The relation between daily travel and use of the home computer

On the basis of the Norwegian national personal travel survey (NPTS) 1997/98 and a connected mail back survey of the use of information – and communication technology at home, the relation between mobility and use of stationary communication has been studied. On the basis of these results we cannot see any direct substitutionary effects of the use of stationary technology at people's home on the use of mobile technology. Access to and use of information technology seems not to have a significant impact on travel activities in everyday life. Stationary communication seems to be a supplement to activities based on mobile technology. For people who work more than “normal” weekly working hours, stationary technology seems to give them greater flexibility in regard to where to work, but it does not necessarily reduce their travel activity. There is a tendency that people who own home computers make less work trips, but this does not affect the total number of daily trips. The spatial flexibility give a temporal flexibility, which means that work trips and other trips can be more dispersed over the day than is the situation today. The positive consequence can be a reduction in the rush-hour traffic; the negative is that it is more difficult to offer a high frequent public transport service when travel needs are more spread in time. Ownership and use of both mobile and stationary technologies are unequally distributed. Men, people with high education and income are the most frequent owners and users.     

Beyond the journey to work

This paper analyses the Nationwide Personal Transportation Study (NPTS) surveys of 1977 and 1983–1984 that reveal a remarkable increase in nonwork travel. This growth occurred among all city size classes but was stronger for suburban residents. Also interesting is that the rate of increase in nonwork trips was higher in the peaks (especially in the morning peak) than in the off-peak period. Some, but not all, of these trips may be price-elastic and might be diverted by congestion pricing strategies. The nonwork trip growth is concentrated in the “family and personal” and the “social and recreational” categories. Although higher-income households make more trips than low-income households, the increase in nonwork travel is common to all income groups. The growth in nonwork travel does not appear to be closely associated with the growth in female employment or trips related to the children of working women. The most convincing explanation of the growth in nonwork travel is that the trip cost savings (less time and distance) experienced because of more efficient spatial settlement patterns have provided an incentive to undertake more trips. Another implication is that urban economic models and urban transport policies have overemphasized the journey to work, especially to the central business district (CBD).     

The use of GIS and relational database management systems to improve the scheduling operations of paratransit

The scheduling operations of many paratransit agencies in the United States are undertaken manually. Those customers who are eligible to travel call in their requests the day before the trip is needed. As the trip requests are received, they are entered into a list of unscheduled trips. In order to schedule these trips, the scheduler must first determine the number of drivers and shuttle buses that are available as well as the time of availability of each. The scheduler must then try to match the rides that are in “similar” areas around the “same” time to place together on the driver's schedule. As new trip requests are made, the schedulers must adjust the trips that are already scheduled to try and schedule as many trips as possible in the most efficient way.

By developing a system that would improve the scheduling system operations of, in this case, DART (Delaware Administration for Regional Transit) First State Paratransit, customers can expect to receive better service that will improve their ability to travel throughout the community. Some devices that could also improve the operations of paratransit agencies are described in this paper, such as satellite‐based Global Positioning System (GPS), radio communication systems, mobile computers, radio frequency‐based data communication systems, internet web pages, automated paratransit information systems, and card‐based data storage and transfer media. However, because paratransit systems are difficult to operate cost‐efficiently, the optimum and most cost‐efficient device must be selected. The system chosen for DART First State Paratransit includes the use of a relational database management system (RDMS) and a transportation Geographic Information System (GIS). RDMS keeps track of the database information as well as the scheduled trips and the GIS is ideal for analyzing both geographic and temporal data. This system is shown to be superior to the manual system.     

Avoiding specification errors in estimating the value of time

Sources of specification as well as measurement error in previous estimates of the value of time are examined in this paper, and a new set of estimates avoiding these errors is presented. The sources of specification error being analyzed are: (1) failure to take account of drivers' uncertainty in making their choices between alternative routes or modes, which was found empirically to bias the value of time estimate 50 percent or more; (2) the differential in comfort and similar intangible characteristics between two modes; and (3) the inability to account for cross-time substitutions by travelers in peak-hour conditions. Ways of avoiding these sources of error are suggested and implemented. The choice between “reported” and “measured” data is re-examined, with an emphasis on random rather than systematic perception errors by travelers. Some resulting estimates are: $1.91 per hour per adult for off-peak work trips, $2.08 for off-peak social-recreational trips, and $5.17 for peak-hour work trips.     

Modelling media choices in business organizations: Implications for analyzing telecommunications-transportation interactions

A framework to analyze the impact of the new electronic communication technologies on transportation systems in the business setting has been proposed. A component of the framework that focuses on the media choice processes of individuals was empirically tested using scenarios in which the physical mail media, courier services, the telephone, voice mail, and electronic mail were alternatives to complete information communication tasks. The media choice model developed in this research emphasizes the influence of the context of the communication activity on media choice. Individual and organizational characteristics are explicitly considered, along with variables describing the communication activity itself, and the relationship between the initiator and the recipient of the communication. These characteristics determine the relative importance of a set of communication attributes and personal needs which are then matched against the individual's perceptions and feelings about the media to form preferences and choices in specific contexts. Empirical results are presented using preference logit models for a series of information communication situations. Significant variations in preferences and the levels of significance of the independent variables provided evidence of the strong influence the context of the communication activity has on media choice. Implications of these results are discussed in terms of other types of business meetings which may involve choices between telecommunications media and transportation modes. The primary contribution of this research is a methodology that can be extended to rigorously analyze telecommunications-transportation interactions. The paper discusses some of the issues that need to be addressed in modelling telecommunications-transportation interactions.     

Discussing the “positive utilities” of autonomous vehicles: will travellers really use their time productively?

ABSTRACT

Autonomous vehicles (AVs) are expected to reshape travel behaviour and demand in part by enabling productive uses of travel time—a primary component of the “positive utility of travel” concept—thus reducing subjective values of travel time savings (VOT). Many studies from industry and academia have assumed significant increases in travel time use and reductions in VOT for AVs. In this position paper, I argue that AVs’ VOT impacts may be more modest than anticipated and derive from a different source. Vehicle designs and operations may limit activity engagement during travel, with AV users feeling more like car passengers than train riders. Furthermore, shared AVs may attenuate travel time use benefits, and productivity gains could be limited to long-distance trips. Although AV riders will likely have greater activity participation during travel, many in-vehicle activities today may be more about coping with commuting burdens than productively using travel time. Instead, VOT reductions may be more likely to arise from a different “positive utility”—subjective well-being improvements through reduced stresses of driving or the ability to relax and mentally transition. Given high uncertainty, further empirical research on the experiential, time use, and VOT impacts of AVs is needed.     

Virtual mobility and organizational reality – a note on the mobility needs in knowledge organisations

This article addresses the potential for reducing international work-related air travelling through the use of information and communication technologies such as videoconferences and e-learning in knowledge companies. It looks at the potential for reducing travel related to such things as meetings and teaching. In the absence of regulations, however, we do not find potential for reducing the number of trips of this type because they do not facilitate face-to-face contacts. Therefore the conclusion is, that policy and planning have to look for other options for pursuing ‘sustainable mobility’ policies in the future.     

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.     

Dynamic process model of mass effects on travel demand

Whereas transportation planners commonly predict the negative impacts of mass transportation, there is increasing empirical evidence of the existence of positive mass effects, whereby increased use of a mode by the ‘mass’ will generally increase its attractiveness for future travellers. In this paper we consider the dynamic impact of such an effect on the problem of travel demand forecasting, with particular regards to social network effects. Our proposed modelling approach is inspired by literature from social physics, evolutionary game theory and marketing. For simplicity of exposition, our model is specified for a scenario in which (a) there is a binary choice between two mobility lifestyles, referred to as car-oriented and transit-oriented, and (b) there are two population groups, where one is the “leading” or “innovative” population group and the other the “following” or “imitating” population group. This latter distinction follows the rather well-known Bass model from the marketing literature (1969). We develop the transition probabilities and transition dynamics. We illustrate with a numerical case study that despite lower intrinsic utility for the transit lifestyle, significant changes towards this lifestyle can be achieved by considering congestion, service improvements and mass effects. We further illustrate that mass effects can be positive or negative. In all cases we explore the sensitivity of our conclusions to the assumed parameter values.     

Congestion and pollution consequences of driving-to-school trips: A case study in Beijing

Parents compete for high-quality education for their children by enrolling them in good schools. However, in a Chinese mega-city like Beijing, three factors jointly lead to the spatial separation between schools and homes: the centralized public goods provision mechanism, the historical dependency in school location, and the constrained supply of housing in downtown. Without an adequate number of school buses, this spatial separation of schools and homes triggers the numerous long-distance driving-to-school trips by private vehicle during workday morning rush hours in Beijing. We use the start and end dates of “school holiday” as exogenous repeated shocks to the aggregate traffic congestion, and employ the two-stage least squares (2SLS) regression approach to examine the congestion and pollution consequences of such driving-to-school trips in Beijing. We find that, all else being equal, workdays during school holidays have a traffic congestion index 20% lower than that of non-school-holiday workdays. Such a sharp reduction in congestion leads to a significant decrease in PM₁₀ concentration. Policymakers should lower such “extra” congestion and environmental costs via optimizing the spatial balance between school supply and demand.     

Modeling traveler mode choice behavior of a new high-speed rail corridor in China

This study examines mode choice behavior for intercity business and personal/recreational trips. It uses multinomial logit and nested logit methods to analyze revealed preference data provided by travelers along the Yong-Tai-Wen multimodal corridor in Zhejiang, China. Income levels are found to be positively correlated with mode share increases for high-speed rail (HSR), expressway-based bus, and auto modes, while travel time and trip costs are negatively correlated with modal shift. Longer distance trips trigger modal shifts to HSR services but prevent modal shift to expressway-based auto use due to escalation of fuel cost and toll charges. Travelers are less elastic in their travel time and cost for trips by nonexpressway-based auto use modes. The magnitude of elasticity for travel time is higher than trip costs for business trips and lower for personal/recreational trips. The study provides some policy suggestions for transportation planners and decision-makers.     

Where do cyclists ride? A route choice model developed with revealed preference GPS data

To better understand bicyclists’ preferences for facility types, GPS units were used to observe the behavior of 164 cyclists in Portland, Oregon, USA for several days each. Trip purpose and several other trip-level variables recorded by the cyclists, and the resulting trips were coded to a highly detailed bicycle network. The authors used the 1449 non-exercise, utilitarian trips to estimate a bicycle route choice model. The model used a choice set generation algorithm based on multiple permutations of path attributes and was formulated to account for overlapping route alternatives. The findings suggest that cyclists are sensitive to the effects of distance, turn frequency, slope, intersection control (e.g. presence or absence of traffic signals), and traffic volumes. In addition, cyclists appear to place relatively high value on off-street bike paths, enhanced neighborhood bikeways with traffic calming features (aka “bicycle boulevards”), and bridge facilities. Bike lanes more or less exactly offset the negative effects of adjacent traffic, but were no more or less attractive than a basic low traffic volume street. Finally, route preferences differ between commute and other utilitarian trips; cyclists were more sensitive to distance and less sensitive to other infrastructure characteristics for commute trips.     

Non-commitment bias in public opinion on transit usage

Estimation of ridership on a new transit system in an area where no comparable service existed before is a difficult task of transit planning. Traditional modal split models cannot be used in these cases, because no data or basis for developing a new model or adjusting a “borrowed” model are available. One of the techniques which can be used in this type of situation, is to perform a “concept test” based on public opinion. This approach, however, is plagued with the phenomenon of non-commitment bias of interviewees, and tends to overestimate the ridership. A new fixed route and fixed schedule transit service in Johnson City in Tennessee provided a rare opportunity to perform an investigation on the non-commitment bias through “before” and “after” surveys. The analysis of the non-commitment and actual responses of a sample of residents revealed substantial bias. Overall, the non-commitment ridership estimate was about twice (100% greater than) the actual ridership.:It was also observed that the bias was higher for persons owning automobiles, and for work and shopping trips.     

Vehicle scheduling under stochastic trip times: An approximate dynamic programming approach

Due to unexpected demand surge and supply disruptions, road traffic conditions could exhibit substantial uncertainty, which often makes bus travelers encounter start delays of service trips and substantially degrades the performance of an urban transit system. Meanwhile, rapid advances of information and communication technologies have presented tremendous opportunities for intelligently scheduling a bus fleet. With the full consideration of delay propagation effects, this paper is devoted to formulating the stochastic dynamic vehicle scheduling problem, which dynamically schedules an urban bus fleet to tackle the trip time stochasticity, reduce the delay and minimize the total costs of a transit system. To address the challenge of “curse of dimensionality”, we adopt an approximate dynamic programming approach (ADP) where the value function is approximated through a three-layer feed-forward neural network so that we are capable of stepping forward to make decisions and solving the Bellman’s equation through sequentially solving multiple mixed integer linear programs. Numerical examples based on the realistic operations dataset of bus lines in Beijing have demonstrated that the proposed neural-network-based ADP approach not only exhibits a good learning behavior but also significantly outperforms both myopic and static polices, especially when trip time stochasticity is high.     

A measure of linked‐trip accessibility

The concept of accessibility has been variously interpreted as being the “nearness to places,” the “nearness to activities” and more recently the “ease of participating in activities.” With each of these qualitative interpretations, there has also been a variety of quantitative definitions of accessibility. This paper shows that many of the proposed definitions of accessibility can in fact be gathered together to form a spectrum of accessibility measures. These measures differ with respect to the factors included in their formulation and their degree of behavioural interpretation.

Existing measures of accessibility are shown to be deficient in one major aspect. That is, they assume that for any one measure of accessibility there is but one origin of trips. Thus, in estimating the accessibility of a point within a region it is assumed that all potential trips, which contribute to the accessibility of that point, start from that single point. In view of the considerable amount of evidence demonstrating the widespread, and increasing, occurrence of trip‐linking such a proposition must be viewed as being rather doubtful.

In the light of this, the paper proceeds to develop a measure of accessibility which explicitly accounts for the linking of trips. The implications of this measure, compared to a conventional unlinked‐trip accessibility measure, are discussed as are some problems which are foreseen in the practical implementation of such a measure.     

Would personal carbon trading reduce travel emissions more effectively than a carbon tax?

The application of personal carbon trading (PCT) to transport choices has recently been considered in the literature as a means of reducing CO₂ emissions. Its potential effectiveness in changing car travel behavior is compared to the conventional carbon tax (CT) by means of a stated preferences survey conducted among French drivers (N ∼ 300). We show evidence that PCT could effectively change travel behavior and hence reduce transport emissions from personal travel. There is however a definite reluctance to reduce car travel. We were unable to demonstrate any significant difference between the effectiveness of PCT and the CT with regard to changing travel behavior. However, in the experiment, the PCT scheme provided consistent results while this was not the case for the CT scheme. Further research is needed into the “social norm” conveyed by a personal emissions allowance.     

Transition to a cyclable city: Latent variables affecting bicycle commuting

An understanding of the key factors influencing bicycle commuting is essential for developing effective policies towards a cyclable city. This paper contributes to this line of research by proposing a methodology for including cycling-related indicators in mobility surveys based on the Theory of Planned Behaviour (TPB), and applying an exploratory factor analysis (EFA) to evaluate the structure of latent variables associated with bicycle commuting. The EFA identified six cycling latent variables: Lifestyle, Safety and comfort, Awareness, Direct disadvantages, Subjective norm, and Individual capabilities. These were complemented with a latent variable related to habit: Non-commuting cycling habit. Statistical differences and regression analysis were applied with the cycling latent variables. The study also includes the relationship between objective factors and bicycle commuting, which reveals minor associations. This methodology was applied to the “starter cycling city” of Vitoria-Gasteiz (Spain). The results confirm that in this context – in transition to a cyclable city – safety and comfort issues are not the main barriers for all commuters, although more progress needs to be made to normalise cycling. A set of customised policy initiatives is recommended in the light of the research findings, including marketing campaigns to encourage non-commuting cycling trips, bicycle measures to target social groups as opposed to individuals, bicycle-specific programs such as “Bike-to-work Days”, and cycling courses.     

A control scheme for high traffic density sectors

The development and testing of a traffic control scheme for the high density sectors of the Manhattan Central Business District (CBD) is described. The proposed control scheme is based on “spillback avoidance” approach rather than the conventional “progressive movement” approach. This plan is characterized by signal splits which reflect the need to service the growing east-west cross street demands in the direction of travel, yet provide near optimal offsets and splits to the north-south arterial traffic. Under this scheme, the signal offsets for the cross streets exhibit a “backward progression” which is optimal (or near optimal) for streets with long queues and slow discharge headways. Netsim was executed to simulate traffic operations with the existing and proposed signal timing patterns on one of the test networks. Comparison of the results indicated that the number and duration of spillback blockages were markedly decreased, with a concommitant reduction in vehicle travel time and number of stops, coupled with an increase in vehicle trips serviced. A before-and-after field study yielded similar results, with the new control scheme providing a 20% reduction in overall travel time.     

Policy packages for modal shift and CO2 reduction in Lille,France

This paper proposes different policy scenarios to cut CO₂ emissions caused by the urban mobility of passengers. More precisely, we compare the effects of the ‘direct tool’ of carbon tax, to a combination of ‘indirect tools’ – not originally aimed at reducing CO₂ (i.e. congestion charging, parking charges and a reduction in public transport travel time) in terms of CO₂ impacts through a change in the modal split. In our model, modal choices depend on individual characteristics, trip features (including the effects of policy tools), and land use at origin and destination zones. Personal “CO₂ emissions budgets” resulting from the trips observed in the metropolitan area of Lille (France) in 2006 are calculated and compared to the situation related to the different policy scenarios. We find that an increase of 50% in parking charges combined with a cordon toll of €1.20 and a 10% travel time decrease in public transport services (made after recycling toll-revenues) is the winning scenario. The combined effects of all the policy scenarios are superior to their separate effects.     

Do high income households reduce driving more when living near rail transit?

Transportation planning today requires an understanding of how income and near-rail residence jointly influence household travel behavior. This article fills a gap in the literature by showing how vehicle miles traveled (VMT) and transit trips taken (TT) vary with income and rail transit access by neighborhood type. Results indicate that, when comparing households with similar incomes and examining how the “near-rail” versus “far from rail” VMT and TT gap varies by income, the cross-sectional reduction in nominal VMT and the increase in TT on a percentage basis is generally larger for higher-income households (>$50,000), and particularly so in neighborhoods dense with both jobs and population. These findings offer support for the notion that near-transit housing targeting higher-income households can have both sustainability and transit use benefits. We note, though, that equity considerations are a strong reason to include low-income housing near rail transit, and argue that policies focusing overly singly on either low-income or high-income housing near rail transit will not be as impactful as a robust focus on mixed-income housing developments in rail transit-oriented developments (TODs).