Trade Uber for the Bus?

Abstract

Problem, research strategy, and findings: Few studies have examined ride-hail users’ individual preferences between ride-hail and transit. Based on a survey of ride-hail users in the Philadelphia (PA) region, I examine who uses ride-hail and investigate ride-hail users’ willingness to use ride-hail versus transit. My results suggest that more than one-quarter of respondents replaced transit with ride-hail in their last ride-hail trips. Mixed logit regression analysis based on stated preference choice experiments indicate that higher-income respondents and respondents over 30?years old are increasingly willing to choose ride-hail over transit, even though their actual ride-hail usage is lower than that among lower-income and younger respondents. Results also show that female respondents are more willing to choose ride-hail over transit than male respondents and less frequent transit users are more likely to choose ride-hail than frequent transit users. Higher cost and longer trip duration are significant deterrents for travel by either mode. Respondents consider the time spent on walking to and from transit more burdensome than in-vehicle travel time and wait time for transit and ride-hail. They consider waiting for ride-hail less burdensome than waiting for transit. Survey sampling and design limitations provide lessons for future ride-hail studies.

Takeaway for practice: Practitioners should ensure convenient, affordable travel options for lower-income residents, who are more frequent but less willing ride-hail users than higher-income residents. Female respondents’ safety concerns about transit should urge transit agencies to recognize female transit riders’ travel needs. The relationship between age and willingness to use ride-hail reminds planners to anticipate greater substitution of ride-hail for transit as the more tech-savvy generation starts entering their 30s. Last, fare reduction alone may not be enough to prompt ride-hail users to switch to transit. Service improvements that shorten the overall trip duration are imperative to make transit more attractive.     

Polycentrism as a sustainable development strategy: empirical analysis from the state of Maryland

We present in this paper an analysis of economic centers and their role in shaping employment development patterns and travel behavior in the state of Maryland. We begin by identifying 23 economic centers in the Baltimore-Washington region. We then examine these centers first in their role as centers of economic activity and then in their role as nodes in the state’s transportation system. Finally, we identify the commute sheds of each center, for multiple modes of travel and travel times, and examine jobs–housing balance within these various commute sheds. We find that Maryland’s economic centers not only promote agglomerative economies and thus facilitate economic growth; they also generate a disproportionate number of trips and promote transit ridership. These results provide empirical support for policies that promote polycentric urban development, and especially policies that promote polycentric employment development. Further, they suggest that polycentrism as a sustainable development strategy requires careful coordination of regional transportation systems designed to balance jobs and housing within a center’s transit commute shed. Based on these findings we recommend that the Maryland state development plan, and regional sustainable communities plans across the nation, encourage the concentration of employment within economic centers and encourage housing development within the transit commute sheds of those centers.     

Alternative Approaches to Modeling the Travel-Demand Impacts of Smart Growth

Four-step travel demand forecasting models were never meant to estimate the travel impacts of neighborhood-level smart growth initiatives like transit villages, but rather to guide regional highway and transit investments. While progress has been made in enhancing large-scale models, some analysts have turned to post-processing and direct models to reduce modeling time and cost, and to better capture the travel impacts of neighborhood-scale land use strategies. This paper presents examples of direct or off-line modeling of rail and transit-oriented land use proposals for greater Charlotte, the San Francisco Bay Area exurbs, and south St. Louis County. These alternative approaches provided a useful platform for scenario testing, and their results revealed that concentrating development near rail stations produced an appreciable ridership bonus. These alternative models are appropriate as sketch-planning supplements to, not substitutes for, traditional four-step models.     

Moving from Public Housing to Homeownership: Perceived Barriers to Program Participation and Success

Abstract: The goals of public housing have evolved from providing shelter to providing opportunities for escaping from welfare and buying one's own home. Despite numerous federal policies aimed at enhancing resident self‐sufficiency and homeownership through programs run by local public housing authorities, little is known about who participates and who succeeds. This study explores barriers to participation and success in an innovative resident self‐sufficiency/homeownership program developed by the Housing Authority of the city and county of Denver. We conduct surveys of participants in the Foundations for Homeownership program, eliciting their perceptions regarding willingness and ability to participate in the program and, thereafter, completing it successfully. We find that at time of entry into the program, participants reported, on average, 4.6 major barriers that they perceive would limit their ability to achieve current goals. OLS and logistic regression analyses were conducted to ascertain the degree to which perceived barriers were associated with participants’ demographic, economic, or attitudinal characteristics.     

Exploring the catchment area of an urban railway station by using transit card data: Case study in Seoul

To enhance transit ridership, Seoul introduced a transfer discount fare scheme that uses an automated fare collection system in Seoul 2004. The transfer discount fare system records all transfer information between rail and buses in transit smartcard data, which enabled us to explore an urban railway station's catchment area. In this study, we examined the geographic distribution of rail-to-bus transfer trips and their characteristics by using transit smartcard data. Mokdong station in Seoul was used as a case study to demonstrate the benefits of data mining for the depiction and easy evaluation of a station's catchment area. The results showed that the average transfer passenger traveled 1.7 km with five bus stops after boarding to access the business district during the morning peak hour. The cumulative distribution of alighting passengers by bus route helped with inferring the shape and size of the urban railway station's catchment area in each direction and depending on the time of day. We found that reliable transfer travel data constitute valuable information for evaluating an urban railway station's catchment area with respect to the type of land use and will help transit agencies with providing better transit services in terms of enhanced accessibility by changing bus headways and routes, as well as land use planners with evaluating transit-oriented development based on the expanded concept of a metro station's catchment area.     

Measuring Transportation Characteristics of the Disabled: Louisville,Kentucky

ABSTRACT: The transportation authority serving Louisville and Jefferson County, Kentucky purchased a set of lift-equipped buses to be placed in service in January 1988 and needed to know on which routes to place them. Soon afterward, they would need to make a decision whether to purchase additional lift-equipped buses. More generally, they wanted to know how best to plan for the needs of people with disabilities. A single general population survey that could provide all the information needed would have been too costly. An alternative method, using three stages of data collection, was selected: a survey of agencies and organizations serving people with disabilities, a canvass of people identified by these organizations, and telephone interviews with a subset of canvass respondents. This article reports on information collected through the canvass. Simultaneous to public media coverage of the study, canvass questionnaires were mailed to the members or clients of local organizations and agencies made up of or serving people with disabilities. A follow-up telephone interview was completed with a sample of those who did not return the canvass questionnaires. It was estimated that 5.5% of the Jefferson County, Kentucky population have disabilities, and that one-half of these people are under 65 years of age. As many as one-fourth of them may require lift access to use a public bus. The findings showed that most people with disabilities are driven by a relative or a friend when they need to travel; the second most common means of transportation for them is driving their own cars. Fixed-route bus users are younger than users of other types of transportation. They have fewer limitations overall, but are more likely to have communication or learning limitations than are disabled people driving their own cars. About half of the respondents had problems getting places; reaching places that provide health care was highest on the problem list. Although, half said they would use the bus if it were more easily accessible, current users were more likely to use the bus if it were better accessible in terms of schedule, route, or vehicle. Subsequent experiences of the transportation authority and other information suggest the canvass procedure produced reasonably reliable information.     

Reliability‐Based Transit Assignment for Congested Stochastic Transit Networks

Abstract: This article proposes a nonlinear complementarity problem (NCP) formulation for the risk‐aversive stochastic transit assignment problem in which in‐vehicle travel time, waiting time, capacity, and the effect of congestion are considered as stochastic variables simultaneously and both their means and variances are incorporated into the formulation. A new congestion model is developed and captured in the proposed NCP formulation to account for different effects of on‐board passengers and passengers waiting at stops. A reliability‐based user equilibrium condition is also defined based on the proposed generalized concept of travel time budget referred to as effective travel cost, and is captured in the formulation. A column generation based algorithm is proposed to solve the NCP formulation. A survey was conducted to validate that the degree of risk aversion of transit passengers affects their route choices. Numerical studies were performed to demonstrate the problem and the effectiveness of the proposed algorithm. The results obtained show that underestimating the congestion effect and ignoring the risk aversion behavior can overestimate the patronage of transit service, which have profound implications on the profit of the operators involved and the development of transit network design models.     

Spatial mismatch and the affordability of public transport for the poor in Singapore’s new towns

Singapore has redeveloped its Central Area into business districts and relocated the affected population to new towns. Unfortunately, this strong center policy has hindered the development of employment sub-centers. Most jobs are located in the Central Area, resulting in a spatial mismatch that the government is attempting to address by building a world-class public transport system. However, the poor not only face affordability problems and long travel times for employment, but they are also experiencing a shrinking supply of employment due to economic restructuring. Route tests were conducted, and the results indicate that the poor, who generally choose to travel by bus, have to spend up to 9.8% of their household income per month and 70 min per trip from their neighborhoods to the city center. Those who take the hub-and-spoke network have to spend 13.2% of household income and take 60 min for similar trips. To increase the job-seeking range of these people, they should be offered concessions to encourage use of the hub-and-spoke network. The government should also build a light-rail transit line to pass through the Central Catchment Nature Reserve to connect employment sub-centers.     

基于Android的景区景点路线推荐服务研究

移动空间信息服务是移动网络、互联网、空间信息服务、移动终端技术协同发展的产物,是一种基于位置的空间信息服务。本文从移动空间信息服务关键技术探讨基于路线推荐服务的研究方法,设计并编程实现了一个基于特定景区景点的满足用户时间需求的旅游路线推荐服务软件。该软件基于Android平台,使用了SQLite数据库等多种技术,实现了基于用户所在景点的景区概况介绍、景区风景欣赏以及根据用户现有时间推荐最优旅游路线和到达出口的最优旅游路线推荐服务等功能。     

Book Reviews

Problem, research strategy, and findings: We evaluate the role of transportation in improving the employment outcomes of participants in the Moving to Opportunity (MTO) for Fair Housing Voucher Program, a 10-year demonstration project designed to enable low-income families to improve their outcomes by moving out of high-poverty neighborhoods. We use longitudinal data from the MTO program to assess the role of transportation—automobiles and improved access to public transit—in moving to, and maintaining, employment. We use multi-nomial logistic regression to predict changes in employment status as a function of change in automobile availability and transit accessibility, controlling for other potential determinants of employment. We find that keeping or gaining access to an automobile is positively related to the likelihood of employment. Improved access to public transit is positively associated with maintaining employment, but not with job gains. Although we cannot say for certain whether car ownership preceded or followed employment, it is clear that having a car provides multiple benefits that facilitate getting and keeping a job.

Takeaway for practice: Policies to increase automobile access among low-income households—even in dense urban areas—will most clearly enhance job gain and job retention. While auto programs are unpopular with many planners, they would improve the lives of low-income families who currently have the least access to cars. In addition, supporting moves to transit-rich neighborhoods may help households maintain consistent employment.     

Are multimodal travelers more satisfied with their lives? A study of accessibility and wellbeing in the Denver,Colorado metropolitan area

In this study, we ask how the ability to use multiple transportation options affects one's subjective wellbeing (SWB), including aspects such as physical health, financial security, standard of living, and personal relationships. A clearer understanding of these associations can inform investments in multimodal infrastructure. We draw on 232 surveys from a diverse set of residents in the Denver, Colorado metropolitan area and find that having more transportation choices can improve standard of living for low- and middle-income residents. Multimodal middle-income residents are also more satisfied with their health and what they are achieving in life. Vehicle owners report higher levels of satisfaction with their standard of living, health, and achievements, compared to non-owners, unless auto is their only travel mode. Only low-income respondents had significant differences in standard of living by where they lived, with greatest satisfaction in the urban core. These results confirm the relationship between public transit and SWB, and contribute to our understanding of how the concept of motility (social and spatial mobility) shapes one's quality of life. The findings have implications for investments in transportation modes across neighborhood types and populations, so that people have a range of travel options to meet their needs and increase their satisfaction with their goals through improved daily travel.     

A Bayesian mixture model for short-term average link travel time estimation using large-scale limited information trip-based data

Accurate estimation and prediction of urban link travel times are important for urban traffic operations and management. This paper develops a Bayesian mixture model to estimate short-term average urban link travel times using large-scale trip-based data with partial information. Unlike typical GPS trajectory data, trip-based data from taxies or other sources provide limited trip level information, which only contains the trip origin and destination locations, trip travel times and distances, etc. The focus of this study is to develop a robust probabilistic short-term average link travel time estimation model and demonstrate the feasibility of estimating network conditions using large-scale trip level information. In the model, the path taken by each trip is considered as latent and modeled using a multinomial logit distribution. The observed trip data given the possible path set and the mean and variance of the average link travel times can thus be characterized using a finite mixture distribution. A transition model is also introduced to serve as an informative prior that captures the temporal and spatial dependencies of link travel times. A solution approach based on the expectation–maximization (EM) algorithm is proposed to solve the problem. The model is tested on estimating the mean and variance of the average link travel times for 30 min time intervals using a large-scale taxi trip dataset from New York City. More robust estimation results are obtained owing to the adoption of the Bayesian framework.     

Toward a Richer Picture of the Mobility Needs of Older Americans

Problem, research strategy, and findings: People older than 65 are the most rapidly growing segment of the U.S. population, yet our cities and transportation systems are not age friendly. Low-income, minority, older adults residing in inner-city neighborhoods are largely transit dependent, rely significantly on walking for transportation, and thus have particular mobility needs. We used a mixed-methods approach that drew information from the California Household Travel Survey but also from direct interaction (through focus groups, interviews, and neighborhood walking audits) with 81 low-income, inner city–living older adults to understand their travel patterns and mobility challenges and needs. We find that despite some positive mobility indicators in the inner city (mixed-use environment, frequent bus service, and short travel distances), these elders face significant mobility challenges because of a deteriorated built environment, heavy traffic, homelessness, and crime. A limitation of this research is that the small sample did not allow the study of possible gender or race/ethnicity differentiation in the travel patterns and needs of older adults.

Takeaway for practice: Planners should not rely only on information from the census and other aggregate data sources to understand the mobility needs of older adults but should complement this information with direct interaction with the communities for which they are planning. Although some social problems limiting the mobility of older adults are difficult to tackle, environmental and streetscape improvements can significantly enhance their mobility.     

Guidelines for a Polycentric Region to Reduce Vehicle Use and Increase Walking and Transit Use

Abstract

Problem, research strategy, and findings: The monocentric development pattern in the Alonso–Mills–Muth model underpinned theoretical discussions of urban form in the 1960s and 1970s and truly dominated theory up to the point when Joel Garreau published Edge City: Life on the New Frontier in the early 1990s. Monocentric development patterns remain dominant to this day among smaller metropolitan areas in the United States. However, for larger metropolitan areas in the United States, regional transportation plans suggest a paradigm shift to a polycentric structure. We review 126 regional transportation plans in the United States and find that a hierarchy of centers connected by high-quality transit has become the dominant vision for most of them. The plan for Salt Lake City (UT), for example, strives for a multicentered region even though secondary centers are only beginning to emerge beyond a dominant downtown. Generally missing from regional transportation plans are quantitative criteria for designating and guiding centers: In no case are the quantitative criteria empirically based on proven transportation benefits. Here we investigate how the built environment characteristics of centers are associated with people’s travel mode choices and vehicle use. We employ visual and exploratory approaches through a generalized additive model (GAM) to identify nonlinear relationships between travel outcomes and “D” variables (density, diversity, design, destination accessibility, and distance to transit) within centers. The model and plots help us recommend the built environment characteristics of centers.

Takeaway for practice: The built environment thresholds and relevant tools provided here can enable planners to make informed decisions about future growth patterns, set realistic—yet visionary—goals, and improve the overall health of its residents and communities. We provide strategies and tools that planning agencies, such as metropolitan planning organizations, transit agencies, and municipalities, can adopt to channel developments into centers.     

From the Editors

Problem: Reducing gasoline consumption could sharply curtail greenhouse gas emissions. Ongoing research seeks to document factors associated with green travel behavior, like walking and transit use.

Purpose: We seek to determine whether green beliefs and values are associated with green travel behavior. We measure whether residents of communities with environmentalist attributes drive less, consume less gasoline, and are more likely to commute by private vehicle. We explore several channels through which green beliefs and values may affect travel behavior and vice versa.

Methods: We drew our demographic, transportation, and built environment data from the 2000 Census of Population and Housing including the Public Use Microdata Sample and the 2001 National Household Travel Survey, and constructed our indicators of green ideology using voting records, political party membership, and data on hybrid auto ownership. We estimated ordinary least squares regression and linear probability models using both individual households and small areas as units of analysis.

Results and conclusions: We find green ideology is associated with green travel behavior. People with green values are more likely than others to be located in communities with high population densities and proximity to city centers and rail transit stations, which are attributes conducive to environmentally friendly travel. We also find that residents of green communities engage in more sustainable travel than residents of other communities, even controlling for demographics and the effects of the built environment. Green ideology may cause green travel behavior because greens derive utility from conservation or because greens locate in, or create, areas with characteristics that promote sustainable travel. We also discuss the possibility that green travel behavior may cause green beliefs.

Takeaway for practice: If greens self-select into dense, central, and transit-friendly areas, the demand for these characteristics may rise if green consciousness does. Alternatively, if these characteristics cause green consciousness, their promotion promises to increase green behavior. The implications of our finding that residents of green communities engage in more sustainable travel patterns than others depends on the causal mechanism at work. If greens conserve because they derive utility from it, then environmental education and persuasion may bring about more sustainable travel. Alternatively, if green travel behavior causes green beliefs, it is possible that attracting more travelers to alternate modes and reducing vehicle miles traveled may increase environmental consciousness, which may in turn promote other types of pro-environment behavior.

Research support: None.     

Transit Strategies for Suburban Communities

Transit is asked to cure a variety of ills in modern, low-density cities: isolation of those who cannot drive, traffic congestion, air pollution, energy waste, and inner-city decay. Transit planning is difficult because of the wide dispersion of origins and destinations and the temporal rhythms of travel. The options in deploying buses are reviewed relative to those attributes that attract passengers: accessible service that goes directly from here to there without taking too long. The planner who understands these fundamental requirements can both evaluate transit proposals and modify land use plans to facilitate transit service.     

Complementary Pricing and Land Use Policies: Does It Lead to Higher Transit Use?

Problem, research strategy, and findings: A shift toward more sustainable transportation requires both adequate pricing of externalities from driving and supportive land use policies. However, proponents of each approach often under-estimate the complementarity and potential synergy between them. This study investigates the interaction effects between gasoline prices and land use (policy) variables using a panel dataset of transit ridership in 67 urbanized areas between 2002 and 2010. We found that while doubling the average gasoline price would increase transit ridership by 8.4% in an urbanized area with mean density and no regional containment policy, in areas with slightly higher density and a regional containment policy, the impact of higher gasoline prices would rise to 21%. In communities that had adopted a package of smart growth land use options, the impact of higher gasoline prices on transit use is even greater.

Takeaway for practice: Pricing schemes will be more effective where alternatives to automobility and supportive land use policies exist. The impacts of urban form on travel behavior are also strengthened when driving externalities are correctly priced. Planners and policymakers should take advantage of the complementarity between pricing and land use planning approaches by implementing policies in combined and well-coordinated ways.     

Travel mode choice as a representation of travel utility: A multilevel approach reflecting the hierarchical structure of trip,individual, and neighborhood characteristics

Trip characteristics, travel utility, socio-economic characteristics, and built environment influence travel mode choice. Since the elements have a hierarchical structure, this study conducted multilevel multinomial logistic regression to evaluate the relationship between these elements and travel modes. Particularly, this study focused on how twelve types of expressed travel utilities affect travel mode choice for five travel purposes. The results show that people consider various travel utilities for each travel purpose; these elements influence the travel mode choice of cars, public transit, or non-motorized modes, for example, public transit is preferred for punctuality and multitasking in commute, and for health benefits in shopping.