely to be perceived as significantly more expensive (in terms of monetary and time costs) than pooled ridesourcing or solo private vehicle trips except for those with a very high value of time. Solo ridesourcing does better in dense, slow, urban trips than in faster suburban trips. In the longer term, with automated driverless vehicles, solo ridesourcing could become the cheapest mode for many travelers in a range of situations. This report includes an initial consideration of the implications of these policies for affecting travel choices, presumably to push choices toward pooled ridesourcing as a sustainable option. VMT-based pricing, pricing that could be adjusted with vehicle occupancy, and parking-related approaches are described. A large price signal might be needed to shift travel, given some of the differences in generalized cost found in this analysis

Getting Around When You’re Just Getting By: The Travel Behavior and Transportation Expenditures of Low-Income Adults, MTI Report 10-02

How much do people with limited resources pay for cars, public transit, and other means of travel? How does their transportation behavior change during periods of falling employment and rising fuel prices? This research uses in-depth interviews with 73 adults to examine how rising transportation costs impact low-income families. The interviews examine four general areas of interest: travel behavior and transportation spending patterns; the costs and benefits of alternative modes of travel; cost management strategies; and opinions about the effect of changing transportation prices on travel behavior. Key findings include: Most low-income household are concerned about their transportation costs. Low-income individuals actively and strategically manage their household resources in order to survive on very limited means and to respond to changes in income or transportation costs. In making mode-choice decisions, low-income travelers—like higher-income travelers—carefully evaluate the costs of travel (time and out-of-pocket expenses) against the benefits of each of the modes. Some low-income individuals in our sample were willing to endure higher transportation expenditures—such as the costs of auto ownership or congestion tolls—if they believed that they currently benefit or would potentially benefit from these increased expenses. Although low-income households find ways to cover their transportation expenditures, many of these strategies had negative effects on households. The report concludes with recommendations on how to increase transportation affordability, minimize the impact that new transportation taxes or fees have on low-income people, and develop new research and data collection to support the previous two efforts

Social Equity Impacts of Congestion Management Strategies

This white paper examines the social equity impacts of various congestion management strategies. The paper includes a comprehensive list of 30 congestion management strategies and a discussion of equity implications related to each strategy. The authors analyze existing literature and incorporate findings from 12 expert interviews from academic, non-governmental organization (NGO), public, and private sector respondents to strengthen results and fill gaps in understanding. The literature review applies the Spatial – Temporal – Economic – Physiological – Social (STEPS) Equity Framework (Shaheen et al., 2017) to identify impacts and classify whether social equity barriers are reduced, exacerbated, or both by a particular congestion mitigation measure. The congestion management strategies discussed are grouped into six main categories, including: 1) pricing, 2) parking and curb policies, 3) operational strategies, 4) infrastructure changes, 5) transportation services and strategies, and 6) conventional taxation. The findings show that the social equity impacts of certain congestion management strategies are not well understood, at present, and further empirical research is needed. Congestion mitigation measures have the potential to affect travel costs, commute times, housing, and accessibility in ways that are distinctly positive or negative for different populations. For these reasons, social equity implications of congestion management strategies should be understood and mitigated for in planning and implementation of these strategies