Experience conditioning in commuter modal choice modelling – Does it make a difference?

This paper investigates the impact of decision maker’s experience on model elasticities and predicted market share, using data collected in Sydney on commuter mode choice. Usage frequency is used as a proxy for experience and two separate mode choice models are estimated – one with experience conditioning choice and one without. Key model outputs are compared and we find that differences in the value of travel time savings and model elasticities are very marked. This suggests that ignoring experience that one has with each alternative in their choice set may be a candidate source of error in travel demand forecasts. We develop a method to obtain the level of experience for use in application of choice models to increase their prediction power.     

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.     

Toward a spatial understanding of active transportation potential among a university population

Universities and surrounding communities stand to benefit when active travel mode choices are elevated. Despite this, there is little research on travel mode choice at commuter universities and, in particular, the nonlinear spatial relationships among active travel potential and various contextual and compositional factors. The purpose of this study was to examine and visualize linkages among personal, household, density, diversity, and design factors, and active travel (bicycling, walking, and mass-transit modes) among a commuter-university population residing throughout southeastern Michigan, USA. This was accomplished by employing exploratory spatial data analysis (ESDA), ordinary least squares (OLS) regression, and a geographically weighted regression (GWR) model. The GWR model outperformed the traditional OLS model in terms of goodness of fit (R² = .534 and R² = .461, respectively). A novel cartographic mapping technique was employed to depict where statistically significant parameter estimates negatively or positively influenced active travel. The main finding was that personal, household, density, diversity, and design estimates varied in both magnitude and spatiality throughout the university's study area. Interestingly, distance was not a universal barrier to active travel potential. These variations emphasize the importance of promoting active transportation through localized interventions as well as coordinating efforts among universities and surrounding communities.     

Do your neighbors affect your bicycling choice? A spatial probit model for bicycling to The Ohio State University

Neighborhood social effects have recently become a focus of interest in transportation research, whereby transportation mode choice is not only affected by an individual’s characteristics and transportation system conditions, but also by the mode choices of that individual’s social neighbors. This study supports the neighborhood social effects argument, using a spatial econometrics approach and data from The Ohio State University (OSU) 2012 Campus Transportation Survey. A spatial probit model of commuters’ mode choices (bicycling versus non-bicycling) is estimated, accounting for spatial autocorrelation. The results show that the more OSU-affiliated bicycle riders are residing around an individual OSU commuter, the more attractive bicycling becomes, controlling for other factors such as gender, status, proximity to campus, bicycle infrastructure and attitudes. The results indicate that students and males are more likely to commute by bicycles. The probability of choosing bicycles decreases with distance from campus. In addition, proximity to bicycle infrastructure and physical environment both encourage respondents to bicycle. Feeling of safety, travel cost and concern for the environment also affect bicycling choice.     

Cycling in multimodal transport behaviours: Exploring modality styles in the Danish population

Multimodality is important for achieving less car dependent lifestyles and more sustainable transport behaviours. It is widely recognised that cycling plays a prominent role in sustainable transport. However, research has largely focused on cycling substituting motorised transport. This study explores how cycling forms part of multimodal transport behaviour based on survey data on transport modes and travel purposes and the weekly frequency of out-of-home activities and travel mode use in a representative sample of adult Danes (n = 1957). The following five distinct multimodal travel segments or ‘modality styles’ are identified: ‘education transport’; ‘public-based transport’; ‘limited transport’; ‘bicycle-based transport’; and ‘car-based transport’. Travel behaviour is predominantly multimodal with few unimodal car-drivers being identified. Substantial cycling takes place in all modality styles, and is embedded in a multimodal behaviour as the modality style combined cycling with several other modes. Furthermore, the study demonstrates that cycling serves many purposes that transgress the division of utility cycling and recreational cycling, and that cycling takes place in both dense urban settings and small towns. Thus, the way in which travel modes relate to the urban environment and variations in modality styles must serve as the starting point for policies aiming to fulfil the potential of multimodal transport behaviour and promote cycling.     

Spatial and socio-demographic determinants of South East Queensland students’ school cycling

The low prevalence of Australian students’ utilitarian school cycling could be attributed to the varied and context specific demographic, socio-economic and spatial school travel mode choice determinants. Travel distance is universally important for school cycling and is reliant amongst related home and school spatial proximity factors on a student’s choice of schools. This paper, primarily based on school students’ travel data extracted from the 2009 South East Queensland Household Travel Survey (SEQHTS), examines comparative school cycling travel patterns, school catchment choices and the significant analytical determinants of cycling mode choices from within an urban regional Australian context. Students’ choice of a school external to that located within their designated State school catchment zone was associated with household attributes of parent/guardian employment location, number of income earners and ownership of private vehicles coupled with State school and catchment attributes. Noteworthy variations in school travel distances and modal splits were allied with school catchment choices. Adolescent male students from two parent households owning fewer than two cars and more than two bicycles, with parents/guardians commuting using non-motorised travel modes and resident in Census Collection Districts with conducive cycling environments, contributed largely to the one-way bi-directional primary and secondary school cycling mode shares. This prevalent student cyclist profile indicates the need for enhancements in student school cycling participation, through policies addressing both the spatial (built) and social environment which impact students’ personal and traffic safety coupled with utilitarian cycling image enhancements. Concerted efforts to bolster cycling amongst student segments with current low cycling participation inclusive of females, students from single parent households and those with adequate access to private motorised travel modes may be necessary to further enhance school cycling mode shares. The paper makes a case for individualised targeted travel interventions informed by segregated mode choice determinant analysis for respective primary and secondary school types and directions of school travel.     

Green commuter plans and the small employer: an investigation into the attitudes and policy of the small employer towards staff travel and green commuter plans

One potential solution to reducing peak hour congestion has been to identify a role for the employer in reducing car-based travel to work and promoting more sustainable alternatives through comprehensive ‘employee travel plans’ (Rye, T., 1995. Employee Transport Plans—An Easy Means to Cut Congestion? The 23rd European Transport Forum, Proceedings of Seminar B, Planning for Sustainability, PTRC, pp. 229–241). In the UK such plans have seen a steady increase in interest since the early 1990s culminating in their recognition in the Department of the Environment, Transport and the Regions DETR, 1998 (DETR, 1998. A New Deal for Transport: Better for Everyone, The Government's White Paper on the Future of Transport, HMSO, London) Transport White Paper as a policy tool for reducing car-based travel. Despite their inclusion as a policy tool little information exists on the views of employers towards such plans (Rye, T., 1995. Employee Transport Plans—An Easy Means to Cut Congestion? The 23rd European Transport Forum, Proceedings of Seminar B, Planning for Sustainability, PTRC, pp. 229–241; Rye, T., MacLeod, M., 1998. An Investigation of Employer Attitudes to Employer Transport Plans, AET European Transport Conference 1998, Policy Planning and Sustainability Seminar (Seminar C), vol. 2, PTRC). This is of considerable concern given that employers by default are the key implementers. Studies to date on employers’ attitudes have concentrated on the views of the large employer (over 100 employees). The Transport White Paper however suggests that there is also a role for the small employer. This paper therefore investigates the attitudes and policy of the small employer (under 100 employees) towards staff travel and green commuter plans. The paper is based on the analysis of data collected in 1998 from 352 small Oxfordshire employers. The research was funded under the DETR's Seedcorn Research Programme. The paper outlines selected findings of this research, and concludes by suggesting that while ultimately there should be a role for the small employer in developing green commuter plans it is the large firms that are more likely to implement green commuter plans in the short term. In policy terms, the continuing focus of green commuter plans on large employers is therefore the best way forward. In the long term however consideration needs to be given to the role that the small employer can play in reducing employee travel.     

Travel behavior of university students who live on campus: A case study of a rural university in Asia

With their irregular class schedules and considerable freedom in the campus environment, university students are an example of a social group that tends to have complex and unique travel behavior. This study examined travel patterns of 130 students who study and live on campus in a rural university of Thailand. All survey participants completed a travel diary for seven consecutive days in a typical school week. Other than overall travel patterns, such as trip generation, mode split, distance traveled, and travel time, this study also investigated the differences in traffic patterns of four student groups, categorized by their gender and whether they own a private vehicle or not. It was found that students of both genders appeared to have similar travel patterns in all aspects. Whether they own a private vehicle does not appear to impact daily trip generation nor the total distance traveled of the students, but it does have an effect on the travel modes used by students. Those students who own a private vehicle mostly rely on driving the vehicle, while those who do not own a vehicle rely on three modes of travel: primarily being a passenger on or in a friend’s private vehicle, and to a lesser extent, driving a friend’s vehicle, and taking a bus (the only form of public transport on the campus). The results indicate a high social interdependency among university students, which makes the development of a model to simulate travel behavior of university students a complicated task.     

The role of schedule delays on passengers’ choice of access modes: A case study of Japan’s international hub airports

We empirically study passenger modal-choice behavior to access an international hub airport, by using stated preference (SP) data and by constructing a binomial logit model. We found that passenger modal choice is affected by the service level of the access modes: travel time, travel cost, waiting time, and delay cost. The results also indicate that if passengers choose access mode in advance they consider service frequency: departure timing from home, and the arrival timing at the airport. Moreover, our results indicate that travelers’ willingness to pay for saving time differs by time of a day. They are apt to pay more in the morning than in the afternoon. These outcomes must contribute to improve the access flight service from local to hub airports to handle the needs of passengers.     

Optimal allocation of protective resources in urban rail transit networks against intentional attacks

This paper advances the field of network interdiction analysis by introducing an application to the urban rail transit network, deploying protective resources against intentional attacks. The resource allocation problem for urban rail transit systems is considered as a game between two players, the attacker interdicting certain rail stations to generate greatest disruption impact and the system defender fortifying the network to maximize the system’s robustness to external interdictions. This paper introduces a game-theoretic approach for enhancing urban transit networks’ robustness to intentional disruptions via optimally allocating protection resources. A tri-level defender–attacker–user game-theoretic model is developed to allocate protective resources among rail stations in the rail transit network. This paper is distinguished with previous studies in that more sophisticated interdiction behaviors by the attacker, such as coordinated attack on multiple locations and various attacking intensities, are specifically considered. Besides, a more complex multi-commodity network flow model is employed to model the commuter travel pattern in the degraded rail network after interdiction. An effective nested variable neighborhood search method is devised to obtain the solution to the game in an efficient manner. A case study based on the Singapore rail transit system and actual travel demand data is finally carried out to assess the protective resources’ effectiveness against intentional attacks.     

An explanation of the relationship between adults’ work trip mode and children’s school trip mode through the Heckman approach

Most studies on children’s travel hypothesize that the characteristics of children, households, schools, and neighborhoods exogenously affect their travel mode to school. This study makes an additional assumption that children’s mode to school and household adults’ travel mode to work are interrelated because of a lifestyle choice made by parents and caregivers. With this assumption, Heckman probit models were used with data from the 2009 US National Household Travel Survey to predict household adults’ travel mode to work and children’s travel mode to school jointly. It found strong evidence that household adults’ decision to drive to work significantly increases the probability of children being dropped off at school and decreases their likelihood of walking and bicycling, but not vice versa. As adults’ mode choice is more fundamental in the household decision-making process, the study suggests that children’s mode choice studies should not ignore how parents or caregivers travel to work.     

Mitigating the impact of errors in travel time reporting on mode choice modelling

Travel time is a major component in understanding travel demand. However, the quantification of demand and forecasting hinges on understanding how travel time is perceived and reported. Travel time reporting is typically subject to errors and this paper focuses on the mitigation of their impact on choice models. The aim is to explain the origin of these errors by including elements of travel behaviour (e.g., activities during the trip), which have been shown to significantly affect mode choices and commuting satisfaction. Based on responses from a revealed preferences survey, we estimate a mode choice model that treats travel time as a latent variable and incorporates different sources of data along with information on travel activities. Employing these multiple – sometimes incongruent – sources of information in the choice model appears to be beneficial. Results from comparing a logit model assuming error-free inputs and the integrated hybrid model revealed significant impacts on the generated policy scenarios. The model results also contributed to identifying the main travel activity features that affect travel time reporting, providing indications that can assist in understanding and mitigating the impact of imprecise measurements.     

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.     

Investigating household vehicle ownership,mode choice and trip sharing decisions using a combined revealed preference/stated preference Nested Logit model: case study in Bangkok Metropolitan Region

This study proposes a Nested Logit model to investigate household travel behaviour in respect to vehicle ownership, mode choice and trip sharing decisions. The model is analysed using revealed preference (RP) and stated preference (SP) data since a combined estimation of RP/SP data is an effective method of expressing complex travel behaviour and forecasting travel demand for new transport services. In the proposed model, the nesting structure has two levels. The upper level shows car ownership, motorcycle ownership, and no vehicle-ownership choices, and the lower level shows the mode choice combinations for two-traveller households. Trip sharing is considered as one of the mode-choice options in the model. The proposed model is analysed using data from the Bangkok Metropolitan Region. The analysis conducted informs that Central Business District (CBD) travel, long distance travel, household income, job status, age of travellers and presence of school children in households are key aspects in household travel decisions. Based on these aspects, households make important decisions on vehicle ownership, mode choice and trip sharing. In addition, this study reveals commuters’ hidden preferences for modes that are not in existence, in particular the Mass Rapid Transit System in the Bangkok Metropolitan Region due to be fully implemented in 2010.     

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.     

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.     

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.     

A model for time of day and mode choice using error components logit

The severity of road congestion not only depends on the relation between traffic volumes and network capacity, but also on the distribution of car traffic among different time periods during the day. A new error components logit model for the joint choice of time of day and mode is presented, estimated on stated preference data for car and train travellers in The Netherlands. The results indicate that time of day choice in The Netherlands is sensitive to changes in peak travel time and cost and that policies that increase these peak attributes will lead to peak spreading.     

Estimation and validation of hybrid choice models to identify the role of perception in the choice to cycle

Cycling is one of the most sustainable and ecofriendly modes of travel and a good form of exercise. Many government and public health authorities recommend cycling to stay fit as well as to reduce air and noise pollution, CO₂ emissions, traffic congestion, and other negative consequences of car use. In light of these benefits, a major challenge for researchers today is how to promote cycling. However, in countries where cycling is not common, apart from the need for proper cycling facilities, one major issue concerns people’s perception of cycling for sport or recreational activities rather than as a mode of transport. The aim of this paper is to explore the role of perception in the likelihood of the bike being used for utilitarian purposes. We focus on the perception of: the bicycle as a means of transport; bikeability (in terms of usefulness and safety) and of bike infrastructure. Hybrid Choice Models (HCMs) have been used to estimate the effect of people’s perception on the propensity to bike. The HCM also accounts for the serial correlation between error terms in the discrete and latent perceptions, to allow for agent-common unknown factors. Furthermore, we also validate the model results using a hold-out sample and discuss some policy measures aimed at changing travel behavior. The results suggest that, besides individual characteristics, latent aspects related to the perception of the context and of the bicycle as a means of transport strongly affect the propensity to cycle.     

Does bicycle network level of traffic stress (LTS) explain bicycle travel behavior? Mixed results from an Oregon case study

This paper draws on census data, mode choice, and regional household travel survey data to investigate the relationship between the varying levels of traffic stress (LTS) routes and bicycle travel behavior. Specifically, does bicycle level of traffic stress explain bicycle behavior enough to warrant its use given the limitations? Bicycle level of traffic stress is a new system of bicycle infrastructure classification for cities that cannot afford existing alternatives such as bicycle level of service which is more data-intensive. The LTS criteria lacks many of the input variables found significant in predicting both route choice and mode choice, including several that are required for its more expensive alternatives. The authors select the Salem-Keizer metropolitan area, a case study representative of the kinds of small and medium-sized communities that may prefer to use the LTS to evaluate cycling infrastructure given its lower input costs. The results validate LTS on travel behavior data from the Oregon Household Activity Survey (OHAS), but not mode choice data from the American Community Survey (ACS). These results suggest the LTS criteria may not be useful for cities looking to prioritize infrastructure improvements for specifically increasing commuter cycling. That said, results suggest the system provides a valid measure of a household's propensity to cycle. Further research on a broader cross-section of communities can clarify these mixed results.