A simultaneous route-level transit patronage model: demand,supply, and inter-route relationship

In this paper we present a route-level patronage model that incorporates transit demand, supply and inter-route effects in a simultaneous system. The model is estimated at the route-segment level by time of day and direction. The results show strong simultaneity among transit demand, supply and competing routes. Transit ridership is affected by the level of service, which in turn is determined by current demand and ridership in the previous year. The model demonstrates that a service improvement has a twofold impact on ridership; it increases ridership on the route with service changes, but it also reduces the ridership on competing routes so that the net ridership change is small. The model is thus useful for both system-level analysis and route-level service planning.     

Airlines’ reaction to high-speed rail entries: Empirical study of the Northeast Asian market

We investigate the impact of the commencement of high-speed rail (HSR) services on airlines’ domestic available seats on affected routes in China, Japan, and South Korea. The study is based on a dataset covering the 1994–2012 period. We use the propensity score matching method to pair HSR affected routes with routes without HSR services. The difference-in-difference approach is used to estimate the impact of HSR entry. We find that HSR entries may, on average, lead to a more significant drop in airlines’ seat capacity in China than in Japan and Korea given similar HSR service speed. In China, HSR services with a maximum speed about 200 km/h can produce strong negative impacts on medium-haul air routes but induce more air seat capacity on long-haul routes. HSR services with a maximum speed of 300 km/h have little extra impact on medium-haul routes but a strong negative impact on long-haul routes. Finally, although HSR has a strong negative impact in Japan’s short-haul and medium-haul air markets, little impact is observed in its long-haul markets.     

The Movingo integrated ticket: seamless connections across the mälardalen region of Sweden

ABSTRACT

The need for improved public transport (PT) ticketing in ever-growing deregulated PT markets has made well-designed integrated ticketing systems a priority area of intervention for PT service providers around the world. Yet, very little practical evidence of its impacts are reported in Sweden and in the world at large. The focus of this study was the impacts of the Movingo integrated ticketing scheme in terms of PT patronage, user satisfaction and the perceived quality of the ticketing set-up. Three travel surveys were conducted along the Stockholm-Uppsala route. Methods including logistic regression and correlated t-tests were used to analyse the samples. The findings suggest that the scheme made rail commuting more attractive resulting in an overall increase of about 24% in ticket sales with 3% – 15% car commuters reporting that they patronised PT services after the project. The scheme also resulted in increased rail commuter satisfaction. The overall perceived quality of the ticketing set-up did not however improve due to interoperability challenges. Service providers’ uncertainty about equitable distribution of revenue among the participating service providers, interoperability challenges and the lack of interest among most of the participating service providers to sell Movingo tickets are some issues to be addressed.     

Integrating geographic information systems into transit ridership forecast models

Researchers have produced sophisticated modal split and transit demand models, including forecasts that are sensitive to the level of service. However, little effort has been made to integrate these models into corridor studies and route alignment analyses since (a) re-routing is itself an extremely complex modeling task, and (b) the results of the demand models are presented in tabular form with no facility to visualize spatial patterns and relationships that, if recognized, would aid in the routing tasks. GIS tools can be used, together with the demand models, to identify both clusters of city blocks that house families with certain socioeconomic characteristics and potential trip destinations conducive to transit use. In other words, GIS tools can be used to better measure some of the factors that are needed by transit demand models. The results of these models can be displayed graphically, enabling analysts to target places needing improved service, evaluate route re-alignment alternatives, and operate more efficient and effective bus lines. This paper examines how a particular class of model used by transit agencies for estimating ridership can be integrated with GIS tools in order to facilitate such analyses. It also explores the effects of visualization of routes, demographics, and employment data on the process of designing route alignments with better targeting of high transit ridership areas. This paper is part of a research project sponsored by the Region One University Transportation Center, at MIT.     

Secrets of success: assessing the large increases in transit ridership achieved by Houston and San Diego transit providers

This paper summarizes and updates the findings from an earlier study by the same authors of transit systems in Houston (all bus) and San Diego (bus and light rail). Both systems achieved unusually large increases in transit ridership during a period in which most transit systems in other metropolitan areas were experiencing large losses. Based on ridership models estimated using cross section and time series data, the paper quantifies the relative contributions of policy variables and factors beyond the control of transit operators on ridership growth. It is found that large ridership increases in both areas are caused principally by large service increases and fare reductions, as well as metropolitan employment and population growth. In addition, the paper provides careful estimates of total and operating costs per passenger boarding and per passenger mile for Houston's bus operator and San Diego's bus and light rail operators. These estimates suggest that the bus systems are more cost-effective than the light rail system on the basis of total costs. Finally, the paper carries out a series of policy simulations to analyze the effects of transit funding levels and metropolitan development patterns on transit ridership and farebox recovery ratio.     

The impact of real-time information on bus ridership in New York City

In the past few years, numerous mobile applications have made it possible for public transit passengers to find routes and/or learn about the expected arrival time of their transit vehicles. Though these services are widely used, their impact on overall transit ridership remains unclear. The objective of this research is to assess the effect of real-time information provided via web-enabled and mobile devices on public transit ridership. An empirical evaluation is conducted for New York City, which is the setting of a natural experiment in which a real-time bus tracking system was gradually launched on a borough-by-borough basis beginning in 2011. Panel regression techniques are used to evaluate bus ridership over a three year period, while controlling for changes in transit service, fares, local socioeconomic conditions, weather, and other factors. A fixed effects model of average weekday unlinked bus trips per month reveals an increase of approximately 118 trips per route per weekday (median increase of 1.7% of weekday route-level ridership) attributable to providing real-time information. Further refinement of the fixed effects model suggests that this ridership increase may only be occurring on larger routes; specifically, the largest quartile of routes defined by revenue miles of service realized approximately 340 additional trips per route per weekday (median increase of 2.3% per route). Although the increase in weekday route-level ridership may appear modest, on aggregate these increases exert a substantial positive effect on farebox revenue. The implications of this research are critical to decision-makers at the country’s transit operators who face pressure to increase ridership under limited budgets, particularly as they seek to prioritize investments in infrastructure, service offerings, and new technologies.     

Ridership estimation procedure for a transit corridor with new bus rapid transit service

Ridership estimation is a critical step in the planning of a new transit route or change in service. Very often, when a new transit route is introduced, the existing routes will be modified, vehicle capacities changed, or service headways adjusted. This has made ridership forecasts for the new, existing, and modified routes challenging. This paper proposes and demonstrates a procedure that forecasts the ridership of all transit routes along a corridor when a new bus rapid transit (BRT) service is introduced and existing regular bus services are adjusted. The procedure uses demographic data along the corridor, a recent origin–destination survey data, and new and existing transit service features as inputs. It consists of two stages of transit assignment. In the first stage, a transit assignment is performed with the existing transit demand on the proposed BRT and existing bus routes, so that adjustments to the existing bus services can be identified. This transit assignment is performed iteratively until there is no adjustment in transit services. In the second stage, the transit assignment is carried out with the new BRT and adjusted regular bus services, but incorporates a potential growth in ridership because of the new BRT service. The final outputs of the procedure are ridership for all routes and route segments, boarding and alighting volumes at all stops, and a stop‐by‐stop trip matrix. The proposed ridership estimation procedure is applicable to a new BRT route with and without competing regular bus routes and with BRT vehicles traveling in dedicated lanes or in mixed traffic. The application of the proposed procedure is demonstrated via a case study along the Alameda Corridor in El Paso, Texas. Copyright © 2015 John Wiley & Sons, Ltd.     

What determines rail transit passenger volume? Implications for transit oriented development planning

Transit oriented development (TOD) has been an important topic for urban transportation planning research and practice. This paper is aimed at empirically examining the effect of rail transit station-based TOD on daily station passenger volume. Using integrated circuit (IC) card data on metro passenger volumes and cellular signaling data on the spatial distribution of human activities in Shanghai, the research identifies variations in ridership among rail transit stations. Then, regression analysis is performed using passenger volume in each station as the dependent variable. Explanatory variables include station area employment and population, residents’ commuting distances, metro network accessibility, status as interchange station, and coupling with commercial activity centers. The main findings are: (1) Passenger volume is positively associated with employment density and residents’ commuting distance around station; (2) stations with earlier opening dates and serving as transfer nodes tend to have positive association with passenger volumes; (3) metro stations better integrated with nearby commercial development tend to have larger passenger volumes. Several implications are drawn for TOD planning: (1) TOD planning should be integrated with rail transit network planning; (2) location of metro stations should be coupled with commercial development; (3) high employment densities should be especially encouraged as a key TOD feature; and (4) interchange stations should be more strategically positioned in the planning for rail transit network.     

Evaluating light rail sketch planning: actual versus predicted station boardings in Phoenix

In recent years, transit planners are increasingly turning to simpler, faster, and more spatially detailed “sketch planning” or “direct demand” models for forecasting rail transit boardings. Planners use these models for preliminary review of corridors and analysis of station-area effects, instead of or prior to four-step regional travel demand models. This paper uses a sketch-planning model based on a multiple regression originally fitted to light-rail ridership data for 268 stations in nine U.S. cities, and applies it predictively to the Phoenix, Arizona light-rail starter line that opened in December, 2008. The independent variables in the regression model include station-specific trip generation and intermodal–access variables as well as system-wide variables measuring network structure, climate, and metropolitan-area factors. Here we compare the predictions we made before and after construction began to pre-construction Valley Metro Rail predictions and to the actual boardings data for the system’s first 6 months of operations. Depending on the assumed number of bus lines at each station, the predicted total weekday ridership ranged from 24,767 to 37,907 compared with the average of 33,698 for the first 6 months, while the correlation of predicted and observed station boardings ranged from r = 0.33 to 0.47. Sports venues, universities, end-of-line stations, and the number of bus lines serving each station appear to account for the major over- and under-predictions at the station level.     

Analysis of Metro ridership at station level and station-to-station level in Nanjing: an approach based on direct demand models

A growing base of research adopts direct demand models to reveal associations between transit ridership and influence factors in recent years. This study is designed to investigate the factors affecting rail transit ridership at both station level and station-to-station level by adopting multiple regression model and multiplicative model respectively, specifically using an implemented Metro system in Nanjing, China, where Metro implementation is on the rise. Independent variables include factors measuring land-use mix, intermodal connection, station context, and travel impedance. Multiple regression model proves 11 variables are significantly associated with Metro ridership at station level: population, employment, business/office floor area, CBD dummy variable, number of major educational sites, entertainment venues and shopping centers, road length, feeder bus lines, bicycle park-and-ride (P&R) spaces, and transfer dummy variable. Results from multiplicative model indicate that factors influencing Metro station ridership may also influence Metro station-to-station ridership, varied by both trip ends (origin/destination) and time of day. In comparison with previous case studies, CBD dummy variable and bicycle P&R are statistically significant to explain Metro ridership in Nanjing. In addition, Metro travel impedance variables have significant influence on station-to-station ridership, representing the basic time-decay relationship in travel distribution. Potential implications of the model results include estimating Metro ridership at station level and station-to-station level by considering the significant variables, recognizing the necessity to establish a cooperative multi-modal transit system, and identifying opportunities for transit-oriented development.     

Transit passenger response: Short and long term elasticities using time series analysis

This paper investigates the effects of price and service changes on transit ridership. The concept of elasticity is introduced and the traditional methods for estimating elasticities are discussed. In this paper an extra dimension is added by investigating short and long term elasticities. Time series analysis, developed by Box and Jenkins is chosen for the analysis. The Box and Jenkins methodology is applied to a monthly time series of average weekday ridership on the Chicago Transit Authority (CTA) rail system. Four categories of explanatory variables are investigated: fare on the CTA rail system, service provided on the CTA rail system, cost of car trips and weather effects. The effects of gas prices and rail service were found to be significant; however the results indicate a twelve month delay before service changes influence ridership. The effect of transit fares was found to be insignificant, indicating that both the short and long term fare elasticities are zero.     

Passenger rail in North America in the light of developments in Western Europe and Japan

Because of different geo‐demographic and economic conditions, the impact of the new passenger modes (road and air) on rail travel was much larger in North America than in Europe. In 1960s and 1970s, as the railway share of intercity traffic in North America shrunk to a negligible one or two percent, the passenger trains were abandoned by private railway companies and taken over by state organizations, which have continued to operate traditional trains and generate mounting losses. On the technology side, no attempts have been made to improve competitiveness of trains vis‐a‐vis automobiles and airplanes.

In Europe and Japan, the railways responded to the challenge by (i) upgrading the performance (speed) and comfort of traditional trains operating on existing tracks and (ii) developing trains which could, on short and intermediate range distances, compete successfully, in terms of speed and economy, with the road and air modes. The Japanese (Shinkansen trains) and French (TGV trains) experience clearly shows that trains operating on dedicated lines at average speeds of 150 to 200 km/hr provide a superior transportation service and economy on high‐traffic intercity routes of up to about 500 km length. In this paper the factors responsible for the present status of passenger rail in North America are analysed, the current policies in the U.S. and Canada are evaluated in the light of experience to date and developments abroad, and suggestions for a long‐term passenger rail policy are made. This includes examination of (i) the viability of continued subsidization of traditional train services, (ii) the viability of operation of faster trains on existing tracks, (iii) the scope for introduction of modern, fast trains on dedicated lines in high‐density, intercity corridors, (iv) the application of fast trains as access to major airports and integration of airports with fast intercity lines, and (v) the impact of energy (oil) consumption in transportation.

     

Joint optimization of a rail transit line and its feeder bus system

A model is developed for jointly optimizing the characteristics of a rail transit route and its associated feeder bus routes in an urban corridor. The corridor demand characteristics are specified with irregular discrete distributions which can realistically represent geographic variations. The total cost (supplier plus user cost) of the integrated bus and rail network is minimized with an efficient iterative method that successively substitutes variable values obtained through classical analytic optimization. The optimized variables include rail line length, rail station spacings, bus headways, bus stop spacings, and bus route spacing. Computer programs are designed for optimization and sensitivity analysis. The sensitivity of the transit service characteristics to various travel time and cost parameters is discussed. Numerical examples are presented for integrated transit systems in which the rail and bus schedules may be coordinated.     

A time series analysis of monthly ridership for an urban rail rapid transit line

This paper presents two time series regression models, one in linear form and the other in logarithmic form, to estimate the monthly ridership of a single urban rail rapid transit line. The model was calibrated for a time period of about six and a half years (from 1978–1984) based on ridership data provided by a transit authority, gasoline prices provided by a state energy department, and other data.The major findings from these models are: (1) seasonal variations of ridership are –6.26%, or –6.20% for the summer period, and 4.77%, or 4.62% for the October period; (2) ridership loss due to a station closure is 2.46% or 2.41%; and (3) elasticities of monthly ridership are –0.233 or –0.245 with respect to real fare, 0.113 or 0.112 with respect to real gasoline price, and 0.167 or 0.185 with respect to real bridge tolls for the competing automobile trips. Such route specific application results of this inexpensive approach provide significant implications for policymaking of individual programs in pricing, train operation, budgeting, system changes, etc., as they are in the case reported herein and would be in many other cities.     

Customer choice patterns in passenger rail competition

This study explores determinants of customer choice behaviour in passenger rail competition on two cross-border routes, Cologne–Brussels and Cologne–Amsterdam. It fills a gap in the literature on competition in commercial passenger rail by relying on newly collected stated preference data from about 700 on-train interviews. Our multinomial Logit estimations reveal two important effects that are closely connected to (psychological) switching costs. First, the customers on the route Cologne–Amsterdam, for whom competition is a purely hypothetical situation, value a competitive market structure lower than customers on the already competitive route Cologne–Brussels. Second, travellers show a status quo bias with a preference for the service provider on whose trains they were interviewed. This effect goes beyond the impact exercised by explanatory variables capturing the observable differences of the services and customers, including loyalty-enhancing effects like the possession of customer cards. Our results imply that entry into the commercial passenger rail market may be more difficult than often thought. Thus, the study contributes to explaining the low level of competition in these markets in Europe.     

Examining the relationship between built environment and metro ridership at station-to-station level

Very few studies have examined the impact of built environment on urban rail transit ridership at the station-to-station (origin-destination) level. Moreover, most direct ridership models (DRMs) tend to involve simple a prior assumed linear or log-linear relationship in which the estimated parameters are assumed to hold across the entire data space of the explanatory variables. These models cannot detect any changes in the linear (or non-linear) effects across different values of the features of built environment on urban rail transit ridership, which possibly induces biased results and hides some non-negligible and detailed information. Based on these research gaps, this study develops a time-of-day origin-destination DRM that uses smart card data pertaining to the Nanjing metro system, China. It applies a gradient boosting regression trees model to provide a more refined data mining approach to investigate the non-linear associations between features of the built environment and station-to-station ridership. Data related to the built environment, station type, demographics, and travel impedance including a less used variable – detour, were collected and used in the analysis. The empirical results show that most independent variables are associated with station-to-station ridership in a discontinuous non-linear way, regardless of the time period. The built environment on the origin side has a larger effect on station-to-station ridership than the built environment on the destination side for the morning peak hours, while the opposite holds for the afternoon peak hours and night. The results also indicate that transfer times is more important variables than detour and route distance.     

Evaluating the assumption of independent turning probabilities

Several urban traffic models make the convenient assumption that turning probabilities are independent, meaning that the probability of turning right (or left or going straight through) at the downstream intersection is the same for all travelers on that roadway, regardless of their origin or destination. In reality most travelers make turns according to planned routes from origins to destinations. The research reported here identifies and quantifies the deviations that result from this assumption of independent turning probabilities.An analysis of this type requires a set of reasonably realistic “original” route flows, which were obtained by a static user-equilibrium traffic assignment and an entropy maximization condition for most likely route flows. These flows are compared with those route flows resulting from the Assumption of Independent Turning Probabilities (ITP). A small subnetwork of 3 km by 5 km in Tucson, Arizona, was chosen as a case study. An overall “typical ratio” of 2.2 between original route flows and ITP route flows was obtained. Aggregating route flows to origin–destination flows led to an overall “typical ratio” of 1.7. Such deviations are particularly high for routes that go back-and-forth, reaching a ratio of more than 3 in certain time periods. Substantial deviations for origins and destinations that are on the same border of the subnetwork are also observed in the analyses. In addition, under the ITP assumption, morning rush hour traffic peaking is the same in all directions, while in the original flows some directions do not exhibit a peak in the morning rush hour period. Overall, the conclusion of the paper is that the assumption of independent turning probabilities leads to substantial deviations both at the route level and at the origin–destination level, even for such a small network of the case study. These deviations are particularly detrimental when a network is being modeled and studied for route-based measures of effectiveness such as the number and types of routes passing a point – for monitoring specified vehicles and/or managing detouring strategies.     

Exhaust emissions generated under actual operating conditions from a hybrid vehicle and an electric one fitted with a range extender

The paper describes exhaust emission tests performed on a PHEV (Plug-in Hybrid Electric Vehicle) and a BEV (Battery Electric Vehicle), in which the combustion engine was used as a range extender. The measurements of the exhaust emissions were performed for CO₂/fuel consumption, CO, THC and NO_x. The RDE measurements were performed including the engine operating parameters and emissions analysis. This analysis shows that the engines of BEVs and PHEVs operate in a different parameter range when under actual operating conditions, which directly translates into the exhaust emission values. This is particularly the case for the emission of NO_x. The investigations were carried out for two routes differentiated by the length and share of the urban and extra-urban cycles. For both routes, the emission of THC and CO were lower for the PHEV engine – HC by 69% (22 mg/km, route 1) and 6% (15 mg/km, route 2), CO by 69% (0.12 mg/km, route 1) and 80% (0.1 mg/km, route 2). For route 1, characterized by a greater share of the urban cycle, the emission of NO_x was lower by 70% (2 mg/km) for the BEV engine, and (route 2) lower by 60% (8 mg/km) for the PHEV engine. Additionally, the curves of the exhaust emissions in time for individual exhaust components have been presented that indicate that in the motorway cycle the emission of THC and CO from the BEV vehicle increases significantly up to ten times compared to urban cycle.     

Role of the Railways in the Future of Air Transport

Abstract

The role of the railways in the air transport industry is usually limited to provision of access to airports. However, the development of high-speed rail networks and the congestion and environmental problems faced by the air transport industry suggest the railways could have a greater role in working with the airlines to provide an integrated transport service for medium-distance journeys (up to 800 km). Many air journeys involve two flights and a transfer at a hub airport. The alternative being investigated here would replace air journeys by a rail journey and a flight, and a transfer between them at the hub airport. Such integration could offer a positive alternative to aircraft on some routes and lead to railway journeys to airports becoming part of air transport services, and not only to provide access to them. Integration could therefore provide a better use of available air capacity rather than duplicating some high-speed rail routes and services.