Investigating users' travel behaviours and perceptions of single-corridor BRT: Lessons from Lahore

Despite the global popularity of bus rapid transit (BRT) in last couple of decades, there is limited empirical evidence in the rapidly urbanizing developing countries regarding corridor-wide users' typical travel characteristics and perceptions of the system attributes. The factors affecting BRT users' (dis)satisfaction are also often disregarded, given less priority than needed, or delayed till issues become more difficult and costlier to manage. Although on a rise, currently only ~10% of BRT systems worldwide are in lower-middle-income and low-income countries, which also supports the need to effectively address BRT passengers' mobility issues in such countries with cramped resources, contributing towards more sustainable urban mass transit systems. As major share of BRTs worldwide are single-corridors (~63%), this study investigates the above stated gaps using case of such BRT in the megacity of Lahore, Pakistan via on-site structured interview surveys using intercept method from BRT users along all stations of the corridor. Typical travel characteristics, correlations and cross-comparisons of sample demographics with mobility attributes, underlying (dis)similar themed factors ensuring internal consistency, and rankings of (dis)satisfactions regarding service attributes were evaluated using combination of statistical methods. Visual comparisons of factors in 2D and 3D rotated space were also explored. Results revealed differences in travel characteristics of BRT users for various demographics; convergence of eight factors from twenty-two service quality attributes; spectrum of highest, average and lowest ranked attributes; and inter-spatial relationship of service quality attributes based on the factors contributing relatively more variation. The overarching findings provide useful insights for transportation practitioners, policy makers and could also contribute towards updating BRT guidelines by incorporating the needs and requirements of BRT users in the developing countries.     

Measuring individuals' travel behaviour by use of a GPS-based smartphone application in Dar es Salaam,Tanzania

A range of mega-cities in the Global South have started to invest in Bus Rapid Transit (BRT) systems, as a complement or replacement for informal paratransit services, in an effort to improve the mobility and accessibility in the city. Yet, few studies have tried to analyse the impact of such systems on the mobility patterns of cities' residents, in part because traditional travel diary surveys are often too expensive to conduct and unsuitable to capture spatial mobility patterns in fast growing cities with a high level of informality in spatial development. In this study, we analyse the applicability of a new method of data collection, i.e. a GPS-based smartphone application, to capture individuals travel behaviour in fast growing mega-cities in the Global South. Our case study is the city of Dar es Salaam (DES) in Tanzania, where the first BRT line is currently being implemented. In our study, the GPS-based app was used by individuals in DES to record distances, departure times and destinations of their trips. Socio-demographic data of respondents were recorded in short questionnaires. The spatial distribution of the trip patterns shows the mobility demand in both high and less connected areas. The results reveal a variation in departure times, travel destinations and trip distances that are one the one hand spatially limited within neighbourhoods and away from the planned BRT, and on the other hand along major roads connecting to the Central Business District (CBD). The short average distances of the trips (<3 km) reveal the characteristics of paratransit modes. The GPS-based smartphone application provides an opportunity to policy makers to engage deeply with the spatial reality of local communities, as a basis for transport investments and policy improvements as steps towards an integrated public transport system.     

Predicting transit mode choice of New Jersey workers commuting to New York City from a stated preference survey

This study examines transit mode choice preferences of New Jersey commuters traveling to New York City (NYC) with the objective of assisting trans-Hudson ferry service planning on the basis of variables significantly affecting mode choice. A stated preference survey was conducted to collect data from a total of 2134 respondents who commute from northern New Jersey to NYC. A mixed multinomial logit model (MMLM) with random coefficients was used to analyze the data. The study considered the choice between four transit modes—ferry, PATH train, bus, and commuter rail—all of which can be used to cross the Hudson River to travel from New Jersey to NYC. Essential model results are presented for all four modes, but detailed results are discussed for only the ferry, PATH, and bus modes. Model results indicate that commuters' choices are affected not only by travel time and cost for the segment of the journey that crosses the Hudson River, but also reliability and comfort during that segment, number of access modes required by the journey, and travel time and cost of trips from home to stations/terminals before crossing the river. The results also show that commuters' attachment to the modes they currently use serves as a barrier to switching to other modes. The most important takeaway from this research for transit service planning is that there is a need to consider the attributes of both individual trip segments as well as entire journeys between commuters' home and work when exploring changes to transit service characteristics.     

Effects of parking and cordon charge policies on tourist's modal shift in central business district of Mashhad city,Iran

The second largest holy city of the world, Mashhad, attracts high volumes of tourists and pilgrims every year. Most visitors travel by private car and are a source of considerable funds for the local economy. Among road users, tourists as one of the major traveller categories in Mashhad city behave differently due to the particular trip purpose. The aim of this research is to model tourist's shifting modes of travel behaviour when policy measures, such as the parking and cordon fares, are implemented. The tourists’ preferences were examined using binary logit analysis when different options of travel cost and time scenarios were provided. Results indicate that travel time, parking cost, cordon cost, education level and vehicle price influence tourist's modal choice. In addition, the finding shows that congestion pricing will be more effective than a parking pricing strategy in encouraging switching of modes.     

Dependence between travel distance,individual socioeconomic and health-related characteristics,and the choice of the travel mode: a cross-sectional study for Kaunas,Lithuania

The aim of this study was to analyse the associations between individual socioeconomic and health-related characteristics, travel distance, and the choice of different travel modes in urban population. A cross-sectional study included 932 adults of Kaunas city, Lithuania. The choice of the travel mode and individual characteristics were self-reported by the participants, and their travel routes were calculated using the geographic information system. Multivariate logistic regression was used to assess the most significant factors determining the choice of a car, cycling, walking, or public transport. In total, 529 participants reported using a car, of whom 65.8% had medium or high education levels. These participants were more likely to be younger, male, married, and employed. Among bicycle users, statistically significant differences between the employment status, body mass index, and travel distance were observed. Walkers were significantly more likely to be older, those with lower incomes, unemployed, and travelling the shortest distances. The analysis of the travel distance on the choice of the travel mode revealed that men travelled longer distances with a car compared to women. The employment status was significantly associated with travel distance by car or public transport. Employed individuals travelled longer distances by public transport or by car, compared to unemployed individuals. Among bicycle users, we found that people with higher levels of education and overweight individuals cycled the longest distances. Our study emphasizes the importance of considering different individual characteristics when analysing the choice of transport modes. It provides evidence that is relevant for all urban populations on the choice of the transport mode, particularly considering active versus passive transport.     

Comparing paratransit in seven major African cities: An accessibility and network analysis

Accessibility to transit, together with other important system characteristics such as network coverage and frequency, is a crucial driver of modal choice for urban commuting. In turn, commuting is a major driver of energy consumption and of socio-environmental externalities in cities. So far, few quantitative and comparative assessments of paratransit in cities of Africa have been carried out due to data scarcity and the prevalence of informal services. Here we leverage the recent release of General Transit Feed Specification (GTFS) data to produce comparative metrics of accessibility, network, and service quality of paratransit in seven major cities in sub-Saharan Africa (Abidjan, Accra, Addis Ababa, Freetown, Harare, Kampala, Nairobi). Our results allow for a first-order assessment and comparison of different crucial paratransit characteristics in these cities, shedding light on transport inequality and urban segregation dynamics. The analysis and metrics produced can support transport systems planners in major cities of low-income countries. Further research should focus on approaches for overcoming the residual data limitations and expand the quantitative understanding of paratransit.     

Accessibility across transport modes and residential developments in Nairobi

A key goal of urban transportation planning is to provide people with access to a greater number of opportunities for interaction with people and places. Measures of accessibility are gaining attention globally for use in planning, yet few studies measure accessibility in cities in low-income countries, and even fewer incorporate semi-formal bus systems, also called paratransit. Drawing on rich datasets available for Nairobi, Kenya this analysis quantifies place-based accessibility for walking, paratransit, and driving using three different measures: a mobility measure quantifying how many other locations in Nairobi can be reached in 60 min, a contour measure quantifying the number of health facilities that can be reached in 60 min, and a gravity measure quantifying the number of health facilities weighted by a time-decay function. Health facilities are used because they are an essential service that people need physical access to and as a representation of the spatial distribution of activities more broadly. The findings show that place-based accessibility is highest for driving, then paratransit, then walking, and that there are high levels of access to health facilities near the Central Business District (CBD) for all modes. Additionally, paratransit accessibility is comparatively better in the contour and gravity measures, which may mean that paratransit is efficiently providing access based on the spatial distribution of services. The contour measure results are also compared across different residential levels, which are grouped based on neighborhood characteristics and ordered by income. Counterintuitively, the wealthiest areas have very low levels of place-based accessibility for all modes, while poor areas have comparatively better walking access to health facilities. Interestingly, the medium low residential level, characterized in part by tenement apartment buildings, has significantly higher accessibility than other residential types. One way to reduce inequality in access across income groups is to increase spatial accessibility for the modes used by low- and middle-income households, for example with policies that prioritize public transport and non-motorized travel, integrate paratransit with land use development, and provide safe, efficient, and affordable options.     

Extending public transit accessibility models to recognise transfer location

A longstanding issue for public transit agencies has been how to assess the performance of transit service including spatial service coverage to meet the transport needs of the community. The conventional approach quantifies accessibility using door-to-door travel time in such a way that accessibility declines as the travel time to the opportunity increases. A new approach to modelling transit accessibility is proposed by incorporating the potential effect of transfer location. It builds on the premise that transit users may have a preference for a transfer location best located relative to the trip origin and destination points. The model is tested in Brisbane's bus network which has a radial form, where inner-city suburbs have relatively higher accessibility than outer-city suburbs, if only travel time is counted. Incorporating the transfer location refines the accessibility modelling so that some outer-city suburbs located along the major bus corridors have a relatively higher accessibility level. The new model also suggests that inner-city suburbs do not necessarily have better accessibility. Suburbs close to the city centre may have shorter transit travel time to reach other suburbs, but they do not have a well-connected transit network to other suburbs through service transfers.     

Representing pedestrian activity in travel demand models: Framework and application

There have long been calls for better pedestrian planning tools within travel demand models, as they have been slow to incorporate the large body of research connecting the built environment and walking behaviors. Most regional travel demand forecasting performed in practice in the US uses four-step travel demand models, despite advances in the development and implementation of activity-based travel demand models. This paper introduces a framework that facilitates the abilities of four-step regional travel models to better represent walking activity, allowing metropolitan planning organizations (MPOs) to implement these advances with minimal changes to existing modeling systems. Specifically, the framework first changes the spatial unit from transportation analysis zones (TAZs) to a finer-grained geography better suited to modeling pedestrian trips. The MPO's existing trip generation models are applied at this spatial unit for all trips. Then, a walk mode choice model is used to identify the subset of all trips made by walking. Trips by other modes are aggregated to the TAZ level and proceed through the remaining steps in the MPO's four-step model. The walk trips are distributed to destinations using a choice modeling approach, thus identifying pedestrian trip origins and destinations. In this paper, a proof-of-concept application is included to demonstrate the framework in successful operation using data from the Portland, Oregon, region. Opportunities for future work include more research on the potential routes between origins and destinations for walk trips, application of the framework in another region, and developing ways the research could be implemented in activity-based modeling systems.     

Insights into carsharing demand dynamics: Outputs of an agent-based model application to Lisbon,Portugal

Two important claims for carsharing systems are their increased flexibility and potential contribution to reducing transport externalities such as pollution. Carsharing typically involves a fleet of vehicles in stations around a city that clients may use on an hourly-payment basis. Classical round-trip systems address a niche market of shopping and errand trips. However, a growing market is now arising providing one-way trips to clients. Great uncertainty remains on the economic viability of this type of carsharing given the complex relation between supply and demand, and how this may influence the level of service provided. Realistic modeling tools that include both supply and demand characterization and allow testing several carsharing operational parameters are scarce. In this sense, a detailed agent-based model was developed to simulate one-way carsharing systems. The simulation incorporates a stochastic demand model discretized in time and space and a detailed environment characterization with realistic travel times. The operation includes maintenance operations, relocations and reservations. The model was applied to the case-study city of Lisbon. Our results show that comparing to other modes, carsharing performs worse than private cars both in terms of time and cost. Nevertheless, it clearly outperforms taxis in terms of cost, and outperforms buses, metro and walking in terms of travel time. The competitiveness of carsharing is highly determined by trip length, becoming more competitive than other modes (travel-time wise) as trips become longer. The operational policies as car-fleet relocation and car reservation showed significant effects in enhancing profit while preserving good customers' satisfaction.     

What drives sustainable student travel? Mode choice determinants in the Greater Toronto Area

Examination of mode choice behavior is an important step in accurately predicting future travel demand. Despite having somewhat unique travel needs and challenges, there is a lack of knowledge in understanding the mode use behavior of university student population. The existing studies on university populations relied on a relatively smaller sample in investigating the behavior. Therefore, using world's largest university student's travel database, this study examines the factors affecting the mode choice behavior of a diverse university student population with student samples from four universities and their seven campuses located across the Greater Toronto Area (GTA) in Canada. Additionally, stratifying this diverse population using their attitudinal responses towards numerous travel modes, this study also estimates three additional mode choice models to obtain a more comprehensive understanding of how students in different markets, with different latent attitudes towards transportation, vary in terms of sustainable mode choice. A cluster analysis based on fourteen attitudinal responses, was conducted to stratify the sample whereas the popular multinomial logit approach was used to estimate the mode choice models. This study finds transit pass and bike ownership as important determinants that govern sustainable mode choice among the students in the region. The findings of this study could facilitate the sustainability offices at the four universities in making an informed policy decision in shifting the mode use behavior of students towards sustainable modes.     

Assessing intercity multimodal choice behavior in a Touristy City: A factor analysis

This paper investigates influential factors in passengers' intercity multimodal choice behaviors in a touristy city. By collecting large individual-level data through a comprehensive field survey that was carried out at the major transportation hubs in Xi'an, China, we studied four travel modes of the surveyed travelers in this touristy city, including air, high-speed rail, traditional passenger train, and express bus. For factor analysis, 12 variables, including not only individual-related attributes but also ticketing methods and mental perceptions, were used as the independent factors after the correlation analysis and collinearity test. The regression relationships between the travel mode choice and the independent variables were studied using Bayesian multinomial logistic regression. The results indicate that those 12 factors have significant and various influences on passengers' mode choices. In particular, travel distance, fare rate, intercity travel time per hundred kilometers, quality of service, accessibility of transportation hubs, and ticketing methods have influential contributions for explaining the choice decision-makings. The findings demystify the effects of several unexplored factors in intercity multimodal travel choice behaviors and shed new light on formulating traffic management strategies for service providers and decision-makers in practice.     

Analysis of travel mode choice and trip chain pattern relationships based on multi-day GPS data: A case study in Shanghai,China

As the propensity to link multiple intermediate stops in a trip chain (a sequence of journeys that starts and ends at home, includes visiting one or more locations) is more prevalent, the relationship between travel mode choice and trip chain pattern aroused the attention of academics. This paper examines two distinct structures to identify the decision process of travelers between travel mode choice and trip chain pattern: one structure in which trip chain pattern organization precedes travel mode choice, another structure in which travel mode choice decision precedes the organization of trip chain pattern. To accommodate multi-day behavioral variability and unobserved heterogeneity in personal characteristics ignored by traditional travel surveys, multi-day GPS data collected in Shanghai is employed to estimate these two structures within Nested Logit (NL) model. The Monte Carlo (MC) method simulates the switch of trip-chaining and mode choice under possible Transportation Demand Management (TDM) strategies based on estimation results. The findings of this study are as follows: (1) trip chain pattern decision precedes travel mode choice, which means trip-chaining is organized first and affects travel mode choice; (2) complex trip chain is related to higher automobile dependency, and it is a barrier to the tendency to adopt public transit; (3) people who generally travel by automobiles might switch to public transit when private cars are unavailable, and an increase in household bicycle ownership enhances competition between the bicycle and public transit which leads people to turn to cycling. These findings help implement TDM strategies to develop sustainable transportation systems and optimize the urban trip structure.     

Built for active travel? Investigating the contextual effects of the built environment on transportation mode choice

The study investigates the role of the built environment attributes and their contextual effects on travel behaviour. The study utilized a dataset of 4739 respondents elicited from an online survey distributed in Hamilton City, Canada. A Nested Logit (NL) model and a quadratic polynomial trend surface are employed to spatially investigate the determinants influencing mode choice behaviour. The study contributes to our understanding of how geography moderates the impact of built environment attributes on mode choice behaviour. Socioeconomic demographics are found to play a pivotal role in explaining Hamiltonians' mode choice behaviour. For built environment attributes, sidewalk density is positively associated with walking and public transit use. Moreover, bike lane density is positively associated with biking and negatively associated with public transit use. Regarding land-use entropy (mix), the results show that high land-use entropy is negatively associated with choosing the car as a passenger travel mode. From a contextual perspective, the results affirmed that the influence of built environment attributes is not equally efficacious across the city. Improving the built environment attributes across the city reveals a substantial increase in walking and biking while decreasing the probability of choosing other modes. However, it is noteworthy to mention that the influence of improving the built environment is not homogeneous over geography.     

Multi-city exploration of built environment and transit mode use: Comparison of Melbourne,Amsterdam and Boston

The built environment is an important determinant of travel demand and mode choice. Establishing the relationship between the built environment and transit use using direct models can help planners predict the impact of neighborhood-level changes, that are otherwise overlooked. However, limited research has compared the impacts of the built environment for different networks and for individual transit modes.This paper addresses this gap by developing built environment and transit use models for three multimodal networks, Amsterdam, Boston and Melbourne, using a consistent methodology. A sample of train, tram and bus sites with similar station-area built environments are selected and tested to establish if impacts differ by mode. It is the first study that develops neighborhood-level indicators for multiple locations using a consistent approach.This study compares results for ordinary least squares regression and two-stage least squares (2SLS) regression to examine the impact of transit supply endogeneity on results. Instrumented values are derived for bus and tram frequency in Melbourne and bus frequency in Boston. For other mode and city combinations, the 2SLS approach is less effective at removing endogeneity.Results confirm that different associations exist between the built environment and transit modes, after accounting for mode location bias, and that this is true in multiple networks. Local access and pedestrian connectivity are more important for bus use than other modes. Tram is related to commercial density. This finding is consistent for all samples. Land use mix and bicycle connectivity also tend to be associated with higher tram use. Train use is highest where opportunities exist to transfer with bus. Population density is commonly linked to ridership, but its significance varies by mode and network.More research is needed to understand the behavioral factors driving modal differences to help planners target interventions that result in optimal integration of land use with transit modes.     

The equity impacts of bus rapid transit: A review of the evidence and implications for sustainable transport

The paper offers an analysis of empirical evidence on the equity impacts of operational Bus Rapid Transit (BRT) systems in the Global South. The focus is on vertical equity, i.e. whether BRT systems achieve progressive benefits for poorer segments of the population. Findings from Africa, Asia, and Latin America all suggest that BRT does offer significant benefits to low-income groups, in terms of travel time and cost savings, access enhancement, and safety and health benefits. However benefits are often skewed toward medium-income users and thus less progressive than they might be. Two primary reasons for this are insufficient spatial coverage and inappropriate fare policies. While many features of BRT potentially allow it to deliver pro-poor outcomes, such outcomes only materialize if BRT implementers pay specific and sustained attention to equity. The paper identifies key issues that need to be addressed to steer BRT implementation toward more socially sustainable outcomes—including better integration with other transit, paratransit, and nonmotorized transport services, and with the housing sector.     

Operationalization of path walkability for sustainable transportation

Most walking travel behavior research thus far has tested area-based neighborhood walkability, which is measured with meso-level urban form attributes. In need of micro-level walkability analyses that focus on individual travelers and their routes, we propose a route-oriented linear walkability concept named “path walkability.” It is defined and measured by 42 path walkability indicators that can collectively represent an individual traveler's micro-level walkability. A graphic measurement instrument for an objective and efficient on-field walkability measurement is developed. This study also sets the protocol for quantitatively integrating the walkability data measured at the segment level into path walkability indicators that are comparable at the route level. To test the applicability of the proposed path walkability, a pilot case study is conducted within a station area. A user survey is administered to collect transit users' access mode choices and walking routes to the station. The survey results help identify two groups of street segments: one used by regular walkers and the other selected by habitual auto users/occasional walkers. The routes chosen by the two groups are quantitatively and graphically compared for walkability. The analyses show a physically measurable and quantitatively comparable difference between the routes' walkability and suggest criteria for walking-conducive transit walkability for station users. Specific design recommendations for improving street-level micro-walkability for future transit-oriented developments (TODs) are added along with a future research agenda.     

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.     

Public bicycle as a feeder mode to rail transit in China: The role of gender,age, income,trip purpose,and bicycle theft experience

A marriage between public bicycle and rail transit presents new opportunities for sustainable transportation in Chinese cities. To examine determinants of public bicycle usage for rail transit access, an intercept survey of feeder mode choice among rail transit users was conducted near rail stations in Nanjing, China. Mode choice models were estimated with five feeder mode alternatives, including car, bus, walk, private bike, and public bike. By differentiating between public and private bicycle modes in the mode choice models, the study reveals the effects of personal demographics, trip characteristics, and station environments on public bicycle usage for rail transit access. Results show that female, older, and low-income rail commuters are less likely to use public bicycle to access rail transit. Rail commuters with bicycle theft experience and making school- or work-related trips are more likely to use public bicycle to access rail transit. Land use variables are largely insignificant in this study except that density shows a positive relationship with walking to rail transit. The results on demographic differences raise equity concerns when it comes to investing in public bicycle systems. Policy implications are discussed for Chinese cities to equitably boost public bicycle integration with rail transit.     

Errors in variables in multinomial choice modeling: A simulation study applied to a multinomial logit model of travel mode choice

Modeling travel demand is a vital part of transportation planning and management. Level of service (LOS) attributes representing the performance of transportation system and characteristics of travelers including their households are major factors determining the travel demand. Information on actual choice and characteristics of travelers is obtained from a travel survey at an individual level. Since accurate measurement of LOS attributes such as travel time and cost components for different travel modes at an individual level is critical, they are normally obtained from network models. The network-based LOS attributes introduce measurement errors to individual trips thereby causing errors in variables problem in a disaggregate model of travel demand. This paper investigates the possible structure and magnitude of biases introduced to the coefficients of a multinomial logit model of travel mode choice due to random measurement errors in two variables, namely, access/egress time for public transport and walking and cycling distance to work. A model was set up that satisfies the standard assumptions of a multinomial logit model. This model was estimated on a data set from a travel survey on the assumption of correctly measured variables. Subsequently random measurement errors were introduced and the mean values of the parameters from 200 estimations were presented and compared with the original estimates. The key finding in this paper is that errors in variables result in biased parameter estimates of a multinomial logit model and consequently leading to poor policy decisions if the models having biased parameters are applied in policy and planning purposes. In addition, the paper discusses some potential remedial measures and identifies research topics that deserve a detailed investigation to overcome the problem. The paper therefore significantly contributes to bridge the gap between theory and practice in transport.