Keys to effective transit strategies for commuting

Commuting poses relevant challenges to cities\u2019 transport systems. Various studies have identified transit as a tool to enhance sustainability, efficiency and quality of the commute. The scope of this paper is to present strategies that increase public transport attractiveness and positively impact its modal share, looking at some case studies and underlining key success factors and possible elements of replica to be ultimately planned in some of the contexts of the Interreg project SMART-COMMUTING. The strategies analyzed in this paper concern prices and fares, service expansion, service improvements, usage of vehicle locators and other technology, changes to the built environment. Relevant gains in transit modal share are more easily achievable when considering integrations between various strategies, thus adapting and tailoring the planning process to the specific context

Net Effects of Gasoline Price Changes on Transit Ridership in U.S. Urban Areas, MTI Report 12-19

Using panel data of transit ridership and gasoline prices for ten selected U.S. urbanized areas over the time period of 2002 to 2011, this study analyzes the effect of gasoline prices on ridership of the four main transit modes—bus, light rail, heavy rail, and commuter rail—as well as their aggregate ridership. Improving upon past studies on the subject, this study accounts for endogeneity between the supply of services and ridership, and controls for a comprehensive list of factors that may potentially influence transit ridership. This study also examines short- and long-term effects and non-constant effects at different gasoline prices. The analysis found varying effects, depending on transit modes and other conditions. Strong evidence was found for positive short-term effects only for bus and the aggregate: a 0.61-0.62 percent ridership increase in response to a 10 percent increase in current gasoline prices (elasticity of 0.061 to 0.062). The long-term effects of gasoline prices, on the other hand, was significant for all modes and indicated a total ridership increase ranging from 0.84 percent for bus to 1.16 for light rail, with commuter rail, heavy rail, and the aggregate transit in response to a 10 percent increase in gasoline prices. The effects at the higher gasoline price level of over $3 per gallon were found to be more substantial, with a ridership increase of 1.67 percent for bus, 2.05 percent for commuter rail, and 1.80 percent for the aggregate for the same level of gasoline price changes. Light rail shows even a higher rate of increase of 9.34 percent for gasoline prices over$4. In addition, a positive threshold boost effect at the $3 mark of gasoline prices was found for commuter and heavy rails, resulting in a substantially higher rate of ridership increase. The results of this study suggest that transit agencies should prepare for a potential increase in ridership during peak periods that can be generated by substantial gasoline price increases over$3 per gallon for bus and commuter rail modes, and over $4 per gallon for light rail, in order to accommodate higher transit travel needs of the public through pricing strategies, general financing, capacity management, and operations planning of transit services

Mixed Data and Classification of Transit Stops

An analysis of the characteristics and behavior of individual bus stops can reveal clusters of similar stops, which can be of use in making routing and scheduling decisions, as well as determining what facilities to provide at each stop. This paper provides an exploratory analysis, including several possible clustering results, of a dataset provided by the Regional Transit Service of Rochester, NY. The dataset describes ridership on public buses, recording the time, location, and number of entering and exiting passengers each time a bus stops. A description of the overall behavior of bus ridership is followed by a stop-level analysis. We compare multiple measures of stop similarity, based on location, route information, and ridership volume over time

Centrality and connectivity in public transport networks and their significance for transport sustainability in cities

The promotion of public transport as a backbone of mobility in urban agglomerations, or at least as an alternative to the dominance of the automobile, has become a prominent policy focus in most large cities around the world. However, while some cities have been successful in shifting car journeys onto rail and buses, others are struggling despite considerable effort to make public transport more attractive. This paper provides a brief overview of success factors for public transport and then takes the configuration of public transport networks as a vantage point for policy evaluation. The development of centrality and connectivity indicators for the public transport network of Melbourne's north-eastern suburbs delivers an instrument for assessing the congruence of the systems with the geographical structure of central areas and urban activities in these cities. It is hypothesised that a higher number of convenient transfer points and a choice of routes to users (network connectivity), as well as a high degree of spatial overlap and integration between public transport infrastructure and urban activity centres and corridors (centrality of facilities) will lead to a greater role for public transport in the mobility patterns of the city as a whole

What’s Behind Recent Transit Ridership Trends in the Bay Area? Volume I: Overview and Analysis of Underlying Factors

Public transit ridership has been falling nationally and in California since 2014. The San Francisco Bay Area, with the state’s highest rates of transit use, had until recently resisted those trends, especially compared to Greater Los Angeles. However, in 2017 and 2018 the region lost over five percent (>27 million) of its annual riders, despite a booming economy and service increases. This report examines Bay Area transit ridership to understand the dimensions of changing transit use, its possible causes, and potential solutions. We find that: 1) the steepest ridership losses have come on buses, at off-peak times, on weekends, in non-commute directions, on outlying lines, and on operators that do not serve the region’s core employment clusters; 2) transit trips in the region are increasingly commute-focused, particularly into and out of downtown San Francisco; 3) transit commuters are increasingly non-traditional transit users, such as those with higher incomes and automobile access; 4) the growing job-housing imbalance in the Bay Area is related to rising housing costs and likely depressing transit ridership as more residents live less transit-friendly parts of the region; and 5) ridehail is substituting for some transit trips, particularly in the off-peak. Arresting falling transit use will likely require action both by transit operators (to address peak capacity constraints; improve off-peak service; ease fare payments; adopt fare structures that attract off-peak riders; and better integrate transit with new mobility options) and public policymakers in other realms (to better meter and manage private vehicle use and to increase the supply and affordability of housing near job centers)

THE HIGH-SPEED RAIL DEVELOPMENT IN THE NORTHEAST MEGAREGION OF THE UNITED STATES: A CONCEPTUAL ANALYSIS

This paper examines the high-speed rail (HSR) development issues in the Northeast Megaregion of the United States (U.S.). Due to chronic underinvestment and a myriad of other factors, the only operational HSR in the U.S., i.e., Amtrak’s Acela Express, is lagging behind the Japanese Shinkansen and other advanced HSR systems in the world in its operating performance and relative modal importance. This study adopts both regional and international perspectives to address this issue. The regional perspective conducts the passenger rail transportation deficiency analysis on the Northeast Corridor (NEC). The international perspective introduces the Japanese railway privatization process and its consequences. Based on empirical research, this paper proposes a set of improvement strategies and draws conclusions.Northeast Megaregion, High-Speed rail, Amtrak, Shinkansen, Japan.

Transport poverty meets the digital divide : accessibility and connectivity in rural communities

Peer reviewedPublisher PD

How (In)accurate Are Demand Forecasts in Public Works Projects? The Case of Transportation

This article presents results from the first statistically significant study of traffic forecasts in transportation infrastructure projects. The sample used is the largest of its kind, covering 210 projects in 14 nations worth US$59 billion. The study shows with very high statistical significance that forecasters generally do a poor job of estimating the demand for transportation infrastructure projects. The result is substantial downside financial and economic risks. Such risks are typically ignored or downplayed by planners and decision makers, to the detriment of social and economic welfare. For nine out of ten rail projects passenger forecasts are overestimated; average overestimation is 106 percent. This results in large benefit shortfalls for rail projects. For half of all road projects the difference between actual and forecasted traffic is more than plus/minus 20 percent. Forecasts have not become more accurate over the 30-year period studied. If techniques and skills for arriving at accurate demand forecasts have improved over time, as often claimed by forecasters, this does not show in the data. The causes of inaccuracy in forecasts are different for rail and road projects, with political causes playing a larger role for rail than for road. The cure is transparency, accountability, and new forecasting methods. The challenge is to change the governance structures for forecasting and project development. The article shows how planners may help achieve this.Comment: arXiv admin note: text overlap with arXiv:1302.2544, arXiv:1303.6571, arXiv:1302.364

Transit in Washington, D.C.: Current Benefits and Optimal Level of Provision

The discrepancy between transit’s large share of local transportation resources and its generally low share of local trips has raised questions about the use of scarce transportation funds for this purpose. We use a regional transport model consistent with utility theory and calibrated for the Washington, D.C., metropolitan area to estimate the travel benefits of the local transit system to transit users and the congestion-reduction benefits to motorists. We find that (i) rail transit generates congestion-reduction benefits that exceed rail subsidies; (ii) the combined benefits of rail and bus transit easily exceed local transit subsidies generally; (iii) the lowest-income group receives a disproportionately low share of the transit benefits, both in absolute terms and as a share of total income; and (iv) for practical purposes, the scale of the current transit system is about optimal.transit, transit subsidies, external transit benefits