Evaluating employer programs encouraging the use of alternate transportation modes: Two studies

Since 1976, major Denver metropolitan area firms have been required to encourage employees to use mass transit, carpooling, bicycling, and other alternate transportation modes to commute to work. The encouragement programs of 36 firms were clearly associated with greater use of alternate transportation modes, with the portion of variance in alternate transportation use explained by differences in employer programs of approximately 15%. The effects of the programs on deterring alternate mode users from returning to solo driving are consistently weaker than their effects on persuading drivers to try alternate transportation modes initially. Recommendations for the conduct of alternate transportation encouragement programs are made, based on these and other results. In addition, two recommendations are made concerning the evaluation of encouragement programs: that aggregate percentage change in alternate transportation use should not be used as the sole measure of success, and that environmental variables such as the availability of and pressure for use of alternate transportation modes should be measured and controlled.     

Costs of travel time uncertainty and benefits of travel time information: Conceptual model and numerical examples

A negative effect of congestion that tends to be overlooked is travel time uncertainty. Travel time uncertainty causes scheduling costs due to early or late arrival. The negative effects of travel time uncertainty can be reduced by providing travellers with travel time information, which improves their estimate of the expected travel time, thereby reducing scheduling costs. In order to assess the negative effects of uncertainty and the benefits of travel time information, this paper proposes a conceptual model of departure time choice under travel time uncertainty and information. The model is based on expected utility theory, and includes the variation in travel time, the quality of travel time information and travellers’ perception of the travel time. The model is illustrated by an application to the case of the A2 motorway between Beesd and Utrecht in the Netherlands.     

Factors associated with proportions and miles of bicycling for transportation and recreation in six small US cities

The majority of bicycling in the US is for recreation rather than transportation purposes but few studies have examined the question of bicycling purpose. We use data from an online survey conducted in 2006 in six small cities in the western US to examine factors affecting bicycling for transportation compared to bicycling for recreation. The results indicate that individual, social-environment, and physical-environment factors have important influences on the balance between transportation and recreational bicycling and on miles of bicycling for each purpose. Bicycling comfort and an aversion to driving are associated with more transportation bicycling. A culture of utilitarian bicycling and short distances to destinations are also key factors for transportation bicycling. Bicycle infrastructure appears to play an indirect role through its effect on perceived bicycling safety and through the self-selection effect, by attracting bicycling-inclined people to bicycling-supportive communities.     

The implications of travel profiles for transportation investment: The Bronx Center Project

Investment in transportation infrastructure is generally regarded as an effective means for inducing economic growth and employment in a region. However, the ability of such investments to achieve these objectives, to a large extent, depends on the degree to which travel results from these investments support or conflict with present travel patterns and needs in this region. Using this view as a basis, this paper analyzes travel conditions and choices in the Bronx New York, where large scale transportation and other development projects (commonly called the Bronx Center Project) are presently taking place. Using a large data base, composed of census tract information on socio-economic and travel behavior, the paper first examines the travel profile of the Bronx population, by estimating travel choice elasticities. On the basis of these elasticities it then assesses the impact of the Bronx Center Project on travel patterns and trends.     

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.     

The impact of automated transit,pedestrian, and bicycling facilities on urban travel patterns

This article reports on an integrated modeling exercise, conducted on behalf of the US Federal Highway Administration, on the potential for frequent automated transit shuttles (‘community transit’), in conjunction with improvements to the walking and cycling environment, to overcome the last-mile problem of regional rail transit and thereby divert travelers away from car use. A set of interlocking investigations was undertaken, including development of urban visualizations, distribution of a home-based survey supporting a stated-preference model of mode choice, development of an agent-based model, and alignment of the mode-choice and agent-based models. The investigations were designed to produce best-case estimates of the impact of community transit and ancillary improvements in reducing car use. The models in combination suggested significant potential to divert drivers, especially in areas that were relatively transit-poor to begin with.     

An empirical evaluation of the travel impacts of teleconferencing

On February 20, 1986, the regular monthly meeting of the Southern California Association of Governments (SCAG) Transportation and Communications Committee was held as a two-way videoconference. Analysis of travel changes associated with the videoconference showed that vehicle miles traveled actually increased, compared to an average meeting held at the usual single location at SCAG offices. Although the average distance per person to the nearest teleconference site was 24% lower than the distance to the SCAG offices, the attendance at the teleconference was so much higher than average that total VMT was 29% higher than for a typical meeting held at SCAG.     

Evaluating impacts of coastal flooding on the transportation system using an activity-based travel demand model: a case study in Miami-Dade County,FL

Transportation - Recent climatic disasters have shown the vulnerability of transportation infrastructures against natural hazards. To understand the risk of coastal hazards on urban travel...     

Determinants of the willingness-to-pay for reducing the environmental impacts of road transportation

This paper examines the willingness-to-pay of people living in a number of villages in Navarre, in the Spanish Pyrenees to reduce noise and air pollution. Several models are used for estimation based on contingent valuation, noting that those living near roads are willing to pay more to reduce air and noise pollution. In addition, younger people, the better educated, and the more environmentally aware individuals are also willing to pay more to reduce those externalities.     

Evaluating the environmental impacts of online shopping: A behavioral and transportation approach

Various fields and commercial sectors have witnessed a transformation with the advent of the internet. In the last decade, the retail sector in particular has witnessed the massive growth of e-commerce. This has also significantly altered our shopping experiences, influencing a range of decisions, from where, how, and how much to shop. With the consistent growth of e-commerce transactions, more trucks than ever before are entering cities today, bringing with them the negative externalities of increased congestion and pollution. This study first unravels underlying shopping behaviors–both in-store and online–using the 2016 American Time Use Survey (ATUS) data. The authors also develop an econometric behavioral model to understand the factors that affect shopping decisions. At a macro level, the disaggregate individual shopping behaviors are studied by implementing the model to synthetic populations to estimate potential vehicle miles traveled and environmental emissions in two metropolitan areas, Dallas and San Francisco (SF). Finally, the study estimates the impacts of rush deliveries, basket size, and consolidation levels by developing a breakeven analysis between in-store and online shopping. These results confirm the importance of managing the urban freight system, including delivery services and operations, to foster a more sustainable urban environment.     

School choice: understanding the trade-off between travel distance and school quality

Children are traveling longer distances to school, and the share traveling by car is increasing. This paper examines the effects of school attributes on school choice, which in turn gives rise to travel distance and mode choice. It is well known that school quality is capitalized into residential land values. Households willing and able to pay price premiums may choose to live closer to good-quality schools. In contrast, households with less ability to pay are likely to live in places with schools of lower quality. The California public school system has an open enrollment policy, which allows students to transfer out of their neighbourhood school when places are available. When this option is exercised, students may travel longer distances to school compared with students who attend their neighbourhood schools. We used travel diary data from the 2001 Post Census Regional Household Travel Survey to model school destination choices for K-12 students in the Los Angeles region, California. Parents may choose to send their children to neighbourhood schools, other schools within their home district, or out-of-district schools. We find that location, school quality, and other school features influence the probability of a school being chosen, and the extent to which these factors influence choice varies depending on the characteristics of the residential district and the attributes of the household.     

The analysis of travel and emission impacts of travel demand management strategies using activity-based models

This paper demonstrates, tests and shows the value of activity-based travel demand models and household sample enumeration forecasting techniques in evaluating the transportation and air quality impacts of travel demand management strategies. Using data from the Portland, Oregon metropolitan area, three transportation policies were evaluated both individually and in combination: transit improvements, pricing, and telecommunications. The activity-based models used in this testing represents a significant improvement to today's "four-step" sequential model systems by providing a deeper insight into the individual decision making process in response to transportation policies. A wider range of impacts is predicted, and indirect effects as well as synergistic effects of such policies are taken into consideration. These models are capable of providing the information needed to improve the linkage of transportation models with emissions and air quality analysis methodologies by improving the prediction of variables that are important to accurately estimating emissions and air quality impacts of transportation actions.     

Analyzing the transportation impacts of increased coal haulage: Two case studies

Because of the Powerplant and Industrial Fuel Use Act of 1978 (FUA) and other supporting legislation, one of the goals of U.S. national energy policy has been significantly increased coal utilization. How this increased usage will impact the U.S. freight transportation system is a matter of concern to carriers, coal shippers of other commodities, and federal, state, and local governments. This paper reports a methodology and results of studies that analyze these impacts through the use of a freight network equilibrium model (FNEM). The model is the first to explicitly represent both sets of primary decision makers in freight transportation, namely the carriers and the shippers of freight. The model is described, and model results for two case studies are presented. In the first, the cumulative transportation impacts of switching 42 power plants in the northeastern United States from oil or natural gas to coal are studied. The second is a similar study of conversion to coal of 14 powerplants in Florida. Results include coal source identification, coal source to powerplant routings, congestion levels, and rate estimates.     

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.     

Mitigating environmental impacts in advance: Evidence of cost and time savings for transportation projects

The traditional model for mitigating a transportation project’s environmental impacts typically operates project-by-project and delivers the mitigation just-in-time. In contrast, the newer practice of advance mitigation comprehensively assesses and mitigates impacts from one or multiple transportation projects before or during project planning, sometimes long before project construction begins. The practice has gained adherents for its potential to improve ecological outcomes, by better aligning mitigation and conservation goals. Advance mitigation also stands to reduce mitigation costs, an important secondary benefit for transportation agencies with constrained resources. Evidence of cost savings, however, has been piecemeal and anecdotal. This paper advances knowledge of advance mitigation’s financial impacts in two ways. First, it critically assesses the evidence about cost savings realized through advance mitigation, both through avoided up-front costs and reduced project delay. Second, it directly estimates the project time savings that might accrue with advance mitigation of state highway projects in California. Overall, the balance of evidence is encouraging for transportation agencies that would introduce the practice, and general agreement exists on its financial benefits. Considering project delays related only to the environmental process, we estimate advance mitigation could reduce delivery times by 1.3–5.0 months per project. Still, we also identify factors limiting comprehensive analysis. Transportation agencies adopting advance mitigation practices into their operations could use a pilot approach that includes rigorous environmental and mitigation cost accounting; such pilots would build needed empirical evidence of advance mitigation’s financial and ecological outcomes.     

Modelling the impact of weather conditions on active transportation travel behaviour

Three weather sensitive models are used to explore the relationship between weather and home-based work trips within the City of Toronto, focusing on active modes of transportation. The data are restricted to non-captive commuters who have the option of selecting among five basic modes of auto driver, auto passenger, transit, bike and walk. Daily trip rates in various weather conditions are assessed. Overall, the results confirm that impact of weather on active modes of transportation is significant enough to deserve attention at the research, data collection and planning levels.     

Active school travel: homogeneity or heterogeneity? That is the question

ABSTRACT

To explain and predict active school travel (AST), most studies have not investigated to what extent considering taste heterogeneity is an important influence on AST share. The main aim of the present study was to evaluate whether considering unobserved taste heterogeneity through mixed logit models – including random coefficient and random coefficient analysis (RCA) – materially improves/influences the AST prediction compared to a simpler model – the multinomial logit (MNL) model. The database comprises 735 valid observations. The results show that, with a 10% increase in perceived walking time to school, the MNL model predicts that the AST share would decrease by 7.8% (from 18.9% to 17.4%) while the RCA model predicts that it would decrease by 8.5% (from 18.9% to 17.3%). Thus, the expected share of AST is overestimated by MNL by one-tenth of a percentage point. Although there might be random taste variations around perceived distance to school, it seems the other important policy-sensitive variables, such as safety perception, homogeneously impacts on the AST share across households with different socioeconomic and built environment characteristics. Our empirical assessment suggests that considering taste heterogeneity does not necessarily improve the accuracy of analysis for the aggregate share of the AST concerning policy-sensitive variables.     

Use of energy analysis for assessing environmental impacts due to transportation

This paper reports on a study to develop an energy analysis applications manual for environmental benefit/cost analysis of transportation actions. The manual is intended for state and local transportation agency analysts. The analysis procedure evaluates environmental impacts in energy terms. With energy as a common denominator of impact costs or benefits, the severities of different kinds of impacts are compared and the aggregate severity of a group of impacts is evaluated. A technique for evaluating the economic effects of environmental impacts is also suggested. The energy analysis procedure is briefly illustrated by means of a case study. The research findings indicate that the energy analysis procedure may supplement traditional methods of environmental impact assessment by providing: (i) comprehensive quantifications of individual kinds of impacts or the aggregate environmental impact of a transportation action: (ii) quantitative comparisons of the significance of different kinds of environmental impacts, even enabling comparison of government-regulated impacts with non-regulated ones and of any one category of impact with the aggregate environmental impact; and (iii) a basis for determining dollar values of environmental impacts.     

Characteristics analysis for travel behavior of transportation hub passengers using mobile phone data

The travel behavior of passengers from the transportation hub within the city area is critical for travel demand analysis, security monitoring, and supporting traffic facilities designing. However, the traditional methods used to study the travel behavior of the passengers inside the city are time and labor consuming. The records of the cellular communication provide a potential huge data source for this study to follow the movement of passengers. This study focuses on the passengers’ travel behavior of the Hongqiao transportation hub in Shanghai, China, utilizing the mobile phone data. First, a systematic and novel method is presented to extract the trip information from the mobile phone data. Several key travel characteristics of passengers, including passengers traveling inside the city and between cities, are analyzed and compared. The results show that the proposed method is effective to obtain the travel trajectories of mobile phone users. Besides, the travel behavior of incity passengers and external passengers are quite different. Then, the correlation analysis of the passengers’ travel trajectories is provided to research the availability of the comprehensive area. Moreover, the results of the correlation analysis further indicate that the comprehensive area of the Hongqiao hub plays a relatively important role in passengers’ daily travel.