Transportation impacts of center-based telecommuting: Interim findings from the Neighborhood Telecenters Project

The transportation impacts of center-based telecommuting for 24 participants (representing 69 person-days of travel and 295 trips) in the California Neighborhood Telecenters Project are analyzed. Comparing non-telecommuting (NTC) day to telecommuting (TC) day travel shows that person-trips did not change significantly, whereas vehicle-trips increased significantly (by about one trip) on TC days. Both PMT and VMT decline significantly on TC days: by an average of 68 miles (74%) and 38 miles (65%), respectively. When these savings are weighted by the frequency of telecommuting, overall reductions in PMT and VMT come to 19% and 17%, respectively, of total weekday travel. Commute trips increase slightly (by 0.5 trips) but significantly, mainly due to lunch-time trips made home from the telecenter. Total non-commute travel does not increase, but there is a significant shift from other modes to driving alone on TC days. Commute mode split on NTC days is not affected by telecommuting. Travel on TC days tends to be compressed into fewer hours. Higher numbers of return home, eat meal, shopping, and social/recreational trips are made on TC days, in exchange for a reduction (to zero) in the number of change mode trips.     

Impact of telecommuting on spatial and temporal patterns of household travel

A spatial and temporal analysis of travel diary data collected during the State of California Telecommuting Pilot Project is performed to determine the impacts of telecommuting on household travel behavior. The analysis is based on geocoded trip data where missing trips and trip attributes have been augmented to the extent possible. The results confirm the earlier finding that the Pilot Project telecommuters substantially reduced travel; on telecommuting days, the telecommuters made virtually no commute trips, reduced peak-period trips by 60%, total distance traveled by 75%, and freeway miles by 90%. The spatial analysis of the trip records has shown that the telecommuters chose non-work destinations that are closer to home; they exhibited contracted action spaces after the introduction of telecommuting. Importantly, this contraction took place on both telecommuting days and commuting days. The telecommuters distributed their trips, over the day and avoided peak-period travel on telecommuting days. Non-work trips, however, show similar patterns of temporal distribution on telecommuting days and commuting days. Non-work trips continued to be made during the lunch period and late afternoon and evening hours.     

Does telecommuting reduce vehicle-miles traveled? An aggregate time series analysis for the U.S.

. This study examines the impact of telecommuting on passenger vehicle-miles traveled (VMT) through a multivariate time series analysis of aggregate nationwide data spanning 1966–1999 for all variables except telecommuting, and 1988–1998 for telecommuting. The analysis was conducted in two stages. In the first stage, VMT (1966–1999) was modeled as a function of conventional variables representing economic activity, transportation price, transportation supply and socio-demographics. In the second stage, the residuals of the first stage (1988–1998) were modeled as a function of the number of telecommuters. We also assessed the change in annual VMT per telecommuter as well as VMT per telecommuting occasion, for 1998. The models suggest that telecommuting reduces VMT, with 94% confidence. Together with independent external evidence, the results suggest a reduction in annual VMT on the order of 0.8% or less. Even with impacts that small, when informally compared to similar reductions in VMT due to public transit ridership, telecommuting appears to be far more cost-effective in terms of public sector expenditures.     

Home-based telecommuting and intra-household interactions in work and non-work travel: A seemingly unrelated censored regression approach

Although telecommuting has become a popular option as a new mode of working, no theoretical or empirical consensus has been reached on its potential for substituting or generating travel. This study aims to evaluate the impact of a household head’s telecommuting on household travel while controlling for the interdependence within a household and across travel purposes, by applying seemingly unrelated censored regression models to data from the 2006 Household Travel Survey in the Seoul Metropolitan Area. In terms of vehicle kilometers traveled, the analysis shows that telecommuters’ non-commute and non-work trips as well as his/her household members’ non-work trips are greater than those of non-telecommuters and their household members’, whereas telecommuting partially reduces commuting trips. However, an analysis stratified by household type reveals that the difference for household members is significant only in households with less than one vehicle per employed member: in such households (with insufficient vehicles available), the vehicle otherwise used for mandatory travel, such as for the household head’s commute, can be used for non-commute purposes or by other household members if the household head does not use it for commuting. This implies that, when vehicle travel budgets of a given household are limited, this compensatory travel mechanism can make optimum use of limited resources (i.e., vehicles), but offsets the travel-substituting effect of telecommuting. Accordingly, to more precisely estimate the impact of telecommuting-promotion policies and apply them as part of travel demand management strategies, their counteracting effects among household members should be considered.     

Commuter impacts and behavior changes during a temporary freeway closure: the ‘Fix I-5’ project in Sacramento,California

One mile of Interstate 5 (I-5) in downtown Sacramento, California was closed intermittently for reconstruction (‘the Fix project’) over nine weeks in 2008. We analyze the impacts of the Fix on commuters’ travel behavior, as measured through two contemporaneous Internet-based surveys. The impacts of the Fix on traffic conditions do not appear to have been excessive: majorities in all relevant subsamples did not find conditions worse than usual, and sizable minorities actually found them to be better. Among the active changes to commute trips, the easiest options – avoiding rush hour and changing route – were the most common (adopted by 48% and 44%, respectively). Among the changes that reduced vehicle-miles traveled, increasing transit use and increasing telecommuting (TC) were the most common (each adopted by 5–6% of the relevant subsample). Binary logit models of these two choices suggest that persuading current adopters to increase their frequency of use is easier than convincing nonadopters to start TC or switch to transit. Women and those in larger households were found to be more likely to increase TC and transit use. Employer support of commute alternatives significantly influenced the adoption of both strategies.     

Metropolitan size and the impacts of telecommuting on personal travel

Telecommuting has been proposed by policy makers as a strategy to reduce travel and emissions. In studying the metropolitan size impact of telecommuting on personal travel, this paper addresses two questions: (1) whether telecommuting is consistently a substitute or complement to travel across different MSA sizes; and (2) whether the impact of telecommuting is higher in larger MSAs where telecommuting programs and policies have been more widely adopted. Data from the 2001 and 2009 National Household Travel Surveys are used. Through a series of tests that address two possible empirical biases, we find that telecommuting consistently had a complementary effect on one-way commute trips, daily total work trips and daily total non-work trips across different MSA sizes in both 2001 and 2009. The findings suggest that policies that promote telecommuting may indeed increase, rather than decrease, people’s travel demand, regardless of the size of the MSA. This seems to contradict what telecommuting policies are designed for. In addition, model results show that the complementary impact of telecommuting on daily travel is lower in larger MSAs, in terms of both daily total work trips and daily total non-work trips.     

Telecommuting and urban sprawl: mitigator or inciter?

There is some evidence to the effect that as cities become increasingly congested new housing starts occur at greater distances from urban centers while jobs tend to remain center-concentrated or develop in other suburbs. In either case, mean commute distances tend to increase. Telecommuting is seen as a means of increasing the jobs-housing balance in urban and suburban areas by enhancing the ability to move work to, or closer to, the workers' residences rather than requiring workers to commute to work daily. This has the immediate side effect of decreasing automobile congestion and associated energy consumption and air pollution. There is a possible longer term adverse impact of telecommuting resulting from its ability to decrease constraints on household location, thereby enhancing the rate of spread of suburbia. This paper reviews evidence concerning the possible effects of telecommuting on urban sprawl, as derived from a two-year test of telecommuting in California, and describes two scenarios of urban form development made more feasible by telecommuting.     

Telecommuting and travel: state of the practice,state of the art

This paper provides an overview of the status of telecommuting in the United States, especially as it relates to changes in travel behavior. Regarding the state of the practice, the paper discusses some refinements to the definition of telecommuting that have developed through increased operational experience. It reports several policy statements involving telecommuting, and explores the appeal of telecommuting as a public policy instrument. It highlights some trends in the implementation of home-based and work center-based telecommuting, and suggests that visible public-sector involvement has been crucial to the increased activity in this area.In sketching the state of the art, the paper outlines some frequently-stated hypotheses on telecommuting and travel behavior, and summarizes current empirical findings relating to those hypotheses. Finally, it suggests a variety of topics suitable for further research. These include studying factors influencing the ultimate adoption levels of telecommuting; impacts on energy/air quality, mode choice, and location/urban form; interactions with other transportation demand management strategies; relationships to the traditional urban travel demand forecasting process; cost/benefit tradeoffs; and telecommuting centers.     

Forecasting telecommuting

Transportation planners increasingly recognize telecommuting as an important trend. But while they often advocate telecommuting as a transportation demand management strategy, transportation planners have made little progress toward incorporating telecommuting into transportation forecasts, at least partly because of the limited data available. In this paper we explore four alternative methodologies for forecasting telecommuting and discuss the kinds of data that must be collected before these methodologies can be applied. The first approach is trend extrapolation, using curves of technological substitution. Sufficient data are currently available to produce forecasts, albeit highly uncertain forecasts, using this approach. However, even with better data this approach does not address underlying factors and trends that will affect the future of telecommuting. As a result, we explore three additional approaches that should produce more reliable forecasts but which require new data and knowledge about telecommuting: analyzing the characteristics of telecommuters in contrast to nontelecommuters, analyzing factors affecting the individual choice to telecommute, and incorporating telecommuting into traditional transportation forecasting models.     

Analyzing the preference for non-exclusive forms of telecommuting: Modeling and policy implications

This study examines three models of the individual's preference for home- and center-based telecommuting. Issues concerning the estimation of discrete models when the alternatives are non-exclusive are discussed. Two binary logit models are presented, one on the preference to telecommute from a center versus not telecommuting from a center (adjusted ² = 0.24), and the other on the preference to telecommute from a center over telecommuting from home (adjusted ² = 0.64). A nested logit model is also estimated on the following four alternatives: preferring not to telecommute, preferring either form of telecommuting, preferring to telecommute from home, and preferring to telecommute from a center (adjusted ² = 0.35).The results of the models illustrated the importance of attitudinal measures in measuring an individual's preference to telecommute. Oblique factor scores representing workplace interaction, stress, workaholism, internal control, and commute stress were statistically significant in some or all of the models. Other explanatory variables which were found to be consistently significant were education, job suitability, and age. Most respondents preferred either to telecommute from home or were indifferent between either form of telecommuting, which raises the question as to whether there really is a sizeable market niche to be filled by telecommuting centers, and hence whether they may make a significant contribution to transportation demand reduction.     

Relationships between highway capacity and induced vehicle travel

The theory of induced travel demand asserts that increases in highway capacity will induce additional growth in traffic. This can occur through a variety of behavioral mechanisms including mode shifts, route shifts, redistribution of trips, generation of new trips, and long run land use changes that create new trips and longer trips. The objective of this paper is to statistically test whether this effect exists and to empirically derive elasticity relationships between lane miles of road capacity and vehicle miles of travel (VMT). An analysis of US data on lane mileage and VMT by state is conducted. The data are disaggregated by road type (interstates, arterials, and collectors) as well as by urban and rural classifications. Various econometric specifications are tested using a fixed effect cross-sectional time series model and a set of equations by road type (using Zellner’s seemingly unrelated regression). Lane miles are found to generally have a statistically significant relationship with VMT of about 0.3–0.6 in the short run and between 0.7 and 1.0 in the long run. Elasticities are larger for models with more specific road types. A distributed lag model suggests a reasonable long-term lag structure. About 25% of VMT growth is estimated to be due to lane mile additions assuming historical rates of growth in road capacity. The results strongly support the hypothesis that added lane mileage can induce significant additional travel.     

Interpreting employee telecommuting adoption: An economics perspective

Travel demand is derived from activities at the trip destination; therefore, media that have the potential to provide services previously only supported by transportation will have a chance to be chosen by passengers. The idea of telecommuting is considered the most promising substitute of work trips and thus a good strategy of transportation demand management. From a microeconomics perspective, demand for goods or services can be interpreted as a function of prices and generalized income. Therefore, telecommuting adoption is viewed as a trade-off among the prices of telecommuting itself, substitutes, and complements, as well as generalized income and situational constrains incurred by the employee. The underlying rationale is interpreted by elasticity analysis of aggregate telecommuting demand, based on an adoption model, with respect to various decision variable. The results indicate that the elasticity with respect to the price that the employee may incur in order to telecommute is the largest one, and the elasticity with respect to the living space at home is the second one. Additionally, all of the elasticities found in the group of employees currently commuting by private transportation are greater than the corresponding ones found in the group of transit riders. These findings are expected to have significant implications of transportation policies. This revised version was published online in June 2006 with corrections to the Cover Date.     

Transit-based smart parking: An evaluation of the San Francisco Bay area field test

This paper presents an evaluation of the first transit-based smart parking project in the US at the San Francisco Bay Area Rapid Transit (BART) District station in Oakland, California. The paper begins with a review of the smart parking literature; next the smart parking field test is described including its capital, operational, and maintenance costs; and finally the results of the participant survey analysis are presented. Some key user response results are: (1) most participants used the smart parking system 1–3 days a month for commute travel and (2) 37% of respondents had seen the changeable message signs with parking information, but only 32% of those used this information to decide whether to continue driving or take BART. Some key changes in participant travel behavior include: (1) increases in BART mode share, (2) reductions in drive alone modal share, (3) decreased average commute time, and (4) an overall reduction in total vehicle miles of travel.     

Uncertain benefits: Application of Bayesian melding to the Alaskan Way Viaduct in Seattle

Uncertainty is inherent in major infrastructure projects, but public decision-making for such projects ignores it. We investigate the uncertainty about the future effects of tearing down the Alaskan Way Viaduct in downtown Seattle, using an integrated model of housing, jobs, land use and transportation, on outcomes including average commute times. Our methodology combines the urban simulation model UrbanSim with the regional transportation model. We assess uncertainty using Bayesian melding, yielding a full predictive distribution of average commute times on 22 different routes in 2020. Of these routes, 14 do not include the viaduct and eight do. For the 14 base routes that do not include the viaduct, the predictive distributions overlap substantially, and so there is no indication that removing the viaduct would increase commute times for these routes. For each of the eight routes that do include the viaduct, the 95% predictive interval for the difference in average travel times between the two scenarios includes zero, so there is not strong statistical support for the conclusion that removing the viaduct would lead to any increase in travel times. However, the median predicted increase is positive for each of these routes, with an average of 6 min, suggesting that there may be some measurable increase in travel time for drivers that use the viaduct as a core component of their commute.     

The impact of transit station areas on the travel behaviors of workers in Denver,Colorado

Transit development is one planning strategy that seeks to partially overcome limitations of low-density single use car oriented development styles. While many studies focus on how residential proximity to transit influences the travel behaviors of individuals, the effect of workplace proximity to transit is less understood. This paper asks, does working near a light rail transit station influence the travel behaviors of workers differently than workers living near a station? We begin by examining workers’ commute mode based on their residential and workplace proximity to transit station areas. Next, we analyze the ways in which personal travel behaviors differ between those who drive to work and those who do not. The data came from a 2009 travel behavior survey in the Denver, Colorado metropolitan area, which contains 8000 households, 16,000 individuals, and nearly 80,000 trips. We measure sustainable travel behaviors as reduced mileage, reduced number of trips, and increased use of non-car transportation. The results of this study indicate that living near a transit station area by itself does not increase the likelihood of using non-car modes for work commutes. But if the destination (work) is near a transit station area, persons are less likely to drive a car to work. People who both live and work in a transit station area are less likely to use a car and more likely to take non-car modes for both work and non-work (personal) trips. Especially for persons who work near a transit station area, the measures of personal trips and distances show a higher level of mobility for non-car commuters than car commuters – that is, more trips and more distant trips. The use of non-car modes for personal trips is most likely to occur by non-car commuters, regardless of their transit station area relationship.     

Estimating the trip generation impacts of autonomous vehicles on car travel in Victoria,Australia

Autonomous vehicles (AVs) potentially increase vehicle travel by reducing travel and parking costs and by providing improved mobility to those who are too young to drive or older people. The increase in vehicle travel could be generated by both trip diversion from other modes and entirely new trips. Existing studies however tend to overlook AVs’ impacts on entirely new trips. There is a need to develop a methodology for estimating possible impacts of AVs on entirely new trips across all age groups. This paper explores the impacts of AVs on car trips using a case study of Victoria, Australia. A new methodology for estimating entirely new trips associated with AVs is proposed by measuring gaps in travel need at different life stages. Results show that AVs would increase daily trips by 4.14% on average. The 76+ age group would have the largest increase of 18.5%, followed by the 18–24 age group and the 12–17 age group with 14.6 and 11.1% respectively. If car occupancy remains constant in AV scenarios, entirely new trips and trip diversions from public transport and active modes would lead to a 7.31% increase in car trips. However increases in car travel are substantially magnified by reduced car occupancy rates, a trend evidenced throughout the world. Car occupancy would need to increase by at least 5.3–7.3% to keep car trips unchanged in AV scenarios.     

A specialized equilibrium assignment algorithm for air quality modeling

A multiple user class equilibrium assignment algorithm is formulated to determine vehicle trips and the vehicle miles of travel (VMT) in various operating modes on highway links. A heuristic solution algorithm based on the Frank–Wolfe decomposition of the equilibrium assignment problem is presented. The treatment of intrazonal trips, which are very important for emission studies is also discussed. The solution algorithm is implemented in a traffic assignment program for emission studies, referred to as TAPES. The use of the algorithm is demonstrated through a TAPES model case study on a Charlotte, NC network database for 1990 AM peak period. The operating mode mix of VMT in cold transient, hot transient and hot stabilized modes, also known as the mix of cold-starts, hot-starts and stabilized mode trips, is derived on a link by link basis. The results are aggregated by facility type and the location of link segments. It is observed that the operating mode fractions in transient and stabilized modes could vary widely across different facility types geographic locations. The aggregated operating mode fractions derived from the assignment analysis indicates that a lesser proportion of VMT operates in cold and hot transient modes when compared to the operating mode mix derived from the Federal Test Procedure (FTP).     

Analysis of telecommuting behavior and impacts on travel demand and the environment

The discussion of whether, and to what extent, telecommuting can curb congestion in urban areas has spanned more than three decades. This study develops an integrated framework to provide the empirical evidence of the potential impacts of home-based telecommuting on travel behavior, network congestion, and air quality. In the first step, we estimate a telecommuting adoption model using a zero-inflated hierarchical ordered probit model to determine the factors associated with workers’ propensity to adopt telecommuting. Second, we implement the estimated model in the POLARIS activity-based framework to simulate the potential changes in workers’ activity-travel patterns and network congestion. Third, the MOVES mobile source emission simulator and Autonomie vehicle energy simulator are used to estimate the potential changes in vehicular emissions and fuel use in the network as a result of this policy. Different policy adoption scenarios are then tested in the proposed integrated platform. We found that compared to the current baseline situation where almost 12% of workers in Chicago region have flexible working time schedule, in the case when 50% of workers have flexible working time, telecommuting can reduce total daily vehicle miles traveled (VMT) and vehicle hours traveled (VHT) up to 0.69% and 2.09%, respectively. Considering the same comparison settings, this policy has the potential to reduce greenhouse gas and particulate matter emissions by up to 0.71% and 1.14%, respectively. In summary, our results endorse the fact that telecommuting policy has the potential to reduce network congestion and vehicular emissions specifically during rush hours.     

How much can trip chaining reduce VMT? A simplified method

Trip chaining represents a way to reduce vehicle miles traveled (VMT) that does not require people to shift away from driving private automobiles. While the existing literature on trip chaining acknowledges this potential, little has been done by way of quantifying this. This research seeks to fill this gap by using a large travel survey from the San Francisco Bay area to model the VMT generated by automobile tours as a function of tour composition (i.e., the number and type of destinations on that tour). The model results indicate that many tours involving trips chains (i.e., those tours with more than one destination) generate significantly less VMT than would occur if the destinations in these tours were split into multiple tours with single destinations. Tours that combine a work and non-work destination (which are the most common types of trip chains) particularly demonstrate potential for VMT reduction. Adding a non-work destination to a work tour is usually (depending on the specific type of destination) predicted to result in a reduction of 6–11 VMT, or about 20–30 %. Adding two non-work destinations to a work tour is usually predicted to result in a reduction of 10–22 VMT, or about 25–50 %.     

Sustainable commute in a car-dominant city: Factors affecting alternative mode choices among university students

This paper studies university students’ commute and housing behaviors using samples from Los Angeles, a place notorious for car dependence and dominance. It finds that being embedded in this place does not make university students drive alone more than their peers in other places. Being multimodal and having a discounted transit pass increase the odds of alternative modes while holding a parking permit reduces the odds of these modes. Commute distance is positively related to carpool and telecommuting. Gender, status (undergraduate vs. gradate) and age are significantly correlated to biking, walking or public transit. Students living alone are more likely to commute by driving alone than other students. Having friends and classmates living nearby increases the odds of taking public transit. Due to data constraints, this study cannot prove whether there is any correlation between information contagion and the effects of living alone and having friends and classmates living nearby on alternative mode choice. But it proposes that the issue be worthwhile of further investigations. Base on the above, the paper recommends a comprehensive travel demand management program, utilization of information contagion effects of students and promotion of multimodal commute to better promote alternative mode of commute among university students.