Commute Mode Choice Research Articles

Investigating Telecommuting Considerations in the Context of Commuting Mode Choice

ABSTRACT This article applies an econometric model to investigate the determinants of telecommuting choices in the context of commute mode choices, based on a survey dataset from the City of Edmonton, Canada. Our results indicate that attributes of different commuting modes have different cross elastic effects on the attitude toward telecommuting. However, the magnitudes of cross elasticity are very low. Time of start of work plays a major role in considering telecommuting as a feasible choice. Moreover, it is clear that complementary Travel Demand Management (TDM) policies are necessary to encourage a positive attitude towards telecommuting.

Evaluating the effects of land use and strategies for parking and transit supply on mode choice of downtown commuters

Metropolitan regions around the world are looking for sustainable strategies to battle energy consumption and emissions. These strategies include land use policies and the desire to decrease the externalities from transportation and therefore increase the share of public transit use. The goal of this research is to better understand the relationships between Land-use (LU), public transit accessibility (PT), parking policies, and mode choice for suburban Montreal commuters. In this regard we evaluate the potential impact of land-use, transit accessibility and parking policies on the mode choice of the households dwelling in commuter rail line catchments in the region of Montreal, Canada. The approach adopted here is to consider mode choice as a joint decision with neighborhood type choice, based on neighborhood typologies derived using a cluster analysis characterized by land use variables. Also, the effect of parking fees on mode choice is investigated and quantified. The method used in this study is a simultaneous modeling approach to account for the endogeneity of mode and household location choice. The model system is made up of two models – a neighborhood type choice model and a mode choice model. The results demonstrate the robustness of the models and methodology implemented thus providing important innovations for transportation and land-use planning.

Spatial analysis of commuting mode choice in Guangzhou, China

Metropolitan cities in China are commonly confronted with unresolved traffic congestion issues, primarily due to rapidly increasing traffic demand. Group disparity between commuting mode choice and its spatial distribution on road networks has enabled us to examine the factors that give rise to the discrepancies and the fundamental spatial causes of traffic congestion. In recent years, micro-perspective, individual, and behavior-based spatial analysis have mushroomed and been facilitated with effective tools such as temporal geographic information systems (T-GIS). It is difficult to study the interrelations between transport and space on the basis of commuting mode choice since the mode choice data are invisible in a specific space such as a particular road network. Therefore, in the field of transport, the classical origin destination (OD) four-stage model (FSM) is usually employed to calculate data when studying commuting mode choice. Based on the relative principles of T-GIS and the platform of ArcGIS, this paper considers Guangzhou as a case study and develops a spatio-temporal tool to examine the daily activities of residents. Meanwhile, the traffic volume distribution in rush hours, which was analyzed according to commuting modes and how they were reflected in the road network, was scrutinized with data extracted from travel diaries. Moreover, efforts were made to explain the relationship between traffic demand and urban spatial structure. Based on the investigation, this research indicates that traffic volumes in divergent groups and on the road networks is driven by: 1) the socio-economic characteristics of travelers; 2) a jobs-housing imbalance under suburbanization; 3) differences in the spatial supply of transport modes; 4) the remains of the Danwei (work unit) system and market development in China; and 5) the transition of urban spatial structure and other factors.

Travel mode choice and transit route choice behavior in Montreal: insights from McGill University members commute patterns

In developed countries such as Canada and United States, a significant number of individuals depend on automobile as their main mode of transport. There has been a stronger push towards analyzing travel behavior at the individual level so that transportation agencies can formulate appropriate strategies to reduce the auto dependency. Towards this pursuit of enhancing our understanding on travel behavior, we examine individual home to work/school commute patterns in Montreal, Canada with an emphasis on the transit mode of travel. The overarching theme of this paper is to examine the effect of the performance of the public transportation system on commuter travel mode and transit route choice (for transit riders) in Montreal. We investigate two specific aspects of commute mode choice: (1) the factors that dissuade individuals from commuting by public transit and (2) the attributes that influence transit route choice decisions (for those individuals who commute by public transit). This study employs a unique survey conducted by researchers as part of the McGill University Sustainability project. The survey collected information on commute patterns of students, faculty and staff from McGill University. In addition, detailed socio-demographic and residential location information was also collected. The analysis was undertaken using multinomial logit model for the travel mode choice component and a mixed multinomial logit model for the transit route choice component. The model estimation results were employed to conduct policy sensitivity analysis that allows us to provide recommendations to public transportation and metropolitan agencies.

Effects of incorporating latent and attitudinal information in mode choice models

Hybrid choice modelling approaches allow latent variables in mode choice utility functions to be addressed. However, defining attitude and behavior as latent variables is influenced by the researcher's assumptions. Therefore, it is better to capture the effects of latent behavioral and attitudinal factors as latent variables than defining behaviors and attitudes per se. This article uses a hybrid choice model for capturing such latent effects, which will herein be referred to as modal captivity effects in commuting mode choice. Latent modal captivity refers to the unobserved and apparently unexplained attraction towards a specific mode of transportation that is resulting from latent attitude and behavior of passengers in addition to the urban transportation system. In empirical models, the latent modal captivity variables are explained as functions of different observed variables. Empirical models show significant improvement in fitting observed data as well as improved understanding of travel behavior.

The effect of work-related factors on the bicycle commute mode choice in the Netherlands

Increasing the number of people cycling to work brings a number of benefits: it can lead to reductions in air pollution and traffic jams, and increases people’s physical activity levels. We investigated the extent to which work-related factors influence (1) whether an individual decides to cycle to work, and (2) whether an individual cycles to work every day. It is anticipated that the office culture and colleagues’ and employers’ attitudes would significantly influence both decisions. These factors are expected to impact the provision of cycling facilities and financial compensation schemes in the workplace. We conducted an Internet survey in 4 Dutch municipalities, gathering data from over 4,000 respondents. The results suggest that the following factors increase the likelihood of being a commuter cyclist: having a positive attitude towards cycling; colleagues’ expectations that an individual will cycle to work; the presence of bicycle storage inside; having access to clothes changing facilities; and needing a bicycle during office hours. The presence of facilities for other transport modes, an increase in the commute distance, and the need to transport goods, in turn, reduces the chance that an individual will cycle. Cycling frequency is negatively affected, meanwhile, by an increase in commute distance, a free public transport pass or car parking provided by the employer. These results indicate that an individual’s working situation affects the commuting cycling behaviour. The findings also indicate that (partly) different variables influence an individual’s decision to cycle to work, and their decision to cycle every day.

Investigating Commute Mode and Route Choice Variability in Jakarta using multi-day GPS Data

Traffic congestion has become a part of commuters’ life in Jakarta for several years. Even though 3-in-1 traffic regulation has been implemented since 1992 in order to reduce the number of car driver travelling in busy corridors during morning and evening peak hours, and Bus Rapid Transit (BRT) has been operated since 2004, which is aimed to attract car drivers to use public transport, the traffic congestion problem in Jakarta has not been solved. The condition is even predicted to worse if the transport facilities in Jakarta are not improved. In order to find effective measures for reducing car use and improving public transport attractiveness in Jakarta, better understanding of commute mode and route choice behavior would be advantageous. This paper reports the first results of data analysis regarding dynamic behavior of commuters’ mode and route choice in Jakarta. The data were collected using GPS devices including questionnaire sheets during a one-week period. 93 commuters participated in the survey. Even though commute trips are routine trips and therefore often assumed to be static, the results show the presence of dynamic behavior in choosing both modes and routes for commuting. The dynamic behavior is as a way to avoid traffic congested roads and 3-in-1 corridors, and to maintain trip-chaining activities/stops. Car drivers and motorcyclists change frequently their routes, especially during work-to-home trips. Motorcyclists were more dynamic in choosing their routes than car drivers. A unique pattern of mode and route choice behavior was found which can be used for developing mode and route choice model in Jakarta.

Modeling airport employees commuting mode choice

This paper presents models airport employees’ commuting mode choice using a combination of revealed and stated preference data relating to Athens International Airport. The analysis finds that the employees are particularly sensitive to travel time, money costs, and their income in making modal choices, but do not distinguish between time costs of different components of their journey to work. It is found that a metro/suburban rail service with competitive fares and travel times could attract an important share of employees’ trips.

Modeling commuting mode choice jointly with work start time and work duration

This paper presents a joint trivariate discrete–continuous–continuous model for commuters’ mode choice, work start time and work duration. The model is designed to capture correlations among random components influencing these decisions. For empirical investigation, the model is estimated using a data set collected in the Greater Toronto Area (GTA) in 2001. Considering the fact that work duration involves medium- to long-term decision making compared to short-term activity scheduling decisions, work duration is considered endogenous to work start time decisions. The empirical model reveals many behavioral details of commuters’ mode choice, work start time and duration decisions. The primary objective of the model is to predict workers’ work schedules according to mode choice, which is considered a skeletal activity schedule in activity-based travel demand models. However, the empirical model reveals many behavioral details of workers’ mode choices and work scheduling. Independent application of the model for travel demand management policy evaluations is also promising, as it provides better value in terms of travel time estimates.

Parking management, financial subsidies to alternatives to drive alone and commute mode choices in Seattle

This paper develops a nested logit model to examine the impact of parking management, financial subsidies to alternative modes to drive alone, as well as travel demand management strategies on people's commute mode choices in Seattle based on the Washington State Commute Trip Reduction dataset in 2005. The major findings of this paper suggest that commuter's mode choice can be affected by various public policy tools. In particular, we find commuters' drive alone to work rate decreases as a response to higher SOV parking charges, higher HOV parking discount, and lower onsite parking space ratio. When employers provide reserved parking for HOV and HOV fleet vehicles for shared riders, commuters' likelihood to share ride to work also increases. Commuters also respond to direct financial subsidies to alternative modes positively.

Modeling the choice continuum: an integrated model of residential location, auto ownership, bicycle ownership, and commute tour mode choice decisions

The integrated modeling of land use and transportation choices involves analyzing a continuum of choices that characterize people’s lifestyles across temporal scales. This includes long-term choices such as residential and work location choices that affect land-use, medium-term choices such as vehicle ownership, and short-term choices such as travel mode choice that affect travel demand. Prior research in this area has been limited by the complexities associated with the development of integrated model systems that combine the long-, medium- and short-term choices into a unified analytical framework. This paper presents an integrated simultaneous multi-dimensional choice model of residential location, auto ownership, bicycle ownership, and commute tour mode choices using a mixed multidimensional choice modeling methodology. Model estimation results using the San Francisco Bay Area highlight a series of interdependencies among the multi-dimensional choice processes. The interdependencies include: (1) self-selection effects due to observed and unobserved factors, where households locate based on lifestyle and mobility preferences, (2) endogeneity effects, where any one choice dimension is not exogenous to another, but is endogenous to the system as a whole, (3) correlated error structures, where common unobserved factors significantly and simultaneously impact multiple choice dimensions, and (4) unobserved heterogeneity, where decision-makers show significant variation in sensitivity to explanatory variables due to unobserved factors. From a policy standpoint, to be able to forecast the “true” causal influence of activity-travel environment changes on residential location, auto/bicycle ownership, and commute mode choices, it is necessary to capture the above-identified interdependencies by jointly modeling the multiple choice dimensions in an integrated framework.

Modelling commuting mode choice with explicit consideration of carpool in the choice set formation

This article investigates the carpool mode choice option in the context of overall commuting mode choice preferences. The article uses a hybrid discrete choice modelling technique to jointly model the consideration of carpooling in the choice set formation as well as commuting mode choice together with the response bias corrections through the accommodation of measurement equations. A cross-nested error structure for the econometric formulation is used to capture correlations among various commuting modes and carpool consideration in the choice set. Empirical models are estimated using a data set collected through a week-long commuter survey in Edmonton, Alberta. The empirical model reveals many behavioural details of commuting mode choice and carpooling. Interestingly, it reveals that interactions between various Travel Demand Management (TDM) tools with the carpooling option can be different at different level of decision making (choice set formation level and final choice making level).

Importance of traveler attitudes in the choice of public transportation to work: findings from the Regional Transportation Authority Attitudinal Survey

The commute mode choice decision is one of the most fundamental aspects of daily travel. Although initial research in this area was limited to explaining mode choice behavior as a function of traveler socioeconomics, travel times, and costs, subsequent studies have included the effect of traveler attitudes and perceptions. This paper extends the existing body of literature by examining public transit choice in the Chicago area. Data from a recent Attitudinal Survey conducted by the Regional Transportation Authority (RTA) in Northeastern Illinois were used to pursue three major steps. First, a factor analysis methodology was used to condense scores on 23 statements related to daily travel into six factors. Second, the factor scores on these six dimensions were used in conjunction with traveler socioeconomics, travel times, and costs to estimate a binary logistic regression of public transit choice. Third, elasticities of transit choice to the six factors were computed, and the factors were ranked in decreasing order of these elasticities. The analysis provided two major findings. First, from a statistical standpoint, the attitudinal factors improved the intuitiveness and goodness-of-fit of the model. Second, from a policy standpoint, the analysis indicated the importance of word-of-mouth publicity in attracting new riders, as well as the need for a marketing message that emphasizes the lower stress level and better commute time productivity due to transit use.

Commuting mode choice in the context of travel demand management (TDM) policies: an empirical investigation in Edmonton, Alberta

Travel demand management (TDM) for achieving sustainability is now considered one of the most important aspects of transportation planning and operation. It is now a well known fact that excessive use of private car results inefficient travel behaviour. So, from the TDM perspective, it is of great importance to analyze travel behaviour for improving our understanding on how to influence people to reduce car use and choose more sustainable modes such as carpool, public transit, park & ride, walk, bike etc. This study attempts an in-depth analysis of commuting mode choice behaviour using a week-long commuter survey data set collected in the City of Edmonton. Using error correlated nested logit model for panel data, this study investigates sensitivities of various factors including some specific TDM policies such as flexible office hours, compressed work week etc. Results of the investigation provide profound understanding and guidelines for designing effective TDM policies.

Integrated transit services for minimum cost operation considering heterogeneous demand

In large metropolitan areas, public transit is a major mode choice of commuters for their daily travel, which has an important role in relieving congestion on transportation corridors. The purpose of this study is to develop a model which optimizes service patterns (SPs) and frequencies that yield minimum cost transit operation. Considering a general transit route with given stops and origin-destination demand, the proposed model consists of an objective total cost function and a set of constraints to ensure frequency conservation and sufficient capacity subject to operable fleet size. A numerical example is provided to demonstrate the effectiveness of the developed model, in which the demand and facility data of a rail transit route were given. Results show that the proposed model can be applied to optimize integrated SPs and headways that significantly reduce the total cost, while the resulting performance indicators are generated.

Analysis of work trip timing and mode choice in the Greater Toronto Area

This paper focuses on examining and analyzing observed trends in work trip making in the Greater Toronto Area (GTA). Commuter trip timing and mode choice behaviour are investigated to explain the main reasons behind peak spreading observed in cordon count data from 1975 through 2004 and to better understand the relationship between modal and temporal decisions. From analysis it becomes clear that significant differences exist in the trip timing trends of individuals choosing different modes. Multinomial logit mode choice models are developed for separate occupation groups, revealing significant differences in the mode choice preferences between occupation groups. Such differences are related to the differences in occupation-specific factors, including labour rates, work hour rules, free parking availability, and the spatial distribution of work locations. Overall, the investigations of this paper indicate that a joint analysis and modelling of trip timing and mode choice has considerable merit in travel demand models.

大学通学交通施策検討のための居住交通割当モデル

Recent transportation policy for university students requires wider evaluations in order to promote cooperative activities of stakeholders. An optimization model to allocate residential areas and commuting modes to students is proposed in this study. The model solutions for Tohoku University show the income of bus operator fluctuates unstably and becomes either positive or negative, affected by a small price change of the Bus Free-Pass. Therefore, Bus Free-Pass policy doesn't directly result to the profitability. On the other hand, housing cost decreases stably after introduction of the Free-Pass is introduced. Then they can expect the effect of making a reasonable residential choice, but only in longer time range. This effect can be grasped only by wider consideration both of residential choice and commuting mode choice together.

Optimal All-Stop, Short-Turn, and Express Transit Services under Heterogeneous Demand

As a major mode choice of commuters, public transit plays an important role in relieving congestion on urban transportation networks. A model is developed for cost-efficient operation that optimizes all-stop, short-turn, and express transit services and the associated frequencies by considering heterogeneous demand. For a transit line with given stations and origin–destination demand, the objective total cost function is optimized by considering a set of constraints that ensure frequency conservation and sufficient capacity subject to operable fleet size. A numerical example is designed that is based on a real-world rail transit line to demonstrate the applicability and effectiveness of the developed model. Results show that optimized integrated service patterns and associated service frequencies significantly reduce total cost.

Suburbanization and transit-oriented development in China

The suburbanization of large Chinese cities has placed many residents in locations that are far less accessible than their prior residences, requiring motorized travel. This paper examines the impacts of relocation to outlying areas on job accessibility, commuting mode choice, and commuting durations based on a current-day and retrospective survey of recent movers to three suburban neighborhoods in Shanghai. Job accessibility levels were found to decline dramatically following the move, matched by increased motorized travel and longer commute durations. Relocating to a suburban area near a metrorail station, however, was found to moderate losses in job accessibility and for many, encourage switches from non-motorized to transit commuting. We conclude that transit-oriented development holds considerable promise for placing rapidly suburbanizing Chinese cities on a more sustainable pathway.

Impacts of self-selection and transit proximity on commute mode choice: evidence from Taipei rapid transit system

Debate over how land use and self-selection affect travel behavior continues. Prior research contributes limited empirical evidence to this debate, and characterizing self-selection remains problematic. This empirical research explores the impacts of self-selection and proximity to transit at both residence and workplace. The research hypothesis is self-selection and proximity to transit increase the probability of workers commuting by rapid rail transit. To conduct this research, a station-exit passenger survey was conducted along the Taipei Rapid Transit System. Analysis methods include binomial logit modeling and sensitivity analysis. Research results support the idea that transit proximity to both work and residence increase the probability of transit commuting, but the hypothesis about the impact of self-selection is only partly supported. Policy implications suggest that, on one hand, increasing density around transit stations could realize unfulfilled self-selection; on the other hand, improved quality-of-life characteristics in neighborhoods around station areas may induce residents and companies to relocate to the neighborhood, thereby increasing residents’ and workers’ probabilities of commuting by transit.