An assignment principle for urban networks based on travel budgets

A new assignment principle for traveler behavior in an urban network is described which is based on empirical findings in the theory of travel budgets. It characterizes the distribution of travelers, demand, and modal split. It treats all travel decisions (whether to travel, where to go, how to get there) and the important costs (time and money) in a single, unified way. A numerical technique is proposed and it is applied to several examples to illustrate qualitative features.     

The future mobility of the world population

On average a person spends 1.1 h per day traveling and devotes a predictable fraction of income to travel. We show that these time and money budgets are stable over space and time and can be used for projecting future levels of mobility and transport mode. The fixed travel money budget requires that mobility rises nearly in proportion with income. Covering greater distances within the same fixed travel time budget requires that travelers shift to faster modes of transport. The choice of future transport modes is also constrained by path dependence because transport infrastructures change only slowly. In addition, demand for low-speed public transport is partially determined by urban population densities and land-use characteristics. We present a model that incorporates these constraints, which we use for projecting traffic volume and the share of the major motorized modes of transport—automobiles, buses, trains and high speed transport (mainly aircraft)—for 11 regions and the world through 2050. We project that by 2050 the average world citizen will travel as many kilometers as the average West European in 1990. The average American's mobility will rise by a factor of 2.6 by 2050, to 58,000 km/year. The average Indian travels 6000 km/year by 2050, comparable with West European levels in the early 1970s. Today, world citizens move 23 billion km in total; by 2050 that figure grows to 105 billion.     

TTB or not TTB, that is the question: a review and analysis of the empirical literature on travel time (and money) budgets

This paper summarizes and analyses findings from more than two dozen aggregate and disaggregate studies of travel time (and sometimes money) expenditures, exploring the question of the existence of a constant travel time budget. We conclude (with prior researchers) that travel time expenditures are not constant except, perhaps, at the most aggregate level. Nevertheless, individuals’ travel time expenditures do show patterns that can be partly explained by measurable characteristics. Travel time expenditure is strongly related to individual and household characteristics (e.g., income level, gender, employment status, and car ownership), attributes of activities at the destination (e.g., activity group and activity duration), and characteristics of residential areas (e.g., density, spatial structure, and level of service). To the extent that travel time expenditures are constant at the aggregate level, the underlying mechanisms explaining that regularity are not well understood. Consequently, further research into explaining travel time and money expenditure patterns is justified.     

On the cost of misperceived travel time variability

Because individuals may misperceive travel time distributions, using the implied reduced form of the scheduling model might fall short of capturing all costs of travel time variability. We reformulate a general scheduling model employing rank-dependent utility theory and derive two special cases as econometric specifications to study these uncaptured costs. It is found that reduced-form expected cost functions still have a mean–variance form when misperception is considered, but the value of travel time variability is higher. We estimate these two models with stated-preference data and calculate the empirical cost of misperception. We find that: (i) travelers are mostly pessimistic and thus tend to choose departure times too early to achieve a minimum cost, (ii) scheduling preferences elicited using a stated-choice method can be relatively biased if probability weighting is not considered, and (iii) the extra cost of misperceiving the travel time distribution might be nontrivial when time is valued differently over the time of day and is substantial for some people.     

Why do urban travelers select multimodal travel options: A repertory grid analysis

The increasing number of travelers in urban areas has led to new opportunities for local government and private mobility providers to offer new travel modes besides and in addition to traditional ones. Multimodal travel provides an especially promising opportunity. However, until now the underlying reasons why consumers choose specific alternatives have not been fully understood. Hence, the design of new travel modes is mainly driven by obvious criteria such as environmental friendliness and convenience but might not consider consumers’ real or latent needs. To close this research gap, sixty in-depth interviews with urban travelers were conducted. To identify the perceptual differences of customers among different travel modes, the repertory grid technique as an innovative, structured interview method was applied. Our data show that urban travelers distinguish and select travel alternatives based on 28 perceptual determinants. While some determinants associated with private cars such as privacy, flexibility and autonomy are key indicators of travel mode choice, costs and time efficiency also play a major role. Furthermore, by comparing travel modes to an ideal category, we reveal that some perceptual determinants do not need to be maximized in order to fulfill customer needs optimally. A comparison of consumers’ perceptual assessments of alternative travel modes identifies specific advantages and disadvantages of all alternatives, and provides fruitful implications for government and private mobility providers.     

A review of the evidence for induced travel and changes in transportation and environmental policy in the US and the UK

This paper reviews recent research into the demand inducing effects of new transportation capacity. We begin with a discussion of the basic theoretical background and then review recent research both in the UK and the US. Results of this research show strong evidence that new transportation capacity induces increased travel, both due to short run effects and long run changes in land use development patterns. While this topic has long been debated amongst transportation planners, the fundamental hypothesis and theory has long been apparent in studies of transportation economics and planning that evaluated different issues (e.g. travel time budgets and urban economic development effects). We summarize much of this work and relate the theoretical issues to recent empirical research. We then proceed to examine recent changes in transportation and environmental policy in the US and the UK. The role of the new knowledge of induced travel effects would be expected to lead to changes in the conduct of transportation and environmental policy. Changes in policy and implementation of those policies are still occurring and we provide some suggestions on how to move forward in these areas.     

Testing the stability of travel expenditures in Nigeria

A report is presented on a study carried out to develop a functional form for travel money expenditure in a Nigerian setting, and test its stability against energy policy change, specifically the fuel price increase of October 1994. The Box–Cox transformation regression approach was adopted in the modelling exercise in order to evolve a data-defined functional form and ensure a more rational basis for the stability test. The results of the modelling exercise show that while statistically significant functional forms were estimated for the “before” and “after” fuel price increase periods, the functional forms estimated are not stable across the periods. Thus “travel budget” is as yet not usable as a term for travel expenditures in Nigeria. The implication of this for travel demand modelling in Nigeria is that, at least till other evidences prove otherwise, there is as yet no basis for using the “Universal Mechanism Of Travel” model developed by Zahavi (The UMOT Project. Report No. DOT-RSPA-DPB-20-79-3; The UMOT Travel Model II Report No. DOT-RSPA-DPB-50-82-11). Of disposable income and total expenditure, the former has proved to be more appropriate for use as “available money” for the estimation of travel expenditures in Nigeria in the “before” energy policy change period, while total expenditure proved appropriate in the “after” period.     

A model for integrated analysis of household location and travel choices

We develop a model for integrated analysis of household location and travel choices and investigate it from a theoretical point of view.Each household makes a joint choice of location (zone and house type) and a travel pattern that maximizes utility subject to budget and time constraints. Prices for housing are calculated so that demand equals supply in each submarket. The travel pattern consists of a set of expected trip frequencies to different destinations with different modes. The joint time and budget constraints ensure that time and cost sensitivities are consistent throughout the model. Choosing the entire travel pattern at once, as opposed to treating travel decisions as a series of isolated choices, allows the marginal utilities of trips to depend on which other trips are made.When choosing trip frequencies to destinations, households are assumed to prefer variation to an extent varying with the purpose of the trip. The travel pattern will tend to be more evenly distributed across trip ends the less similar destinations and individual preferences are. These heterogeneities of destinations and individual preferences, respectively, are expressed in terms of a set of parameters to be estimated.     

Optimal locations and travel time display for variable message signs

This paper first develops a network equilibrium model with the travel time information displayed via variable message signs (VMS). Specifically, the equilibrium considers the impact of the displayed travel time information on travelers’ route choices under the recurrent congestion, with the endogenous utilization rates of displayed information by travelers. The existence of the equilibrium is proved and an iterative solution procedure is provided. Then, we conduct the sensitivity analyses of the network equilibrium and further propose a paradox, i.e., providing travel time information via VMS to travelers may degrade the network performance under some poor designs. Therefore, we investigate the problem of designing the VMS locations and travel time display within a given budget, and formulate it as a mixed integer nonlinear program, solved by an active-set algorithm. Lastly, numerical examples are presented to offer insights on the equilibrium results and optimal designs of VMS.     

Reducing average comprehensive travel cost by rationally allocating trips to different travel modes

To study the effect of different transport policies on reducing the average comprehensive travel cost (CTC) of all travel modes, by increasing public transport modal share and decreasing car trips, an optimization model is developed based on travel cost utility. A nested logit model is applied to analyze trip modal split. A Genetic Algorithm is then used to determine the implementation of optimal solutions in which various transport policies are applied in order to reduce average CTC. The central urban region of Beijing is selected as the study area in this research. Different policies are analyzed for comparison, focusing on their optimal impacts on minimizing the average CTC utility of all travel modes by rationally allocating trips to different travel modes in the study area. It is found that the proposed optimization model provides a reasonable indication of the effect of policies applied.     

The travel and environmental implications of shared autonomous vehicles,using agent-based model scenarios

Carsharing programs that operate as short-term vehicle rentals (often for one-way trips before ending the rental) like Car2Go and ZipCar have quickly expanded, with the number of US users doubling every 1–2 years over the past decade. Such programs seek to shift personal transportation choices from an owned asset to a service used on demand. The advent of autonomous or fully self-driving vehicles will address many current carsharing barriers, including users’ travel to access available vehicles.This work describes the design of an agent-based model for shared autonomous vehicle (SAV) operations, the results of many case-study applications using this model, and the estimated environmental benefits of such settings, versus conventional vehicle ownership and use. The model operates by generating trips throughout a grid-based urban area, with each trip assigned an origin, destination and departure time, to mimic realistic travel profiles. A preliminary model run estimates the SAV fleet size required to reasonably service all trips, also using a variety of vehicle relocation strategies that seek to minimize future traveler wait times. Next, the model is run over one-hundred days, with driverless vehicles ferrying travelers from one destination to the next. During each 5-min interval, some unused SAVs relocate, attempting to shorten wait times for next-period travelers.Case studies vary trip generation rates, trip distribution patterns, network congestion levels, service area size, vehicle relocation strategies, and fleet size. Preliminary results indicate that each SAV can replace around eleven conventional vehicles, but adds up to 10% more travel distance than comparable non-SAV trips, resulting in overall beneficial emissions impacts, once fleet-efficiency changes and embodied versus in-use emissions are assessed.     

A modeling approach for matching ridesharing trips within macroscopic travel demand models

State of the art travel demand models for urban areas typically distinguish four or five main modes: walking, cycling, public transport and car. The mode car can be further split into car-driver and car-passenger. As the importance of ridesharing may increase in the coming years, ridesharing should be addressed as an additional sub or main mode in travel demand modeling. This requires an algorithm for matching the trips of suppliers (typically car drivers) and demanders (travelers of non-car modes). The paper presents a matching algorithm, which can be integrated in existing travel demand models. The algorithm works likewise with integer demand, which is typical for agent-based microscopic models, and with non-integer demand occurring in travel demand matrices of a macroscopic model. The algorithm compares two path sets of suppliers and demanders. The representation of a path in the road network is reduced from a sequence of links to a sequence of zones. The zones act as a buffer along the path, where demanders can be picked up. The travel demand model of the Stuttgart Region serves as an application example. The study estimates that the entire travel demand of all motorized modes in the Stuttgart Region could be transported by 7% of the current car fleet with 65% of the current vehicle distance traveled, if all travelers were willing to either use ridesharing vehicles with 6 seats or traditional rail.     

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.     

Spoke airports,intentional and unintentional ground travel,and the air travel decision-making process

For air travelers originating from the spokes of the US hub-and-spoke air network, price, flight frequency, and aircraft type are all known factors in their travel decision-making process. Less well known, however, is the extent to which different elements of ground travel enter into these travelers’ air journeys. Based on 51 interviews at four universities at spokes surrounding O’Hare International Airport, this article describes how considerations such as vehicle availability, individual driving ability, localized weather, and unanticipated ground travel are fundamentally part of the air travel decision-making process for spoke travelers.     

Value of travel time reliability: A review of current evidence

Travel time reliability is a fundamental factor in travel behavior. It represents the temporal uncertainty experienced by travelers in their movement between any two nodes in a network. The importance of the time reliability depends on the penalties incurred by the travelers. In road networks, travelers consider the existence of a trip travel time uncertainty in different choice situations (departure time, route, mode, and others). In this paper, a systematic review of the current state of research in travel time reliability, and more explicitly in the value of travel time reliability is presented. Moreover, a meta-analysis is performed in order to determine the reasons behind the discrepancy among the reliability estimates.     

Modelling discretionary travel in the presence of imperfect data

The use of mathematical models in transportation and regional planning is limited by the need to obtain reasonably accurate, complete data sets. In particular complete spatial coverage is required for the usual discrete origin-destination models. Because of the time and cost constraints of obtaining such data, those charged with decision making responsibilities may choose to do without information that could be provided by quantitative models. This paper presents a procedure for estimating origin-constrained flows in situations where complete data collection is difficult or impossible. To this end an abstract model of origin-constrained travel is formulated. The required urban fields are constructed using interpolation and/or approximation techniques applied to available data. The tractability of the general model is demonstrated in the case of estimating the energy consumed in travel to existing or proposed facilities. The ability of the model to function with incomplete data was tested by using it to predict travel to the major retail centers located in the Albany-Schenectady-Troy Metropolitan Area.     

A combined land use-transportation model when zonal travel demand is endogenously determined

A combined transportation-land use model is proposed in this paper. Unlike other existing urban land use and transportation planning models in which a “fixed demand” for services is assumed to be known at the zonal level of an urban area, zonal travel demand is endogenously determined together with link congestion costs, optimal amounts of production and resulting efficient densities of land uses, once the transportation network is given. Some characteristics of alternative solutions are demonstrated. The proposed model represents progress over previous efforts in combining land use-transportation problems since the travel choice as to origin, destination and routes as well as amounts of goods to be produced at the optimal density of land uses are integrated into a consistent mathematical programming framework.     

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.     

The use of travel time by rail passengers in Great Britain

In the face of a society that exhibits an increasing dependence on motorised mobility, the response of transport policy is one that remains grounded in the pursuit of quicker journey times. Less time spent travelling is assumed to convert ‘unproductive’ time into economically valuable time. This paper explores an alternative perspective on travel time. It seeks to examine the notion that travel time, rather than being wasted, can and does possess a positive utility. This brings into question the extent of assumed economic benefits derived from schemes and policies intended to reduce journey times. Specifically the paper reports on a national mail-back questionnaire survey of 26,221 rail passengers in Great Britain conducted in autumn 2004. The survey examined how passengers used their time on the train, how worthwhile that time use was considered to be and the role of mobile technologies. The results paint a picture of travel time use in which the behaviour and opinions of commuters, business travellers and leisure travellers are compared and contrasted. A substantial if not overwhelming incidence of positive utility of travel time use is revealed, especially for business travel but also for commuting and leisure travel. In light of the survey evidence the paper points to the challenge of understanding the notion of productivity and offers some critical comments concerning the current approach to economic appraisal in Britain.