Role of user's socio-economic and travel characteristics in mode choice between city bus and informal transit services: Lessons from household surveys in Visakhapatnam,India

Informally operated paratransit or Intermediate Public Transport (IPT) systems provide demand responsive transit in many developing countries, often competing with formal public transport systems. Literature on the relative user characteristics of the two modes and their choice behaviour between the systems is limited. This article addresses the gap by presenting a methodology to derive a comprehensive understanding of socio-economic and travel demand characteristics of all transit users in a city. The household survey based data collection and analysis framework is demonstrated for the case of Visakhapatnam, a medium sized Indian city. The variables impacting users' choice between the formal and informal modes were derived through binary logistic regression. It was observed that gender, income and travel time have a significant influence on users' choice between the modes, with waiting time having the maximum impact on mode choice. Therefore, the high frequency services offered by paratransit attract users making shorter trips.     

Anticipating long-distance travel shifts due to self-driving vehicles

Increasing population and travel demand has prompted new efforts to model travel demand across the United States. One such model is rJourney that estimates travel demand among thousands of regions and models mode and destination choice. rJourney includes records representing 1.17 billion long-distance trips throughout the year 2010. Although inter-regional impacts caused by an increase of automated vehicles (AVs) has been investigated, there is little research on inter-regional travel and how longer distance destination and mode choices will change. Because of conveniences offered by AVs, the value of travel time of drivers is expected to fall, thus reducing the generalized cost of AV travel. To initially analyze the impacts of AVs in the United States, a new AV mode was added to a subset of the rJourney mode and destination choice models. With an initial scenario assuming an operating cost of AVs that is 118% of traditional cars, two outcomes are observed that are solely based on model results. First, the attractiveness of AVs severely digs into the airline travel market, reducing airline revenues to 53%. Second, the introduction of AVs results in a shift of destination choice, increasing travel in further distances for personal vehicles, but favoring closer distances across all modes, for an overall 6.7% decline in US passenger-miles traveled on existing long-distance trips. While this preliminary research has revealed an initial perspective on how an existing model can support AVs, the increasing availability of data as AVs emerge will refine nationwide long-distance modeling.     

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.     

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.     

Optimizing the benefits of urban road user charging

Traffic congestion is a feature of most modern cities but attempts to control it or limit its effects have met with only modest success. There is significant and continuing interest in the concept of charging city vehicle users, although apart from the use of parking charges actual operational schemes are few and far between. In this paper, we compare three alternative charging policies using a simplified model of travel demand and supply, which we combine with cost benefit techniques. The charging policies are area-based charging in which users pay to locate in or enter an area, terminal-charging based on supplementary parking fees in residential and non-residential locations and distance-based charging which is a charge related to how far users travel. The model allows for behavioural effects resulting from trip diversion and demand suppression, as well as capacity restraint (speed-flow feedback effects based on limited route capacity). In the case study, we parameterize the model using data and geographical dimensions based on London. We show that area based charging delivers the least benefits whilst a hybrid policy based on terminal and distance-based charges delivers the most. Because it is of topical interest, we compare our results and predictions with the Mayor's strategy for London, which is an area-based scheme. We conclude that the revenue generated using a hybrid policy would be as great as for an area based scheme whilst at the same time delivering substantially greater benefits to road users in terms of travel time and other savings.     

Built environment effects on leisure travel for children: Trip generation and travel mode

This study empirically analyzed the effects of built environment on leisure travel among children. Students of three elementary schools, namely Yangmingshan, Sanyu and Shilin, all located in the Shilin District of Taipei, were chosen to provide sample data. The negative binomial regression model and multinomial logit model were used to analyze trip generation and travel mode, respectively. This study reached the following empirical findings: (1) mixed land use, employment density, walkway quality, leisure facility supply and leisure travel distance encouraged generation of leisure trips for children; (2) intersection density, building density, employment density and walkway quality encouraged a child to use transit systems or non-motorized travel modes for leisure travel; and (3) vehicle density and leisure travel distance discouraged walking and biking but encouraged the use of transit systems for leisure travel involving children. Local government can use the empirical findings of this study to develop urban planning strategies to encourage children to perform leisure activities outside the home using transit systems or non-motorized travel modes.     

The effect of travel cost on frequencies of shopping and recreational trips in Sweden

This article focus on how the cost of travel affects travel behavior. A trip frequency model for recreational and shopping trips is suggested and used to investigate this. The data that is used comes from a Swedish travel habit survey where the respondents’ trip frequencies of both types of trips on a certain day are recorded. This is likely to introduce a correlation structure, which is incorporated in the model. Special attention is paid to the effect of travel cost on trip frequencies for different regions and income groups. As a measure of the sensitivity of cost changes, elasticity of demand is calculated. The precision of the elasticities are evaluated with simulated p-values.     

The path and time efficiency of residents' trips of different purposes with different travel modes: An empirical study in Guangzhou,China

Improving residents' travel efficiency and reducing carbon emissions from travel are the key issues for sustainable development of urban transportation. This study first employed a circuity index to measure the path efficiency of residents' trips based on 2015 survey data in Guangzhou and developed a generalized additive model (GAM) to investigate the relationship between the path efficiency and travel distance for different purposes of trip and different travel modes. On this basis, it further evaluated the time efficiency of different travel modes for each trip. The results showed that there is a complex and nonlinear relationship between the path efficiency and travel distance, which differs between different purposes of trips and different travel modes. In general, trips by non-motorized transport have a lower circuity index and higher path efficiency than those by cars or public transport. Moreover, non-motorized transport is the time-efficiency optimal mode for almost half of the trips, especially for daily shopping trips. However, people prefer to choose public transport on their trips even though public transport is not the time-efficiency optimal mode for these trips. Generally, only about half of the residents chose the time-efficiency optimal mode for their trips. Those who did not choose the time-efficiency optimal mode tended to choose the modes with higher carbon-intensity. The conclusions of this study indicate that for improving travel efficiency and reducing carbon emissions from transport, more efforts should be focused on the non-motorized travel environment and developing relevant policies to encourage more walking and cycling.     

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.     

A dynamic carsharing decision support system

This paper proposes a dynamic optimization–simulation model as a decision support system for one-way carsharing organizations. To reduce the vehicle imbalance in one-way systems, a Vehicle Relocation Optimization model is solved successively in a discrete event simulation. Each event is the arrival of a new user. The model is compared to an a priori benchmark model. Autoshare is chosen as a case study. Results show that increasing the reservation time (time between requesting and picking up a vehicle) from 0 to 30 min reduces fleet size by 86%. The model captures a tradeoff between vehicle relocation hours and fleet size.     

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.     

Examining the impact of weather variability on non-commuters’ daily activity–travel patterns in different regions of Sweden

By jointly modelling the routine and leisure activity–travel engagements of non-commuters in different regions of Sweden, this paper explores the interactions between time allocation, travel demand and mode choice under different weather conditions. Combined weather and travel survey datasets that span a period of over 13 years were analysed. Simultaneous Tobit models were applied to explore the interactions among these activity–travel indicators, whilst municipalities’ unique conditions and heterogeneities between different time-points were taken into account. The model results reveal the trade-offs between routine and leisure activities in terms of activity duration, number of trips and travel time. Positive mutual endogeneity was found between slow-mode share in routine and leisure trips. The results also highlight the trade-offs between routine and leisure activities under abnormal weather conditions. Regional differences between weather effects are substantial due to differences in direct, indirect and total marginal effects. Between-municipality variability constitutes a considerable part of the variability in activity duration and travel time. Between-municipality variability in leisure activity duration and leisure travel time is larger in northern Sweden, while that of routine activity duration and routine travel time is larger in central Sweden, after weather and social demographics have been controlled.     

Exploring tertiary students' travel mode choices in Auckland: Insights and policy implications

It is crucial that policymakers and public transport operators comprehend tertiary students' travel mode choices and understand the factors that inform these choices in order to manage travel demands effectively and to optimise the use of public transport and improve its quality of service, particularly during the peak hours. This study aims to examine tertiary students' travel mode choices in Auckland, which is recognised as one of the most car-dependent cities in the world. The city is struggling with traffic congestion, particularly around its Central Business District (CBD) during peak hours. Auckland is New Zealand's largest city, with a population of 1.4 million residents. The main campuses of two major public universities, The University of Auckland (UoA) and Auckland University of Technology (AUT), are located in the CBD, attracting a large number of daily trips by both staff and students, particularly during the teaching semesters. However, there is a limited understanding of tertiary students' travel mode choices, particularly the factors that inform these choices when they travel to the universities' city campuses. A mixed methodology approach was used to comprehend the travel mode choices of students attending The University of Auckland and to identify the key factors that are drivers of these choices. The data collection included a questionnaire-based survey, which received 249 responses, and 10 semi-structured interviews with students. Thematic analysis was utilised to codify and then analyse the interviews. Despite the significant car dependency in Auckland, the survey demonstrated that most respondents utilised public transport and active modes when commuting to the university's city campus. Seven factors were identified that inform tertiary students' travel mode choices: cost, parking availability and cost, access to a car, travel time, physical environment, reliability, and attitudinal variables. The interviewees mostly argued that travel cost and lack of or limited access to a private car were the primary drivers of their travel mode choices. The study suggests that different stakeholders, such as Auckland Transport (AT) and The University of Auckland, should work collaboratively to provide an inclusive travel demand management policy. The university could rearrange classes for off-peak hours, and AT could offer tertiary students further discounts during these hours. These actions would result in the optimisation of public transport efficiency, improvement of the quality of the public transport service, and mitigation of traffic congestion around Auckland's Central Business District (CBD).     

Local distribution and collection for environmental and social sustainability – tricycles in central Beijing

Goods distribution is a growing proportion of intra-urban transport worldwide due to changes in supply chains and e-commerce, yet has received scant attention in research. Cities have opted for a regulatory approach to truck movement and deliveries at a local level but few have tried to develop a systematic approach to management. Following certain suggestions in the literature, a hierarchical deliveries approach is being adopted in some new developments in Europe and Australia using light vehicles at the local level. In East, South and South-East Asia, where 3-wheeled non-motorised vehicles have been a mainstay of goods and people transport for several decades, they are under renewed pressure from city governments. This study of the tricycle in Beijing examines their role for packages delivery, food and beverage distribution and waste and recycling services, which covers nearly all of the uses of utilitarian tricycles in northern Chinese cities. Drivers (n = 97) were interviewed, their usual trips were mapped, and the subsequent trip was recorded using a geo-positioning system. These trips were compared with trips executed by small, motorised vans, favoured since 2014 by Beijing government. Operations can be divided into four categories according to delivery chain organisation, field operations and vehicle type. Motorised alternatives to the tricycle are shown to be uncompetitive in terms of time, cost and energy efficiency. This first detailed examination of the operations of the tricycle in a Chinese city provides a useful base for consideration of local distribution services organisation and a possible model for cities outside China.     

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.     

The indirect effect of the built environment on travel mode choice: A focus on recent movers

Many studies have demonstrated that the built environment has a strong impact on people's travel mode choice. However, the built environment also influences elements such as travel distance and car ownership, which might be the true predictors of which travel modes are chosen. In this study, we analyse the effects of changes in residential neighbourhood on changes in travel mode (for commute trips and leisure trips), both directly and indirectly through changes in car ownership, travel distances and travel attitudes. This study applies a structural equation modelling approach using quasi-longitudinal data from 1650 recently relocated residents in the city of Ghent, Belgium. Results indicate that the built environment has strong direct effects on active leisure trips and car use. However, distance (for car use) and attitudes (for active travel) were found to be important mediating variables. In sum, the effect of the built environment on travel mode choice might be more complex than commonly assumed as it partly seems mediated by travel distance and travel attitudes.     

Time use, travel behavior, and the rural-urban continuum: results from the Halifax STAR project

This paper considers variations in time-related aspects of travel behavior along the urban-rural continuum, using the four categories of inner city, suburbs, inner commuter belt (ICB), and outer commuter belt (OCB). It employs geo-coded and GPS-validated data from the STAR survey conducted in the county-sized regional municipality of Halifax, Nova Scotia. Many significant inter-zonal differences are identified, and most travel variables are characterized by progressive urban-to-rural gradients, with large differences between inner-city and outer-commuter values. A clear break between city and country is seldom evident, however. Inner-city residents make most trips, but have trips of shortest duration, and spend least time in travel. Residents of the commuter belts spend most time in travel, and have trips of longest duration. While long trips and much driving were expected in commuter zones, there are significantly fewer trips in the OCB, which we attribute to lack of need, lack of opportunities, and adjustments in discretionary behavior.     

Dynamic analysis of air travel demand in competitive island markets

This paper describes a dynamic demand model, referred to as dynamic abstract mode model, for estimating both the short- and long-term responses of air passengers to changes in relative air-sea travel cost components in competitive markets. The implementation of the model in the competitive market of Aegean islands in Greece demonstrates the importance of considering the past volumes of air passengers and relative travel cost components to explain current air travel demand.     

Changes in car and bus usage amid the COVID-19 pandemic: Relationship with land use and land price

This study aimed to explore the impacts of COVID-19 on car and bus usage and their relationships with land use and land price. Large-scale trip data of car and bus usage in Daejeon, South Korea, were tested. We made a trip-chain-level data set to analyze travel behavior based on activity-based travel volumes. Hexagonal cells were used to capture geographical explanatory variables, and a mixed-effect regression model was adopted to determine the impacts of COVID-19. The modeling outcomes demonstrated behavioral differences associated with using cars and buses amid the pandemic. People responded to the pandemic by reducing their trips more intensively during the daytime and weekends. Moreover, they avoided crowded or shared spaces by reducing bus trips and trips toward commercial areas. In terms of social equity, trips of people living in wealthier areas decreased more than those of people living in lower-priced areas, especially trips by buses. The findings contribute to the previous literature by adding a fundamental reference for the different impacts of pandemics on two universal transportation modes.     

Time-use data, analysis and modeling: toward the next generation of transportation planning methodologies

This paper argues that transportation planning methodologies must be built on the central thesis of the activity-based approach to travel demand modeling, namely, that travel is a derived demand that reflects people's desire and need to participate in activities. The paper discusses why this foundation for transportation planning methodologies is necessary to address contemporary planning and policy analysis issues. The paper also argues that the introduction of time-use data, analysis and modeling is a key element in the development of the next generation of transportation planning methodologies. Following a brief review of time-use studies, the paper discusses a number of planning and policy analysis areas in which time-use data will be of particular value, including the evaluation of induced or suppressed travel demand. The concepts advanced in the paper are illustrated with two brief numerical examples. These examples show how model systems based on time-use data can be used to (i) estimate the number of induced trips that would result from a reduction in commute travel time, and (ii) evaluate the impacts of alternative transportation improvement projects.