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.     

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.     

Extreme weather,public transport ridership and moderating effect of bus stop shelters

This paper examines how extreme weather conditions influence urban public transport ridership with a particular focus on the role of bus stop shelters. Using bus ridership data from the Salt Lake City metropolitan area, we find that extreme weather such as very high and low temperatures, and heavy rainfall reduces public transport ridership, while bus stop shelters have a modest effect on mitigating ridership losses resulting from these adverse weather conditions. The moderating effect of shelters is more pronounced on weekdays, and for bus stops with lower service frequency and fewer transfers. Our research also shows that the installation of bus shelters correlates with a variety of factors including service frequency, land use types, and local socioeconomic and demographic characteristics. Overall, our findings suggest that public transport amenities with weather-proof attributes have the potential to retain and attract more ridership on extreme weather days.     

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.     

Bus rapid transit as a neoliberal contradiction

Bus Rapid Transit (BRT) is being implemented as a neoliberal project, but it creates contradictions that challenge the premise of neoliberalism. BRT projects are affordable rapid transit infrastructure, but they are also an impetus to restructure the urban bus sector in developing cities with informal mass transport. The dominant model of BRT implementation creates a market for bus service from large private companies where the government takes on the risk and brands the service as part of the city's attempt to be a ‘world class’ city that can attract mobile capital. However, BRT and the formalization of the bus sector can increase the power of urban residents by firmly putting transport in the public sphere; workers by increasing the incentives for collective action; and bus riders by prioritizing space for buses over cars. But these are only openings that require action to take advantage of the contradictions.     

Impact of bus rapid transit on housing price and accessibility changes in Sydney: A repeat sales approach

ABSTRACT

New public transport infrastructure is expected to improve accessibility for local residents, and thus contribute to increased land value. The contribution that a bus rapid transit (BRT) system can make to increased land value is less certain than for rail-based systems, with the literature mostly containing bus-based examples from developing countries with extensive BRT networks. This article considers a BRT system named the Liverpool–Parramatta Transitway (LPT) that was implemented in southwestern Sydney in 2003 to improve public transport accessibility in the local area. A repeat sales model is constructed to investigate the impact of the LPT on residential housing prices and accessibility changes using repeat sales data from before and after the opening of the LPT. This identified little price difference between properties close to LPT stations and outside of the area that could be considered as affected by the LPT service coverage. This outcome is at variance with the theoretical underpinning of land value uplift and other empirical evidence relating to the LPT. Hedonic models using the same repeat sales data investigate the study area in more detail, stratifying the sample by housing type and by comparing separate before and after models. These research outcomes identify the extent to which the BRT system has an impact on local housing prices through accessibility improvements to the study area and provide a deeper understanding as to how the quantification of land value uplift from BRT represents one element of the wider economic benefits of a BRT system.     

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.     

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.     

Identifying resident preferences for bus-based and rail-based investments as a complementary buy in perspective to inform project planning prioritisation

Much of the debate associated with the development of new public transport infrastructure appears to have an emotional bias with communities in favour of one mode, especially rail. This, in turn, carries much sway at the political level as if there is no budget constraint or consideration of value for money and coverage. This paper presents a stated choice experiment to investigate this context as two unlabelled options described by 20 potential drivers of community preferences for improved public transport. Each choice scenario is conditioned on a given route length but with different costs, reflecting different modal investment options for the same route length. To establish whether a modal bias exists within and between geographical jurisdictions, the choice scenario is followed by a labelling of each investment option to reveal whether the option is bus rapid transit (BRT) or light rail transit (LRT). Data from all eight capital cities of Australia, collected in mid-2014, form the empirical setting. Mixed logit random regret models provide new evidence on the nature and extent of community modal bias in this choice setting. The paper also proposes a complementary tool to benefit-cost analysis that uses the residence preferences model to show, through scenario analysis, the potential gains in public support for BRT over LRT. The results suggest that BRT should be in the mix of candidate projects if more than one mode is considered and not ignored, as is so often the case in developed economies.     

Modeling aggregate air-travel itinerary shares: logit model development at a major US airline

This study reports the results of aggregate air-travel itinerary share models estimated at the city-pair level for all city-pairs in the US. These models determine the factors that influence airline ridership at the itinerary level and support carrier decision-making. The models are estimated using aggregate multinomial logit methodology and use comprehensive data. Independent variables for the models measure various itinerary service characteristics: level-of-service, connection quality, carrier, carrier market presence, fares, aircraft size and type, and time of day. The results are intuitive, and validation tests indicate that the models outperform existing methods. Finally, the impacts of changing various itinerary service attributes on carrier market share are discussed.     

Electrification of a city bus network—An optimization model for cost-effective placing of charging infrastructure and battery sizing of fast-charging electric bus systems

The deployment of battery-powered electric bus systems within the public transportation sector plays an important role in increasing energy efficiency and abating emissions. Rising attention is given to bus systems using fast charging technology. This concept requires a comprehensive infrastructure to equip bus routes with charging stations. The combination of charging infrastructure and bus batteries needs a reliable energy supply to maintain a stable bus operation even under demanding conditions. An efficient layout of the charging infrastructure and an appropriate dimensioning of battery capacity are crucial to minimize the total cost of ownership and to enable an energetically feasible bus operation. In this work, the central issue of jointly optimizing the charging infrastructure and battery capacity is described by a capacitated set covering problem. A mixed-integer linear optimization model is developed to determine the minimum number and location of required charging stations for a bus network as well as the adequate battery capacity for each bus line. The bus energy consumption for each route segment is determined based on individual route, bus type, traffic, and other information. Different scenarios are examined in order to assess the influence of charging power, climate, and changing operating conditions. The findings reveal significant differences in terms of required infrastructure. Moreover, the results highlight a trade-off between battery capacity and charging infrastructure under different operational and infrastructure conditions. This paper addresses upcoming challenges for transport authorities during the electrification process of the bus fleets and sharpens the focus on infrastructural issues related to the fast charging concept.     

Analysis on bike-share ridership for origin-destination pairs: Effects of public transit route characteristics and land-use patterns

Studies on bike-share programs have dramatically increased during the past decades. While numerous studies have examined various factors affecting bike-share demand at the station-level, few attempts have been made to understand bike-share ridership at the origin-destination (OD) level due to technical difficulties. The objective of this study is to examine whether existing public transit characteristics affect bike-share ridership at OD-level. We combined three datasets: (1) bike-share ridership data, (2) land-use and bike-transit infrastructure, and (3) bike-transit route characteristics between OD pairs of bike stations. Zero-inflated negative binomial (ZINB) regression models were used for the analysis. Our results showed that the travel distance between OD bike stations, land-use compositions, and the existence of bike-friendly infrastructures were significant factors determining bike-share ridership at the OD-level. In particular, a longer duration of public transit trips than bike-share, and more transit transfers, were associated with bike-share ridership. Further, this study showed that bike-share and public transit might compete with or promote each other, even within the city. The study's findings suggest that the relative efficiency of bike-share compared to public transit is highly associated with bike-share demand and help to increase the utility of bike-share system in response to several limitations of existing public transit networks.     

Network–wide prediction of public transportation ridership using spatio–temporal link–level information

Public transportation is a key element to vivid city life. Understanding the dynamics and driving forces of public transportation ridership can be a very rewarding task. It is, however, a highly complex construct. In this research, we focus on a spatial viewpoint, which has seen little attention: the link level. It represents the trip of a vehicle between directly connected stations. Additionally, we put emphasis on the impact of exogenous events. In order to assess their spatio–temporal influences, a temporal resolution of 30 min complements the spatial link level. Ridership data for trams and buses is provided by Stadtwerke München (SWM), which is the operator of the public transportation network in Munich, Germany, including 82 bus and 17 tram lines. About 30% of trams and 50% of buses are equipped with automatic passenger counting sensors, which capture boarding and alighting at each individual station. The equipped vehicles are strategically placed by SWM to obtain a meaningful view on the whole system. The raw sensor data is cleaned and sanitized. The data we are using spans a 4–year period (2014–2017). Following a pre–processing step, ∼59.79% of the data is considered, which equates to ∼97 million observations. There are 693 tram links and 2944 bus links, which makes 3637 links in total. We distinguish the analysis in ridership prediction and inference. For prediction, we specify one model functional form and build this model for each link, using 5–fold cross–validation to avoid overfitting. We employ decision trees, combining them with bagging and boosting. We then perform inference, i.e. attempt to understand the relationship between the variables that emerged in the predictive models. Ridership is assessed for each link separately and visualized together in order to construct network views and maps. Conclusions are drawn, and recommendations for future research are formulated.     

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.     

Sustainable public transport systems: Moving towards a value for money and network-based approach and away from blind commitment

Growing public transport patronage in the presence of a strong demand for car ownership and use remains a high agenda challenge for many developed and developing economies. While some countries are losing public transport modal share, other nations are gearing up for a loss, as the wealth profile makes the car a more affordable means of transport as well as conferring elements of status and imagery of “success”. Some countries however have begun successfully to reverse the decline in market share, primarily through infrastructure-based investment in bus systems, commonly referred to as bus rapid transit (BRT). BRT gives affordable public transport greater visibility and independence from other modes of transport, enabling it to deliver levels of service that compete sufficiently well with the car to attract and retain a market segmented clientele. BRT is growing in popularity throughout the world, notably in Asia, Europe and South America, in contrast to other forms of mass transit (such as light and heavy rail). This is in large measure due to its value for money, service capacity, affordability, relative flexibility, and network coverage. This paper takes stock of its performance and success as an attractive system supporting the ideals of sustainable transport.     

Bus rapid transit impacts on land uses and land values in Seoul,Korea

Bus rapid transit (BRT) has gained popularity as a cost-effective alternative to urban rail investments; however, relatively little is known about its impacts on land-use changes and land values. This paper examines the land-market effects of converting regular bus operations to median-lane bus services in Seoul, Korea, one of the densest, most congested cities in the world. Multilevel models reveal BRT improvements prompted property owners to convert single-family residences to higher density apartments and condominiums. Land price premiums of up to 10% were estimated for residences within 300 m of BRT stops and more than 25% for retail and other non-residential uses over a smaller impact zone of 150 m. The research findings underscore the importance of introducing zoning and other land regulatory changes prior to the initiation of BRT improvements as well as applying value-capture tools to help finance investments and redress inequities.     

Transit ridership estimation with network Kriging: a case study of Second Avenue Subway,NYC

An attractive topic in transportation practice is transit ridership estimation. Reliable estimates are beneficial to spatial structuring, facility design, and vehicle operation, as well as financial and labor management. Traditional ridership estimation approaches mainly rely on regression models that consider subway fares, population, and employment distribution in surrounding areas. Yet consideration of ridership’s spatial dependency is largely lacking in these models. This paper recognizes the spatial effect by estimating the ridership of the new Second Avenue Subway in New York City using a network Kriging method. Network distance, instead of Euclidean distance, is used to reflect the fact that subway stations are only connected by subway tunnels. Results show that the new service should effectively relieve the traffic burden on other currently crowded subway lines.     

Residential property value impacts of proximity to transport infrastructure: An investigation of bus rapid transit and heavy rail networks in Brisbane,Australia

Public transport investment is normally targeted at increasing accessibility which land rent theory identifies and will in turn increase land values. There is a clear policy interest in how much land values increase following a new transport investment so as to establish if there is sufficient land value uplift to capture and to help pay or contribute to investment plans. Identifying an uplift for residential land has been well studied in the context of new light rail systems and bus rapid transit (BRT) systems in developing countries but there is little evidence for BRT in developed countries.This paper has two objectives. First, to examine long term impact of BRT in a developed world context in Brisbane, Australia. Brisbane's BRT uses an open system design which contrasts with the closed system design of the successful BRT systems in South America and elsewhere, including the BRT in the suburbs of Sydney, Australia. Second, BRT in Brisbane was introduced to a network already dominated by a radial heavy rail network and this investigation recognises that the uplift from BRT introduction may therefore be different to a BRT in a single mode city. A third motivation is to consider the spatial distribution of uplift which is an essential pre-requisite to understanding the distributional impact if uplift is used to contribute to infrastructure provision.Spatial modelling is used to examine the accessibility impacts of the BRT at a global level. This is followed by Geographical Weighted Regression, used to examine the spatial distribution of accessibility using a local model.The results show that there is greater uplift in Brisbane, as compared to that identified by studies of Sydney's BRT which is likely due to the greater network coverage of BRT in Brisbane and less strong competition of rail. Land value uplift is also spatially distributed over the network giving higher uplift in some areas than others and lower values than typically found with rail based systems in developed countries. However, the degree of uplift is relatively low, with proximity to BRT stations attracting more uplift than proximity to train stations.     

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.