Relationship between proximity to transit and ridership for journey-to-work trips in Chicago

The use of privately owned vehicles (POVs) contributes significantly to US energy consumption (EC) and greenhouse gas emissions (GHGe). Strategies for reducing POV use include shifting trips to other modes, particularly public transit. Choices to use transit are based on characteristics of travelers, their trips, and the quality of competing transportation services. Here we focus on the proximity of rail stations to trip origins/destinations as a factor affecting mode choice for work trips. Using household travel survey data from Chicago, we evaluate the profile of journey-to-work (JTW) trips, assessing mode share and potential for more travelers to use rail. For work trips having the origin/destination as close as 1 mile from rail transit stations, POVs were still the dominant travel mode, capturing as much as 61%, followed by rail use at 14%. This high degree of POV use coupled with the proportion of JTW trips within close proximity to rail stations indicated that at least some of these trips may be candidates for shifting from POV to rail. For example, shifting all work trips with both the origin/destination within 1 mile of commuter rail stations would potentially reduce the energy associated with all work-related POV driving trips by a maximum of 24%. Based on the analysis of trips having the origin and destination closest to train stations, a complete shift in mode from POV to train could exceed CO₂ reduction goals targeted in the Chicago Climate Action Plan. This could occur with current settlement patterns and the use of existing infrastructure. However, changes in traveler behavior and possibly rail operation would be necessary, making policy to motivate this change essential.     

Economies of scale in bus transit: A review of concepts and evidence

The issue of returns of scale in bus transit continues to be a subject of debate among transportation analysts. From a public policy perspective, returns to scale are relevant to many policy areas such as transit service pricing, cost allocation, productivity and organization of the industry. Empirical studies conducted during the past decade have generated conflicting results. Constant, decreasing and increasing returns to scale have all been reported.This paper identifies the sources of these conflicting results: confusion regarding the concept of scale economies, variable definition, assumptions regarding the shape of the cost function, and certain characteristics of the data base. The paper also discusses the theoretical concept of scale economies, and an interpretation of the concept for bus transit is presented. It is concluded that recent studies which have utilized generalized cost functions more accurately represent the economic structure of bus transit, and provide a stronger basis for transit policy analysis.     

An automated approach to passive sonar classification using binary image features

This paper proposes a new method for ship recognition and classification using sound produced and radiated underwater. To do so, a three-step procedure is proposed. First, the preprocessing operations are utilized to reduce noise effects and provide signal for feature extraction. Second, a binary image, made from frequency spectrum of signal segmentation, is formed to extract effective features. Third, a neural classifier is designed to classify the signals. Two approaches, the proposed method and the fractal-based method are compared and tested on real data. The comparative results indicated better recognition ability and more robust performance of the proposed method than the fractal-based method. Therefore, the proposed method could improve the recognition accuracy of underwater acoustic targets.     

Can rural older drivers meet their needs without a car? Stated adaptation responses from a GPS travel diary survey

Rural seniors are highly dependent on their automobile to meet their trip making needs, yet the effects of aging can make access to the vehicle difficult or impossible over time. The anticipated growth in the older person population, in concert with limited travel data available to support rural transportation planning in Canada suggests a disconnect between what rural older people may require for transportation and the availability of formal alternatives. Many will seek informal alternatives to driving, such as depending on friends and family, to meet their travel needs, but the degree is not well understood in the context of their actual vehicle usage and stated ability to adapt. This paper draws from a Global Positioning System (GPS)-based multi-day travel diary survey of a convenience sample of 60 rural older drivers (29 men, 31 women, average age of 69.6 years) from New Brunswick, Canada. Participants would rely on “friends and family” for 52% of all trips they undertook as driver in the survey, “walk or bike” for 14% of trips, and “not take the trip” in 34% of trips if they did not have access to a vehicle. The formal option of “Transit” was not selected as a viable alternative by any participant for any trip. “Medical trips”, “Shopping” and “Personal Errands” were the least discretionary of all trip types, yet the most difficult for participants to find alternate arrangements. This suggests the need to explore different models of service delivery, such as a community-supported, member-based rural shuttle service with volunteer and paid drivers that build on informal social networks and can provide service when friends and family are unavailable.     

Accounting for inertia in modal choices: some new evidence using a RP/SP dataset

Inertia is related with effect that experiences in previous periods may have on the current choice. In particular, it has to do with the tendency to stick with the past choice even when another alternative becomes more appealing. As new situations force individuals to rethink about their choices new preferences may be formed. Thus a learning process begins that relaxes the effect of inertia in the current choice. In this paper we use a mixed dataset of revealed preference (RP)-stated preference (SP) to study the effect of inertia between RP and SP observations and to study if the inertia effect is stable along the SP experiments. Inertia has been studied more extensively with panel datasets, but few investigations have used RP/SP datasets. In this paper we extend previous work in several ways. We test and compare several ways of measuring inertia, including measures that have been proposed for both short and long RP panel datasets. We also explore new measures of inertia to test for the effect of “learning” (in the sense of acquiring experience or getting more familiar with) along the SP experiment and we disentangle this effect from the pure inertia effect. A mixed logit model is used that allows us to account for both systematic and random taste variations in the inertia effect and for correlations among RP and SP observations. Finally we explore the relation between the utility specification (especially in the SP dataset) and the role of inertia in explaining current choices.     

Predictions of porpoising inception for planing vessels

The inception of porpoising is theoretically predicted for planing vessels. Two different approaches are presented. First, a linear stability analysis is applied to find the porpoising limits while the hydrodynamic coefficients, i.e. added mass and damping coefficients, are determined by either a simplified method or a numerical method. Another approach is to seek the porpoising limits by performing nonlinear time domain simulations. Either the simplified method or the numerical method is used in the simulations. In the numerical method, a 2D+t theory together with a boundary element method is employed. The trim angle limits for porpoising are determined by changing the longitudinal position of the centre of gravity (COG) of the vessel and keeping the forward speed constant. The predicted porpoising limits are compared with Day and Haag’s (Planing boat porpoising, Thesis, Webb Institute of Naval Architecture, 1952) experimental results. The influences of parameters such as the load coefficient, the vertical position of COG and the radius of gyration of the ship are investigated by varying those parameters in the linear stability analysis. In the nonlinear time-domain simulations, by trying different longitudinal position of COG, one can find the critical trim angle when the porpoising commences. The obtained trim limits agree generally with those predicted by the linear stability analysis. Bounded oscillations for the unstable cases near the critical trim angle can be seen in the time-domain simulations due to the nonlinear effects.     

The applicability of non-cooperative game theory in transport analysis

Various models that incorporate concepts from Non-Cooperative Game Theory (NCGT) are described in the transport literature. Game Theory provides powerful tools for analysing transport systems, but these tools have some drawbacks that should be recognised. In the current paper we review games that describe transport problems and discuss them within a uniform context. Although the paper does not introduce new tools, it presents insights concerning the relations between transport models and games. We divide existing games into groups and show that some common features characterise multiple games. We distinguish between games that make a conceptual contribution and games that are suitable for application. Compact or symmetric game structures make remarkable observations but often do not support actual decision-making. Less aesthetic formats, most of which are Stackelberg games between authorities and travellers, are stronger as instruments that assist in determining real-life policies; these formulations can be treated by practitioners as mathematical programs with equilibrium constraints and not as games. Yaron Hollander is currently conducting economic research of bus reliability at the Institute for Transport Studies at the University of Leeds. He previously worked for the Technion—Israel Institute of Technology; for the Israel Institute for Transportation Planning and Research; and for the public transport department at Ayalon Highways Co. Joseph N. Prashker is a professor at the Faculty of Civil and Environmental Engineering at the Technion—Israel Institute of Technology. Till recently he served as head of the Transportation Research Institute at the Technion. His interests are behavioural demand models, network analysis, and Game Theory applications in transportation.     

Generating complete all-day activity plans with genetic algorithms

Activity-based demand generation contructs complete all-day activity plans for each member of a population, and derives transportation demand from the fact that consecutive activities at different locations need to be connected by travel. Besides many other advantages, activity-based demand generation also fits well into the paradigm of multi-agent simulation, where each traveler is kept as an individual throughout the whole modeling process. In this paper, we present a new approach to the problem, which uses genetic algorithms (GA). Our GA keeps, for each member of the population, several instances of possible all-day activity plans in memory. Those plans are modified by mutation and crossover, while bad instances are eventually discarded. Any GA needs a fitness function to evaluate the performance of each instance. For all-day activity plans, it makes sense to use a utility function to obtain such a fitness. In consequence, a significant part of the paper is spent discussing such a utility function. In addition, the paper shows the performance of the algorithm to a few selected problems, including very busy and rather non-busy days.     

The rational locator reexamined: Are travel times still stable?

The rational locator hypothesis posits that individuals can, if they choose, maintain approximately steady journey-to-work travel times by adjusting their home and workplace. This hypothesis was coupled with the observation of long-term stability in drive alone journey-to-work times in metropolitan Washington (those times were unchanged from 1957 through 1968 to 1988). Despite the increase of average commuting distance and congestion, trip duration remained constant or even declined when controlling for travel purpose and travel mode because of shifting a share of traffic from slow urban routes to faster suburban routes. This observation has significance, as it is important to know for travel demand analysis if there is an underlying budget, or even a regularity, as this helps us determine whether our forecasts are reasonable. To re-test the underlying rationale for the hypothesis that travel times are stable, intra-metropolitan comparisons of travel times are made using Washington DC data from 1968, 1988, and 1994, and Twin Cities data from 1990 and 2000. The results depend upon geography. For the larger Washington DC region, keeping the same geography shows little change in commute times, but using the larger 1994 area suggests an increase in commute times. However, the Twin Cities, starting from a much shorter commute time, shows a marked increase over the decade, using either the smaller or the larger geography. Despite the remarkable continuing observation of stability in drive alone commuting times in metropolitan Washington, we reject the theory of personal commuting budgets, as we find that not only are commuting times not generally stable over time at the intra-metropolitan area, but that commuting time clearly depends on metropolitan spatial structure.