Examining the influence of stop level infrastructure and built environment on bus ridership in Montreal

We studied transit ridership from the perspective of the transit provider, with the objective of quantifying the influence of transit system operational attributes, transportation system infrastructure attributes and built environment attributes on the disaggregate stop level boardings and alightings by time of day for the bus transit system in the Montreal region. A Composite Marginal Likelihood (CML) based ordered response probit (ORP) model, that simultaneously allows us to incorporate the influence of exogenous variables and potential correlations between boardings and alightings across multiple time periods of the day is employed. Our results indicate that headway affects ridership negatively, while the presence of public transportation around the stop has a positive and significant effect. Moreover, parks, commercial enterprises, and residential area, amongst others, have various effects across the day on boardings and alightings at bus stops. An elasticity analysis provides useful insights. Specifically, we observe that the most effective way to increase ridership is to increase public transport service and accessibility, whereas enhancements to land use have a smaller effect on ridership. The framework from our analysis provides transit agencies a mechanism to study the influence of transit accessibility, transit connectivity, transit schedule alterations (to increase/reduce headway), and land-use pattern changes on ridership.     

Understanding bus rapid transit route ridership drivers: An empirical study of Australian BRT systems

Bus Rapid Transit (BRT) systems are an increasingly popular public transport option internationally. They provide rail-like quality for bus services for a fraction of the cost of fixed rail. Many claims of high and increasing ridership have resulted from BRT system development; however, it is unclear exactly which aspects of BRT system design drive this. This paper explores whether BRT design features, among other influences, significantly increase ridership above and beyond the impact of service levels. It does so using a series of regression models undertaken on 77 BRT and non-BRT bus routes in Australia which is known for its diversity in BRT route design. Explanatory variables used included service level, frequency, speed, stop spacing, share of segregated right of way, vehicle accessibility, employment and residential density, car ownership levels and BRT infrastructure quality. Five models explored the role of these variables. Two models found that service level dominates predictions of boardings per route km although they suffer from endogeneity. Further models control for this influence by modelling boardings per vehicle km. Overall results suggest that some BRT infrastructure treatments such as right of way have a significant impact on ridership but the influence of infrastructure is within the context of high service levels. The role of accessible vehicles has also been highlighted in this research, although more research is needed to clarify this influence. The paper concludes with a discussion of the various influences on ridership and recommendations for existing policy and future research.     

The demand for reliable transit service: New evidence using stop level data from the Los Angeles Metro bus system

This study explores the role of service reliability in determining bus transit ridership. Using stop level service supply, demand, and performance data from the Los Angeles Metro bus system, I investigate whether reliability of a directional line serving a stop influences the number of passengers boarding the line at that stop, controlling for various other established factors affecting demand. This cross-sectional analysis of the variation in line boardings across about 1300 sample schedule time point bus stops served by about 300 directional bus lines over a six-month period uses a historical archive of real-time geo-referenced vehicle location data, and focuses on five different time periods, peaks and off-peaks, of a typical weekday. By evaluating two measures that capture different dimensions of bus service reliability, and by estimating a series of regression models, I find systematic evidence that higher average service punctuality (or schedule adherence) and lower variation in schedule deviation over time are associated with greater ridership, all else equal, particularly during the peak periods. This study also provides first empirical evidence that the effect of reliability on peak-period ridership is moderated by headway. The demand for reliability seems to be higher for lines with relatively longer headways. The findings indicate that service reliability influences transit mode choice and/or line/route selection, and suggest that system-wide ridership gains can be expected from reliability improvements. From an urban planning perspective, this study provides more evidence that good service quality can effectively compliment transformations in the urban fabric brought about by coordinated land use — transit plans to promote transit use.     

The interplay between dockless bikeshare and bus for small-size cities in the US: A case study of Ithaca

As another mode of shared transportation, bikeshare can substitute or complement public transit. Prior studies mainly relied on self-reported survey data or aggregated station-level data from docked bikeshare systems, and their conclusions and implications were focused on large cities. It is largely unknown how and to what extent a dockless bikeshare system complements or substitutes public transit, especially in small cities. This study was set to measure the interplay between Lime dockless bikeshare and bus service in Ithaca, NY – a typical small-size college town – and its environs. By joining about 3.42 million records of bus stop data and 102 thousand Lime bikeshare trip data from 2019, two types of Bikeshare-Bus-Linkage (BBL) trips were identified, namely (1) the first-mile trip where a user rides a Lime to board a bus, and (2) the last-mile trip where a user bikes to their destination after alighting a bus. BBL trips were identified using a spatiotemporal proximity framework based on two important parameters: the catchment radius and the time window between a bus stop event and a Lime trip. Different values were tested with a sensitivity analysis, and the parameters were finally set at 100 ft. and 5 min. As such, 3026 BBL trips were identified, which was 3% of total Lime ridership or 0.1% of total bus ridership. Our findings indicated that Lime provided useful first- and last-mile transfers to bus service for commuters. The complementary effect was particularly strong in the urban core and with transit development and employment land use areas. Moreover, in the morning peak, there were more first-mile trips from residential areas to bus stops in the urban core, while in the evening peak more last-mile trips started from bus stops in the urban core to residential areas. Based on the unique first-mile and last-mile trip patterns identified, policy implications and recommendations for bikeshare operators, local government, transit agencies, and transportation policymakers were discussed to better integrate bikeshare and public transit.     

Improving Bus Service Levels and social equity through bus frequency modelling

Bus lines play an essential role in providing urban public transport service. Demographic and socioeconomic characteristics determine the specific transport service needs of districts that, in most cases, are not served by the existing bus routes. Small changes in the frequency of a bus route can have a direct effect on the territorial distribution of a city's public transport service. Adjusting the frequencies of a bus fleet can help planners improve the service level and adapt the fleet's spatial distribution. A bus frequency optimization methodology is proposed to improve harmonization between service level and social equity in public transport. The method relies on a simple spreadsheet that integrates geographic data about bus routes and socioeconomic information about city districts. Simulation and optimization procedures are coordinated to appropriately adjust the routes to the geographic space. The proposed method is tested in a real case study that demonstrates its usefulness in analysing the service level and equity of a transport system and improving a city's public transport planning.     

‘Mobility work’: Older adults' experiences using public transportation

This paper contributes to research on public transport accessibility, disabling spaces, and older adult's mobility by highlighting the ‘mobility work’ older adults complete to meet their daily travel needs. Drawing on a systematic and inductive analysis of semi-structured interviews with older adult (65+ years of age) public transit users in Hamilton, Canada, we argue that older adults are faced with mobility work that younger and/or more able-bodied people do not routinely encounter as they meet (or attempt to meet) their daily travel needs using public transportation. Key components of older adults' trips that involve mobility work include walking to and from the bus stop, trip planning, stepping onto/ off of the bus, finding a seat, carrying items on the bus, calling a stop, and travelling in winter conditions. This mobility work can be categorized as physical (e.g., struggling to board the bus), emotional (e.g., worrying about getting a seat), or spatiotemporal (e.g., staying home when the weather is bad). Taken together, this paper puts forward a multidimensional concept of ‘mobility work’ to aid in considering accessibility at the scale of both the individual and the built environment. Further, by highlighting mobility work, this paper demonstrates the ways in which public transport spaces can be disabling for aging bodies and outlines concrete measures public transit agencies can take to make services more accessible to older adult riders.     

Evaluating the relationship between socially (dis)advantaged neighbourhoods and customer satisfaction of bus service in London,U.K.

Affordable and efficient urban public transport is important for the development of a sustainable urban environment. Making sure public transport users are satisfied with the service is a goal many public transport agencies are trying to achieve. Customer satisfaction surveys are often used to monitor customer perceptions of service quality and to determine the relative influence of service attributes on a customer's overall assessment of the service. This study presents a new method to spatially evaluate customer satisfaction survey data through examining satisfaction with bus service across neighbourhoods of varying levels of socio-economic status (SES). Using customer satisfaction survey data collected by Transport for London between 2010 and 2015, multi-level regression modeling is used to estimate the relationship between overall satisfaction and social deprivation of the area in which bus routes were operating. The results indicate lower levels of satisfaction along routes serving low SES neighbourhoods, which appears to be attributed to (1) low satisfaction with service characteristics related to an individual's experience and quality of the bus and (2) conditions of the bus stop and shelter. Findings from this paper shows the importance of including cleanliness and bus internal quality as one of the performance indicators when contracting bus services, to ensure that all customers receive the same quality of service in the region regardless of their SES.     

Improving bus service quality and information in Winchester

This paper reports the results of a package of measures, contained within a quality bus partnership (QBP), designed to improve bus service quality and information on three city centre routes in Winchester, including the Park and Ride (P&R) service. These measures were implemented by Hampshire County Council, Stagecoach Bus Company and Winchester City Council as part of the EU sponsored MIRACLES project, which ran from 2002 to 2006 and whose aims included reducing the environmental impacts of transport at the local level while increasing urban accessibility.These measures included the introduction of new buses, increasing the frequency of one of the main city centre bus routes, new bus infrastructure such as new shelters and poles, physical improvements to the bus/rail interchange and the printing of pocket travel maps. In addition, one of the P&R car parks was extended so that the capacity of the scheme was doubled. The objectives of this work package were to contribute to an 8% increase in bus patronage and the satisfaction rating of bus passengers on the QBP routes as well as integrating public transport services more effectively within Winchester.A review was carried out of bus travel and users’ needs, quality bus partnerships, bus-based P&R schemes and the importance of frequency of service to increasing patronage.In order to evaluate the effects of these measures, data were collected from the bus operator Stagecoach regarding patronage, reliability and the average age of the fleet. In addition, two bus questionnaire surveys were carried out to assess passenger's views to changes made to these three city centre bus services. An evaluation of the QBP routes was made to see how quickly investments made in purchasing the new buses and extending the P&R car park would be recovered. Conclusions and recommendations have been made with regard to the effectiveness of the changes made to the three bus city centre services as well as their cost effectiveness.     

The spatial characteristics and influencing factors of modal accessibility gaps: A case study for Guangzhou,China

This paper presents an analysis of the spatial characteristic of the modal accessibility gap (MAG) in Guangzhou based on travel times for public transport and cars to public centers calculated by the Travel O-D point Intelligent Query System (TIQS). Four spatial regression models are used to investigate the effect on the MAG of six factors of the built environment (distance to city public centers, residential density, landuse mix, bus stop density, metro station density and road network density). The results show that travel time for a given origin to destination (OD) trip is likely to be larger by public transport than by car, especially for a trip of longer travel time. The MAG values of all the communities are larger than 0, indicating that when compared with public transport, travelling by car takes less travel time for individuals. Residential density, land-use mix, bus stop density and metro rail station density have significant negative direct impacts and indirect impacts (spatial spillover effects) on MAG, which indicates that appropriate increase in community residential density, providing diversified service facilities within a community, and improving public transport supply are beneficial to promote modal shift. Specifically, the role of metro rail is greater than that of buses. However, the road network density has significant direct positive impacts on MAG, and its spillover effect is also significantly positive, which indicates that building more roads is not an effective way to narrow the accessibility gap between public transport and cars but may facilitate more car travel instead.     

Modelling and analysing effects of complex seasonality and weather on an area's daily transit ridership rate

Adverse weather is generally perceived as deterrent for public transit uses. This has also been highlighted in previous literatures. In contrary, our previous study found no association between weather and transit ridership while investigating the underlying temporal influences behind variation in daily ridership across the sub-tropical city of Brisbane, Australia. This contraindication led to the primary focus of this research. This research acknowledged that Inclusion of weather variables in conjunction with other relatively strong independent variables might result in washout of the weather effects on ridership. Variables such as rainfall do not recur on a daily basis throughout the year. Thus, generalising their effect on ridership with other independent variables that consistently influence ridership may create a similar problem. Hence, weather variables were converted into their normalised factors and combined with other independent variables while formulated the optimised the daily ridership rate estimation model. Several models were developed concerning various combinations of weather variables and through rigorous analysis it was identified that only the rain variable has noticeable effect on daily ridership. Evidently, this study functions as an update of our former study by directing towards a new approach to the analysis of the relationship between weather and transit ridership.     

Understanding the effects of complex seasonality on suburban daily transit ridership

Fluctuations in transit ridership pattern over the year have always concerned transport planners, operators and researchers. Predominantly, metrological elements have been specified to explain variability in ridership volume. However, the outcome of this research points to new direction to explain ridership fluctuation in Brisbane. It explored the relationship between daily bus ridership, seasonality and weather variables for a one-year period, 2012. Rather than segregating the entire year’s ridership into the four calendar seasons (summer, autumn, spring, and winter), this analysis distributed the yearly ridership into nine complex seasonality blocks. These represent calendar season, school/university (academic) period and their corresponding holidays, as well as other observant holidays such as Christmas. The dominance of complex seasonality over typical calendar season was established through analysis and using Multiple Linear Regression (MLR). This research identified a very strong association between complex seasonality and bus ridership. Furthermore, an expectation that Brisbane’s subtropical summer is unfavourable to transit usage was not supported by the findings of this study. A nil association of precipitation and temperature was observed in this region. Finally, this research developed a ridership estimation model, capable of predicting daily ridership within very limited error range. Following the application of this developed model, the estimated annual time series data of each suburb was analysed using Fourier Transformation to appreciate whether any cyclical effects remained, compared with the original data.     

Analysing the spatial-temporal characteristics of bus travel demand using the heat map

As the basic travel service for urban transit, bus services carry the majority of urban passengers. The characterisation of urban residents' transit trips can provide a first-hand reference for the evaluation, management and planning of public transport. Over the past two decades, data from smart cards have become a new source of travel survey data, providing more comprehensive spatial-temporal information about urban public transport trips. In this paper, a multi-step methodology for mining smart card data is developed to analyse the spatial-temporal characteristics of bus travel demand. Using the bus network in Guangzhou, China, as a case study, a smart card dataset is first processed to quantitatively estimate the travel demand at the bus stop level. The term ‘bus service coverage’ is introduced to map the bus travel demand from bus stops to regions. This dataset is used to create heat maps that visualise the regional distribution of bus travel demand. To identify the distribution patterns of bus travel demand, two-dimensional principal component analysis and principal component analysis are applied to extract the features of the heat maps, and the Gaussian mixture model is used for the feature clustering. The proposed methodology visually reveals the spatial-temporal patterns of bus travel demand and provides a practical set of visual analytics for transit trip characterisation.     

Addressing transit mode location bias in built environment-transit mode use research

Many studies have identified links between the built environment (BE) and transit use. However, little is known about whether the BE predictors of bus, train, tram and other transit modes are different. Studies to date typically analyze modes in combination; or analyze one mode at a time. A major barrier to comparing BE impacts on modes is the difference in the types of locations that tend to be serviced by each mode. A method is needed to account for this ‘mode location bias’ in order to draw robust comparison of the predictors of each mode.This study addresses this gap using data from Melbourne, Australia where three types of public transport modes (train, tram, bus) operate in tandem. Two approaches are applied to mitigate mode location bias: a) Co-located sampling – estimating ridership of different modes that are located in the same place; and b) Stratified BE sampling – observations are sampled from subcategories with similar BE characteristics.Regression analyses using both methods show that the BE variables impacting ridership vary by mode. Results from both samples suggest there are two common BE factors between tram and train, and between tram and bus; and three common BE factors between train and bus. The remaining BE predictors – three for train and tram and one for bus - are unique to each mode. The study's design makes it possible to confirm this finding is valid irrespective of the type of locations serviced by modes. This suggests planning and forecasting should consider the specific associations of different modes to their surrounding land use to accurately predict and match transit supply and demand. The Stratified sampling approach is recommended for treating location bias in future mode comparison, because it explains more ridership variability and offers a transferrable approach to generating representative samples.     

The relationship between recent gasoline price fluctuations and transit ridership in major US cities

The unprecedented increase in gasoline costs between August 2005 and July 2008 has become a major public issue in the US. Of the contentions and potential solutions surrounding higher gasoline costs, one receiving relatively little attention has been the role of public transit. This research examines that question by analyzing the relationship between gasoline prices and transit ridership from January 2002 to April 2008 in nine major US cities. Regression analysis is used to assess the degree to which variability in rail and bus transit ridership is attributable to gasoline costs and fluctuations in gasoline cost, controlling for service changes, seasonality, and inherent trending. The results indicate that a small but statistically significant amount of ridership fluctuation is due to changes in gasoline prices. The results are discussed in light of the policy and practical implications of higher gasoline prices for mass transit and the potential for long term changes in US travel behavior.     

Selecting tram links for priority treatments - The Lorenz Curve approach

Road and public transport authorities often have a difficult task in deciding which road links to select for investment in preferential traffic and public transport measures to improve public transport service performance. This paper presents a new approach which adopts the economic concept of the Lorenz Curve to compare link performance in terms of transit operations as well as weighted passenger volume of travel. The paper explores if, and how, these metrics can be re-interpreted to help with targeting improvements for on-road public transport and priority mitigations. The approach collates operational performance data, in this case link speed and also link public transport travel volume to plot the cumulative distribution of link speed/ridership performance as a curve. Two sets of test applications are presented; on a route level basis and secondly a network level analysis. The network level results present the most powerful results with the Lorenz Curve analysis able to quickly identify links that justify greater attention for preferential treatments since they have the worst 20th percentile of operational performance but the highest 40th percentile of relative link ridership. Mapping shows the problem links to be busy routes leading into the central city. Implications for wider application of these methods are discussed.     

Verkehrsverbund: the success of regional public transport in Germany, Austria and Switzerland

The Verkehrsverbund system of public transport organization offers a practical solution to the problem of providing integrated regional public transport service for the increasingly suburbanized metropolitan areas of Europe and North America. By carefully coordinating fares and services for all routes, all types of public transport, and all parts of the metropolitan region, Verkehrsverbund systems in Germany, Austria, and Switzerland have greatly improved the quality of the public transport alternative to the automobile. Five Verbund systems were chosen for detailed analysis: Hamburg, Munich, the Rhein-Ruhr region, Vienna and Zurich. This article documents the success of each Verbund in attracting more public transport riders and, in most cases, increasing or at least stabilizing public transport's share of modal split. It also analyzes the reasons for the success of the Verkehrsverbund, including service expansion, improvement in service quality, more attractive fares, and extensive marketing campaigns. The five case study systems offer lessons for other public transport systems facing similar challenges of dealing with increasing auto ownership and suburbanization. The article concludes with an analysis of the most challenging problem of all: public transport finance. As shown dramatically by the five case studies, the service improvements and fare structures needed for truly effective regional public transport require substantial government subsidy. Fiscal austerity at every government level is leading to subsidy cutbacks in most countries of Europe and North America. The five case study systems examined in this article provide lessons on how to deal most effectively with limited subsidy funds in order to minimize service deterioration, fare increases and ridership losses.     

Modelling user perception of bus transit quality

This article evaluates how bus users perceive the quality of their public transport service. In particular it looks at how perception of quality varies according to the available information. The experiment compares an overall evaluation of service quality before and after making passengers reflect on the importance of certain fundamental system variables which they may not have previously considered.Focus groups were used to individualise the most relevant variables. A quality survey was carried out both on-board buses and at bus stops and the overall service quality was related to the aforementioned variables using ordered probit models. The perception of quality is shown to change with the category of user and that there tends to be more criticism towards variations in overall quality until the users are stimulated into thinking more deeply about other influential variables. The application of this methodology may provide operating companies with valuable information for planning marketing policies aimed at different categories of user, in order to improve the service quality and attract more passengers to using public transport.     

Influence of the built environment on E-scooter sharing ridership: A tale of five cities

Electric scooter (e-scooter) sharing systems (ESSs) have been widely adopted by many cities around the world and have attracted a growing number of users. Although some studies have explored the usage characteristics and effects of the built environment on ESS ridership using one city as an example, few studies have considered multiple cities to obtain generalizable and robust results. To fill this research gap, we collect the ESS trip data of five cities in the U.S., namely Austin, Minneapolis, Kansas City, Louisville, and Portland, and explore the effects of the built environment on ESS ridership after controlling for socioeconomic factors. The temporal distributions of e-scooter ridership of different cities are similar, having a single peak period on weekdays and weekends between 11:30 and 17:30. In terms of spatial distribution, the ESS ridership is higher in universities and urban centers compared to other areas. Multilevel negative binomial model results show that ESS trips are positively correlated with population density, employment density, intersection density, land use mixed entropy, and bus stop density in the census block group. E-scooter ridership is negatively correlated with the median age of the population in the census block group and distance to the city center. The findings in this article can help operators understand the factors that affect the ridership of shared e-scooters, determine the changes in ridership when the built environment changes, and identify high-ridership areas when ESS is implemented in new cities.     

Exploring the impacts of land use by service coverage and station-level accessibility on rail transit ridership

In this study, we employ spatial regression analysis to empirically investigate the impacts of land use, rail service coverage, and rail station accessibility on rail transit ridership in the city of Seoul and the surrounding metropolitan region. Our analyses suggest that a rail transit service coverage boundary of 500 m provides the best fit for estimating rail transit ridership levels. With regard to land use, our results confirm that density is positively related to rail transit ridership within a 750 m radius of each station. In contrast, land use diversity is not associated with rail transit ridership. We also found that station-level accessibility is as important as land use for explaining rail transit ridership levels. Finally, we conclude that development density and station-level accessibility measures such as the number of station entrances or exits and the number of bus routes at the station are the most important and consistent factors for promoting rail transit ridership.     

Exploring the spatial variations of transfer distances between dockless bike-sharing systems and metros

Dockless bike-sharing is emerging as a convenient transfer mode for metros. The riding distances of bike-sharing to or from metro stations are defined as transfer distances between dockless bike-sharing systems and metros, which determine the service coverages of metro stations. However, the transfer distances have rarely been studied and they may vary from station to station. Therefore, this study aims to explore the influencing factors and spatial variations of transfer distances between dockless bike-sharing systems and metros. First, a catchment method was proposed to identify bike-sharing transfer trips. Then, the Mobike trip data, metro smartcard data, and built environment data in Shanghai were utilized to calculate the transfer distances and travel-related and built environment variables. Next, a multicollinearity test, stepwise regression, and spatial autocorrelation test were conducted to select the best explanatory variables. Finally, a geographically weighted regression model was adopted to examine the spatially varying relationships between the 85th percentile transfer distances and selected explanatory variables at different metro stations. The results show that the transfer distances are correlated with the daily metro ridership, daily bike-sharing ridership, population density, parking lot density, footway density, percentage of tourism attraction, distance from CBD, and bus stop density around metro stations. Besides, the effects of the explanatory variables on transfer distances vary across space. Generally, most variables have greater effects on transfer distances in the city suburbs. This study can help governments and operators expand the service coverage of metro stations and facilitate the integration of dockless bike-sharing and metros.