Transportation Research Record: Journal of the Transportation Research Board

Transit research is explored with the aim of understanding areas covered, research trends, research uses, and how research provision matches needs. The method involves an empirical analysis of the content, use, and users of the World Transit Research Clearinghouse website (http://www.worldtransitresearch.info). Results indicate that the Transportation Research Record is the academic journal that publishes the most transit research, but only 14% of its papers are on transit. Transport Policy is the second-largest source, but papers on transit make up 58% of its publications. Most research papers on transit concern bus, rail, or mass transit. In the past decade, the most significant change in publications by transit mode is that the segment on bus rapid transit research has grown, although it still accounts for a small share of overall content. Consumption of research content by mode is highest for bus rapid transit, followed by light rail or tram, then by bicycle or pedestrian. A comparison of research supply and research consumption suggests that research papers concerning (in order) sustainability, urban density, and ridership growth have the highest readership but represent a small share of research content in the field. User surveys had a low response rate but the responses received suggest that professionals including government policy makers, consultants, and academics are the major research users. The most common use of transit research is to be kept informed; however, research also is cited as evidence, notably by academics. A modest but significant share of professionals use transit research for transit policy, service development, or both. Opportunities for future research are identified.

This paper examines the design of high-performance transit networks that minimize transit agency costs, the time of transit users in the system, and the travel time of car users. Surface transit services need segregated lanes to achieve a target cruising speed so that the transit network length has a significant effect on traffic performance. This effect is modeled with the macroscopic fundamental diagram (MFD). The optimization proceeds in two steps. First, an analytic model defines the optimal layout of surface transit networks according to the time headway, stop spacing, line spacing, and network size variables. Then, the average travel time of the traffic network is evaluated with the MFD curve corresponding to the former transit network length. The full methodology has been implemented in the city of Barcelona, Spain. MFD was calibrated in the city's central district by means of traffic microsimulation runs. The social optimum for the number of corridors is 15, somewhat smaller than the optimization that does not consider traffic (23 corridors).

A location method is presented for an urban public transit (PT) network based on the hub-and-spoke network structure model. The proposed method integrates the PT lines with transfer hubs. PT lines fall into four major service levels: subway, bus rapid transport, bus, and feeder bus. The transfer hubs fall into three major categories: intermodal terminals, transfer centers, and transfer stations. Every level of PT line is located by connecting the different classes of transfer hubs. The optimization objectives, constraints, and procedures for PT line locations are present, and they vary by level of PT service. The design and implementation of the proposed method are illustrated by a case study for the city of Fuzhou, China. The proposed allocation method offers a new approach for increasing the PT level of service of a high-density city. The procedure for allocating PT lines is practical and maneuverable.

Accessibility to public transportation is an important element for the specification of activity participation and travel behavior models, the assessment of level of service by public transportation, equity analysis, and the design of public transportation provision. Although transit ridership is lower in the United States than in other countries, transit serves a segment of the population that may benefit substantially from its provision. The relative attractiveness of public transportation depends critically on its performance in terms of the accessibility provided to link people with employment and activity opportunities. In practice, an effective method to derive such indicators and related performance measures is lacking. An opportunity-based transit accessibility measure applied to the Southern California Association of Governments megaregion is presented. The indicators computed are sensitive to the availability of opportunities for travelers within a day (e.g., related to the opening and closing hours of businesses) and are a direct function of the transit routes and schedules and the associated spatiotemporal variation of level of service during a day. The method is described, examples on transit accessibility are provided, and the results are compared with automobile accessibility.

The development and the application of a stop aggregation model (SAM) for a transit network based on Google's General Transit Feed Specification (GTFS) are detailed. The use of GTFS has been drawing attention in the public transit planning arena. A SAM is proposed to explore how to use this innovative data source in a transit network. The hypothesis is based on the fact that transit users' activity may not originate from or be destined to an individual stop per se. Rather, the activity is associated with a specific location in the vicinity of the stop, and this location may be covered by several adjacent transit stops. Therefore, the goal of a SAM is to define a generalized definition of a stop that more closely matches the nature of locations that serve as passenger origins and destinations. To define an aggregate area around a transit stop or station, three parameters are investigated: distance or proximity, text in the stop description, and the catchment (service) area. These aggregated stop groups can be represented as a single node in the transit network, depending on the level of aggregation desired. A case study of the Minneapolis–Saint Paul metropolitan area in Minnesota is performed with GTFS data from Metro Transit. A SAM can be practically applied in estimating aggregate-level origin–destination flows and linking with onboard survey data.

During the past decade, a significant amount of research has been dedicated to the use of smart card data for various purposes. A method is presented for the detection and estimation of the location, time, duration, and purpose of activities undertaken by public transit users with the use of smart card databases and other available information about land use and user behavior. The method is applied to cases in Santiago, Chile, and Gatineau, Quebec, Canada, to identify activity purpose and time frame to characterize user behavior. The results obtained for each city are compared to discover differences in behavioral activity patterns due to sociological, cultural, and geopolitical differences.

In times of climate change and scarce resources, it is essential to reduce emissions and to use fuel as economically as possible. The transportation sector alone accounts for 44% of the energy use in New Zealand, with only about one-quarter of that amount being used by the transportation industry for transporting goods. Therefore, an attractive public transport service and prudent use of its vehicles can help make travel more economical, thus saving resources and reducing carbon dioxide emissions. How to make public bus services more attractive is demonstrated with two simultaneous objectives: minimizing the expected passenger waiting time and minimizing the discrepancy from a desired occupancy level on the vehicles. The first objective is intended to improve the service and attract more users, and the second objective is intended to ensure economical operation. A network-based procedure is used to create timetables with multiple vehicle types to solve this multiobjective problem. The method is applied to a case study in Auckland, New Zealand, and results in a savings of more than 43% of passenger waiting time while attaining an acceptable passenger load on all vehicles.

The case for transit priority can be substantially enhanced if direct passenger travel time benefits are supplemented by secondary benefits, such as mode shift (from automobile drivers) and operating fleet resource savings (due to running time improvements). Although these effects have been theorized in previous research, no quantitative evidential basis has been established. As part of a wider international research project aiming to develop new methodologies to plan and optimize the design of transit priority schemes, actual evidence of transit priority impacts is used to fill this gap and expand on previous theoretical models. Evidence of mode shift effects suggests that transit priority can generate mode shift from automobile drivers at levels of travel time savings much lower than those suggested in previous theoretical models. A strong statistical link between the percentage of travel time savings resulting from transit priority and reductions in automobile driving was established (R² = .76). Evidence shows that transit fleet savings resulting from priority schemes can occur at much lower levels of travel time savings than previously suggested, as long as transit route lengths and headways are reasonably short. Analysis results suggest that savings in fleet resources will continue beyond the thresholds suggested in theoretical models. A revised theoretical model of the secondary benefits of transit priority is suggested; it reveals that benefits are cumulative and generally higher than previously suggested. Areas for future research are recommended.

Public transit professionals continue to seek methods that offer greater service opportunities without a material increase in the costs of service provision. One strategy is to construct bus transit centers, which operate much like the airline hub-and-spoke concept. More frequent destinations can be made available with shorter patron wait times and little or no increase in the number of bus hours. Patrons tend to appreciate the convenience of a transfer occurring in a lighted facility as well as the increased level of bus service. Many bus-based centers may be close to single-family neighborhoods, and residents might express concern about property values given the presence of a bus transit center nearby. In addition to the bus transit centers that serve traditional local or express routes, several bus rapid transit lines are planned in other cities, with stations that might lead nearby communities to ask similar questions about property values. The impact of bus transit centers is assessed on nearby single-family residential property values in Houston, Texas. Five Houston transit centers show that the transit centers in low- and moderate-income neighborhoods have a positive influence on property values. In the single affluent neighborhood in the study, results indicate the transit center negatively affects property values, but the influence is less than that of other variables.

Since 1999, 23 New Jersey transit villages have been designated in New Jersey municipalities, with the intention of intensifying development around rail stations and bus hubs. As one test of the effectiveness of this state effort, the appreciation in residential property values is investigated and compared with that in other municipalities in the state. Some limited positive evidence is found to support the New Jersey transit village designation. Econometric analysis of the change in average residential sales price over 9 years finds an association but cannot establish a causal effect. Case study analysis of selected New Jersey transit villages suggests that the forethought, commitment, and political will required to apply for transit village status may be what sparks municipal development rather than the designation itself.

Existing research rarely goes beyond individual dimensions of neighborhood change to explore the broader neighborhood impacts of transit investments as perceived by neighborhood residents. To fill gaps in this knowledge, the residents of selected neighborhoods along four transit corridors in the Twin Cities area of Minnesota were surveyed. Survey results show that residents of the study neighborhoods had generally positive perceptions of transit-induced neighborhood change. However, significant differences existed between urban and suburban areas and between individual neighborhoods. In addition, African-Americans, immigrants, frequent transit users, carless residents, and new residents in general had more positive perceptions of transit-induced neighborhood change than did whites, nonimmigrants, infrequent or nontransit users, residents with access to a motor vehicle, and longtime residents. Asian urbanites had more negative perceptions. Implications of these findings are discussed.

The 0.5-mile distance has become accepted for gauging a transit station's catchment area in the United States and is the de facto standard for the planning of U.S. transit-oriented developments (TODs). Planners and researchers use transit catchment areas not only to make predictions about transit ridership and transit impacts (socioeconomic and on land use) but also to prescribe regulations (e.g., relaxing restrictive zoning or carving out TODs for financial plans). This radius is loosely based on the distance that people are willing to walk to transit, but the same reasoning has been used to justify other transit catchment areas. Station-level variables from 1,449 high-capacity American transit stations in 21 cities are used to determine whether a clear benchmark between distance and ridership provides a norm for station-area planning and prediction. Results indicate that, for the purposes of predicting station-level transit ridership, different catchment areas have little influence on a model's predictive power. This finding suggests that transit agencies should use the easiest, most readily available data when estimating direct demand models. The evidence is less clear for prescribing land use policy. Nevertheless, results support the use of a 0.25-mile catchment area around transit for jobs and a 0.5-mile catchment area for population. Even though these distances probably will vary, depending on the location and the study purpose, the distances are good starting points for considering transit-oriented land use policy or collecting labor-intensive data, such as surveys, about transit-adjacent firms or households.

A simple analysis framework is presented to assist transit agencies and station-area communities in making informed planning decisions regarding the highest and best use of parking areas at suburban transit stations. The framework provides the flexibility to tailor values to local settings. The success of high-capacity transit systems depends on well-located and -designed stations. Outside regional commercial business districts, the most favored means of access to transit stations often is a park-and-ride facility. Many suburban station locations have reached full use of limited parking resources, and parking capacity has begun to limit opportunities to increase rail transit ridership. Thus, these major cost transit investments are not fulfilling their full potential as a result of constrained access capacity. Also, many station communities increasingly have been pressuring transit agencies to convert some station patron parking to transit-oriented development (TOD) uses, and some nearby private parking lots have been lost to TOD. Thus, station parking is not only limited but also under pressure for reduction. Little information exists to help transit agencies and local communities understand the highest and best use of limited station site resources. A simple spreadsheet analysis framework is presented to help transit agencies and local communities make informed decisions regarding parking and TOD. This suggested analysis framework focuses on the rail transit ridership implications of parking versus TOD and on the cost of station parking.

The rail rapid transit (metro) systems in Bangkok, Thailand, lack good intermodal connections. Actions that could improve connections between metros and buses are specified. More than 300 surveys were used to identify passenger perceptions of specific conditions of transfers between subway stations and buses. Passengers expressed high levels of dissatisfaction with specified conditions and the overall transfer experience; this finding suggests that intermodal metro–bus transfers could be greatly improved. The information was used to calibrate importance–satisfaction analysis and ordinal regression models. Model results suggest that the conditions that could have the greatest effect on the overall transfer experience are safety from crime and the distance between subway exits and bus stops.

A procedure is developed to assess the economic feasibility of park-and-ride facilities. Relevant literature is discussed, and a mathematical formulation that can be integrated with a regional planning model is produced and applied to the selection of park-and-ride facilities in New York City. The evaluation procedure is divided into two main stages: candidate selection and candidate evaluation. The candidates are selected according to a set of criteria that includes demand considerations, transit connectivity and design, community integration, and economic viability. Economic assessment of the candidates considers the generalized cost of travel and entails the use of a binary logit model and the computation of four performance measures: expected demand, market share, weighted average savings, and present value of benefits.

Metro transit networks are constantly expanding to meet the growing travel demand that accompanies rapid urban growth. One main disadvantage of metro transport is its heavy reliance on access and egress transport and, hence, on the corresponding transfer facilities. Improvements to these transfer facilities therefore have the potential to increase use of the metro system while possibly alleviating the traffic load on the urban road network. Because bicycle transfer at metro stations—that is, using a bicycle as mode of access to or egress from the metro system—is underused, the determinants of the demand for bicycle transfer are investigated. Results and findings are valuable for designing policies aimed at improving metro ridership and for designing bicycle parking and transfer facilities at metro stations. To this end, several metro stations in Nanjing, China, were analyzed, and two stereotypical metro stations were selected for how well they represented the system. A large-scale survey was conducted on metro travelers' opinions on and use of bicycle transfer facilities, and data were collected on the current attributes of service groups, bicycle parking occupancy, and transfer mode alternatives. Furthermore, metro travelers' (latent) transfer preferences for bicycle rental facilities were investigated. Two transfer choice models were estimated to identify and quantify the determinants for bicycle transfer demand: one focuses on current walk–metro trips, and the other focuses on current bus–metro trips. The explanatory determinants are discussed, and relative weights are computed with multiple linear regression analysis.

The Metro light rail line opened in Phoenix, Arizona, in December 2008 as the nation's largest modern high-capacity transit system starter line. Spanning 24 miles and 28 stations, Metro connected three cities with radically different land use policies. The response of the Phoenix land market to the 1997 announcement of the station locations was investigated as an interrupted time series case study. Studies evaluating public investments commonly use hedonic modeling to calculate one average attributable percentage increase for all properties affected by the investment. Conclusions were drawn about the relative development potential of each individual Phoenix transit station by comparing land sales prices per square foot before and after the light rail announcement. Data on the percentage increase in value were augmented with qualitative observations, and transit stations were compared with Phoenix's most prominent, centrally located, mixed-use intersections not serviced by high-capacity transit to further evaluate the development potential for light rail. Across the three cities served by Metro, station area values increased the most in Tempe, Arizona; only the stations immediately adjacent to Tempe decreased in market value. Sales volume tripled in the 3 years immediately after the station location announcement. The effectiveness of public policy, and of the light rail investment itself, can be gauged by the market for vacant land before, during, and after construction of the light rail system. Additional investigation of these three distinct periods may help local governments plan more effective station areas and recapture land value increases to fund transit improvements.

People's perceptions about the appropriate location of mobility centers are modeled. A case study for the Municipality of Kalamaria in Thes-saloniki, Greece, is presented. The results of a stated preference survey, which revealed residents' perceptions about the optimal locations for these centers, as well as the spatial and other characteristics of the region, were used as inputs. Models were then developed and estimated: a linear regression model, a spatial simultaneous autoregressive (SAR) model, and a geographically weighted regression (GWR) model. The exploratory analysis used the respondents' perception of optimal location as the response variable, and the explanatory variables are information about the population; points of interest; bus routes; average income; road network (i.e., length, number of lanes, and average speeds); and distances from stadium, pedestrian shopping zone, and paid parking facility. Results indicated that the selection of the appropriate location for a mobility center was influenced primarily by number of residents, number of points of interest, number of bus routes, average vehicle speed, and length of the road network. The GWR model seemed to fit the data best, whereas Moran's I-test showed that the model solved the autocorrelation of the residuals, something that the other models [ordinary least squares (OLS) and SARmix] fail to accomplish. The model's predicted values were localized (unlike OLS) and made the decision easier. The proposed method is generic (not system dependent) and can be applied to different optimal location selection schemes, especially those with similar demand characteristics (e.g., for automobile- or bike-sharing stations).

The effects of a real-time bus information system, Chicago Transit Authority (CTA) Bus Tracker, on the ridership of the CTA transit rail system in Chicago, Illinois, are examined with panel data on monthly average weekday ridership at each transit train station in the entire CTA system from January 2005 through December 2010. Other factors that might contribute to changes in CTA rail ridership (e.g., socioeconomic situation, transit service, and weather) are controlled. Results of a mixed linear model indicate that Bus Tracker service increases CTA train ridership. This increase might be attributable to the increased intermodal transfer efficiency between CTA buses and trains that results from the real-time bus information provided. Findings suggest that the complementarity effect of providing real-time bus information outweighs its substitution effect on the ridership of a connected transit rail system. Together with the findings from an earlier study (which show that Bus Tracker service helps to increase bus ridership), study results provide empirical evidence in support of the hypothesis that implementation of a real-time transit information system leads to gains in transit ridership.