Mass transportation needs and financing in the United States

The U.S. Department of Transportation (1974) recently completed a comprehensive study of mass transportation needs and methods for financing these needs. Using information from the 1974 National Transportation Study, the study determined the level of capital and operating funds that would be required to implement the 1972–90 long-range plans and 1972–80 short-range programs of the states and urbanized areas. It then analyzed various funding mechanisms at state and local levels for financing their portions of these plans and programs.It was found that urban areas, in general, not only plan to stabilize transit fares in the face of rising costs, but also intend to put $ 23.6 billion into capital investments through 1980 and an additional $ 34.6 billion through 1990. Of the total $ 58.2 billion in capital expenditures by 1990, 63% would be expended by the nine largest urbanized areas; 27.8% by the New York area alone. Rail transit and commuter railroad costs would account for 90% of the nine largest urbanized areas.States and localities would be able to carry the financial burden of mass transportation improvements, even if the proposed 1980 programs were implemented in their entirety, given current levels of Federal assistance. However, there would have to be a substantial financial commitment from the states and localities and some hard decisions made by them about public expenditure priorities, fare policies, and taxation levels, and policies to discourage automobile usage. This underscores the need for careful review of their overall plans and programs by state and local officials before making financial commitments.     

A route-based solution algorithm for dynamic user equilibrium assignments

The aim of this study is to establish a method to calculate good quality user equilibrium assignments under time varying conditions. For this purpose, it introduces a dynamic network loading method that can maintain correct flow propagation as well as flow conservation, and it shows a novel route-based solution algorithm. This novel algorithm turns out to be convenient and logically plausible compared to the conventional [Frank, M., Wolfe, P., 1956. An algorithm for quadratic programming. Naval Research Logistics Quarterly 3, 95–110] algorithm, because the former does not require evaluation of an objective function and it finds solutions maintaining correct flow propagation in the time-varying network conditions. The application of novel dynamic network loading method and solution algorithm to test networks shows that we can find high quality dynamic user equilibrium assignment. This is illustrated in an example network using the deterministic queuing model for a link performance function and associating costs and flows in a predictive way in discrete time.     

On the convergence of Bell's logit assignment formulation

In Bell M.G.H. (1995. Transportation Research B 29, 287–295), a new logit assignment formulation was developed, which considered all possible paths in the network while still retaining the absence of a need for path enumeration. In his formulation, it presumes that the sum of a geometric series of the weights matrix always converges and hence can be computed as the inversion of a matrix. In this paper, we investigate the convergence properties of this geometric series by means of an eigensystem interpretation which states that the series converges if and only if all the eigenvalues associated with the weights matrix fall into the unit circle in a complex plane. It is found that the geometric series converges unconditionally for acyclic networks, but not necessarily does so for general networks.     

A bilevel flow model for hazmat transportation network design

In this work we consider the following hazmat transportation network design problem. A given set of hazmat shipments has to be shipped over a road transportation network in order to transport a given amount of hazardous materials from specific origin points to specific destination points, and we assume there are regional and local government authorities that want to regulate the hazmat transportations by imposing restrictions on the amount of hazmat traffic over the network links. In particular, the regional authority aims to minimize the total transport risk induced over the entire region in which the transportation network is embedded, while local authorities want the risk over their local jurisdictions to be the lowest possible, forcing the regional authority to assure also risk equity. We provide a linear bilevel programming formulation for this hazmat transportation network design problem that takes into account both total risk minimization and risk equity. We transform the bilevel model into a single-level mixed integer linear program by replacing the second level (follower) problem by its KKT conditions and by linearizing the complementary constraints, and then we solve the MIP problem with a commercial optimization solver. The optimal solution may not be stable, and we provide an approach for testing its stability and for evaluating the range of its solution values when it is not stable. Moreover, since the bilevel model is difficult to be solved optimally and its optimal solution may not be stable, we provide a heuristic algorithm for the bilevel model able to always find a stable solution. The proposed bilevel model and heuristic algorithm are experimented on real scenarios of an Italian regional network.     

Algorithms for logit-based stochastic user equilibrium assignment

The paper proposes an efficient algorithm for determining the stochastic user equilibrium solution for logit-based loading. The commonly used Method of Successive Averages typically has a very slow convergence rate. The new algorithm described here uses Williams’ result [ Williams, (1977) On the formation of travel demand models and economic evaluation measures of user benefit. Environment and Planning 9A(3), 285–344] which enables the expected value of the perceived travel costs S_rs to be readily calculated for any flow vector x. This enables the value of the Sheffi and Powell, 1982 objective function [Sheffi, Y. and Powell, W. B. (1982) An algorithm for the equilibrium assignment problem with random link times. Networks 12(2), 191–207], and its gradient in any specified search direction, to be calculated. It is then shown how, at each iteration, an optimal step length along the search direction can be easily estimated, rather than using the pre-set step lengths, thus giving much faster convergence. The basic algorithm uses the standard search direction (towards the auxiliary solution). In addition the performance of two further versions of the algorithm are investigated, both of which use an optimal step length but alternative search directions, based on the Davidon–Fletcher–Powell function minimisation method. The first is an unconstrained and the second a constrained version. Comparisons are made of all three versions of the algorithm, using a number of test networks ranging from a simple three-link network to one with almost 3000 links. It is found that for all but the smallest network the version using the standard search direction gives the fastest rate of convergence. Extensions to allow for multiple user classes and elastic demand are also possible.     

Using longitudinal methods for analysis of a short-term transportation demonstration project

This paper documents an application of panel, or longitudinal data collection in the evaluation of a TSM (Transportation Systems Management) demonstration project. The project was a four-week demonstration of staggered work hours in downtown Honolulu during February–March 1988. The 4 wave panel survey elicited commuting experiences of approximately 2,000 downtown employees at two week intervals before and during the project. The sample involved both employees who participated in the project by shifting their work hours, and those who did not. The panel survey was augmented by floating-car observations of travel times on major routes into downtown Honolulu on the same four dates.The purpose of the analysis was to determine whether employee commute times were affected, and if so, how these changes were distributed among various employee segments. Two methods were used. First, travel time changes were estimated using paired t-tests. Second, regression equations were used to estimate project time savings as a function of trip length, route, and location of residence. Results show that travel time savings due to the project were typically small, less than ten percent. Nonparticipants experienced greater savings than participants, and some segments of participants experienced longer travel times during the project. The panel method proved to be an effective way to measure project travel time impacts and shows that the method is appropriate in short time applications.Presented at the Annual Meeting of Transportation Research Board, January 7–11. 1990, Washington, D.C.     

Anisotropic second-order models and associated fundamental diagrams

According to Banks [Investigation of some characteristics of congested flow. Transportation Research Record, 1999], traffic heterogeneity explains the data scattering on the flow–density plane and positive transferences within the congested phase (a transference is a line connecting adjacent points in the time series). This heterogeneity results from a traffic mixture, made up of various vehicles and drivers, or different traffic conditions such as meteorological conditions. This paper only deals with traffic mixture and more particularly with vehicle classes such as passenger car and truck, which are correlated to the vehicle length. When considering a macroscopic model, the mean vehicle length, which is measured by sensors, is associated with the truck percentage. Then the Generic Second Order Model (GSOM) by Lebacque [Lebacque, J.P., Mammar, S., Haj-Salem, H., 2007a. Generic second-order traffic flow modeling. In: Proceedings of the 17th International Symposium on Transportation and Traffic Theory, London, 23–25 July 2007, 749–770.] provides a rigorous mathematical framework for traffic heterogeneity modeling. The added value in this paper is that admissible invariants which characterize generic fundamental diagrams, possibly depending on the mean vehicle length, are interpreted and debated. Aw–Rascle–Zhang’s [Aw, A., Rascle, M., 2000. Resurrection of second-order models of traffic flow. SIAM Journal of Applied Mathematics, 60 (3), 916–938; Zhang, H.M., 2002. A non equilibrium traffic model devoid of gas-like behavior. Transportation Research Part B, 36, 275–290.] and Colombo’s [Colombo, R.M., 2002. A 2 × 2 hyperbolic traffic flow model. Mathematical and Computer Modeling, 35, 683–688.] anisotropic models are deeply analyzed from a traffic point of view. At last an extended GSOM equation system provides a full parameterization of fundamental diagrams which is needed to traffic heterogeneity modeling.     

An analysis of children’s leisure activity engagement: examining the day of week, location, physical activity level, and fixity dimensions

This paper presents a detailed analysis of discretionary leisure activity engagement by children. Children’s leisure activity engagement is of much interest to transportation professionals from an activity-based travel demand modeling perspective, to child development professionals from a sociological perspective, and to health professionals from an active lifestyle perspective that can help prevent obesity and other medical ailments from an early age. Using data from the 2002 Child Development Supplement of the Panel Study of Income Dynamics, this paper presents a detailed analysis of children’s discretionary activity engagement by day of week (weekend versus weekday), location (in-home versus out-of-home), type of activity (physically active versus passive), and nature of activity (structured versus unstructured). A mixed multiple discrete-continuous extreme value model formulation is adopted to account for the fact that children may participate in multiple activities and allocate positive time duration to each of the activities chosen. It is found that children participate at the highest rate and for the longest duration in passive unstructured leisure activities inside the home. Children in households with parents who are employed, higher income, or higher education were found to participate in structured outdoor activities at higher rates. The child activity modeling framework and methodology presented in this paper lends itself for incorporation into larger activity-based travel model systems where it is imperative that children’s activity-travel patterns be explicitly modeled—both from a child health and well-being policy perspective and from a travel forecasting perspective.

Development and evaluation of a hybrid travel time forecasting model

The purpose of this paper is to develop and evaluate a hybrid travel time forecasting model with geographic information systems (GIS) technologies for predicting link travel times in congested road networks. In a separate study by You and Kim (cf. You, J., Kim, T.J., 1999b. In: Proceedings of the Third Bi-Annual Conference of the Eastern Asia Society for Transportation Studies, 14–17 September, Taipei, Taiwan), a non-parametric regression model has been developed as a core forecasting algorithm to reduce computation time and increase forecasting accuracy. Using the core forecasting algorithm, a prototype hybrid forecasting model has been developed and tested by deploying GIS technologies in the following areas: (1) storing, retrieving, and displaying traffic data to assist in the forecasting procedures, (2) building road network data, and (3) integrating historical databases and road network data. This study shows that adopting GIS technologies in link travel time forecasting is efficient for achieving two goals: (1) reducing computational delay and (2) increasing forecasting accuracy.     

Convergence of the Frank-Wolfe method for certain bounded variable traffic assignment problems

In two recent papers published in Transportation Research, Daganzo presented a modification of the Frank-Wolfe algorithm to solve certain link capacitated traffic assignment problems satisfying certain conditions. In order to show convergence of the modified algorithm, the assumption was made that the integral of the volume delay formula for each link tends to infinity as the link flow approaches the link capacity. In this paper we give a Theorem which establishes convergence of the modified algorithm under much weaker conditions. This result is then used to show convergence if the objective function of the assignment model is sufficiently large (not necessarily infinite) when the link flows are at capacity. Thus the modified method is applicable to a broader class of assignment problems. Two numerical examples illustrate (a) when the method converges and when it does not, and (b) that our Theorem provides a weaker condition for convergence of the method.     

Policy innovations of the US intermodal surface transportation efficiency act and clean air act amendments

In combination, the Intermodal Surface Transportation Efficiency Act of 1991 (ISTEA) and the Clean Air Act Amendments of 1990 (CAAA) are innovative and aggressive efforts to move US cities toward integrated transportation and air quality planning. Under these complementary laws, air quality has become a major national transportation goal. In areas with serious air pollution, air quality will be a major consideration in determining the future shape of urban transportation.This paper considers how the CAAA and ISTEA combine to provide an innovative national policy approach of interest to countries seeking to encourage sustainable development in urban centers. The CAAA mandates measurable and enforceable air quality targets. Nation-wide standards are set for acceptable levels of carbon monoxide, ground level ozone, and small particulates. ISTEA includes directions for transportation planners and decision-makers to follow to reach air quality and other goals — transportation planning must emphasize system efficiency, and for cities with severe air pollution, transportation projects are expected to contribute to cleaner air. Each urban area has flexibility in how it applies this framework to reflect its priorities and solve its problems. Strict federal sanctions provide incentives for compliance with both laws.Enactment of these laws has produced a period of transition and uncertainty as well as of challenge and opportunity for planners and elected officials. The next several years, the US will provide one national laboratory and over 100 different urban laboratories for innovative approaches to integrate transportation and environmental policies to resolve major urban problems.Abbreviations CAAA Clean Air Act Amendments of 1990 - CO Carbon monoxide - ECO Employee Commute Option - EPA US Environmental Protection Agency - HC Transportation hydrocarbons - I/M Inspections and maintenance program - ISTEA Intermodal Surface Transportation Efficiency Act of 1991 - MPO Metropolitan planning organizations - NO_x Nitrogen oxides - PPM Parts per million - PM₁₀ Small particulate matter - SIP State Implementation Plan - TIP Transportation Improvement Program - TCM Transportation control measures - VMT Vehicle miles traveled     

A copula-based joint multinomial discrete–continuous model of vehicle type choice and miles of travel

In this paper, a joint model of vehicle type choice and utilization is formulated and estimated on a data set of vehicles drawn from the 2000 San Francisco Bay Area Travel Survey. The joint discrete–continuous model system formulated in this study explicitly accounts for common unobserved factors that may affect the choice and utilization of a certain vehicle type (i.e., self-selection effects). A new copula-based methodology is adopted to facilitate model estimation without imposing restrictive distribution assumptions on the dependency structures between the errors in the discrete and continuous choice components. The copula-based methodology is found to provide statistically superior goodness-of-fit when compared with previous estimation approaches for joint discrete–continuous model systems. The model system, when applied to simulate the impacts of a doubling in fuel price, shows that individuals are more likely to shift vehicle type choices than vehicle usage patterns.

The Aw–Rascle and Zhang’s model: Vacuum problems,existence and regularity of the solutions of the Riemann problem

In this paper we will discuss some aspects of the recent macroscopic models of the second-order proposed by [Aw, A., Rascle, M., 2000. Resurrection of second order models of traffic flow. SIAM Journal of Applied Mathematics 60 (3), 916–938] and [Zhang, H.M., 2002. A non-equilibrium traffic model devoid of gas-like behavior. Transportation Research Part B 36, 275–290]. These models were suggested after the publication of an article written by [Daganzo, C.F., 1995. Requiem for second-order fluid approximations of traffic flow. Transportation Research Part B 29, 277–286] showing that some classical second-order models can exhibit non-physical solutions. It is shown in this note that the ARZ (Aw–Rascle–Zhang) model respects the anisotropic character of traffic flow, that it yields physical solutions, and that vacuum problems can be solved satisfactorily, provided that the fundamental diagram (equilibrium speed–density relationship) is extended in a suitable fashion. It follows that the Riemann problem for the ARZ model with extended fundamental diagram always admits a solution, and that this solution depends continuously on the initial conditions.     

An analysis of bicycle route choice preferences in Texas,US

In the US, the rise in motorized vehicle travel has contributed to serious societal, environmental, economic, and public health problems. These problems have increased the interest in encouraging non-motorized modes of travel (walking and bicycling). The current study contributes toward this objective by identifying and evaluating the importance of attributes influencing bicyclists’ route choice preferences. Specifically, the paper examines a comprehensive set of attributes that influence bicycle route choice, including: (1) bicyclists’ characteristics, (2) on-street parking, (3) bicycle facility type and amenities, (4) roadway physical characteristics, (5) roadway functional characteristics, and (6) roadway operational characteristics. The data used in the analysis is drawn from a web-based stated preference survey of Texas bicyclists. The results of the study emphasize the importance of a comprehensive evaluation of both route-related attributes and bicyclists’ demographics in bicycle route choice decisions. The empirical results indicate that travel time (for commuters) and motorized traffic volume are the most important attributes in bicycle route choice. Other route attributes with a high impact include number of stop signs, red light, and cross-streets, speed limits, on-street parking characteristics, and whether there exists a continuous bicycle facility on the route.

Unlimited Access

Universities and public transit agencies have together invented an arrangement – called Unlimited Access – that provides fare-free transit service for over 825,000 people. The university typically pays the transit agency an annual lump sum based on expected student ridership, and students simply show their university identification to board the bus. This paper reports the results of a survey of Unlimited Access programs at 35 universities. University officials report that Unlimited Access reduces parking demand, increases students' access to the campus, helps to recruit and retain students, and reduces the cost of attending college. Transit agencies report that Unlimited Access increases ridership, fills empty seats, improves transit service, and reduces the operating cost per rider. Increases in student transit ridership ranged from 71 percent to 200 percent during the first year of Unlimited Access, and growth in subsequent years ranged from 2 percent to 10 percent per year. The universities' average cost for Unlimited Access is $30 per student per year.     

An analysis of weekly out-of-home discretionary activity participation and time-use behavior

Activity-travel behavior research has hitherto focused on the modeling and understanding of daily time use and activity patterns and resulting travel demand. In this particular paper, an analysis and modeling of weekly activity-travel behavior is presented using a unique multi-week activity-travel behavior data set collected in and around Zurich, Switzerland. The paper focuses on six categories of discretionary activity participation to understand the determinants of, and the inter-personal and intra-personal variability in, weekly activity engagement at a detailed level. A panel version of the Mixed Multiple Discrete Continuous Extreme Value model (MMDCEV) that explicitly accounts for the panel (or repeated-observations) nature of the multi-week activity-travel behavior data set is developed and estimated on the data set. The model also controls for individual-level unobserved factors that lead to correlations in activity engagement preferences across different activity types. To our knowledge, this is the first formulation and application of a panel MMDCEV structure in the econometric literature. The analysis suggests the high prevalence of intra-personal variability in discretionary activity engagement over a multi-week period along with inter-personal variability that is typically considered in activity-travel modeling. In addition, the panel MMDCEV model helped identify the observed socio-economic factors and unobserved individual specific factors that contribute to variability in multi-week discretionary activity participation.

Subsidized vehicle acquisition and earned income in the transition from welfare to work

Availability and affordability of reliable transportation – either through public transportation or individual ownership of automobiles – appears necessary to support a successful transition from welfare to work. One approach adopted by state and local governments is to subsidize vehicle acquisition by welfare recipients in transition. To date there are no empirical studies that analyze the impacts or effectiveness of these vehicle subsidy programs. The objective of this study is to examine the extent to which participation in a small-scale vehicle donation-and-sales program in Vermont increases earned income by individuals in transition from welfare to work. Using reduced-form random effects and censored regression models to account for the simultaneity of decisions to work and participate in welfare programs, we examine the impacts of this vehicle acquisition program for a small group of individuals. Our analyses indicate that the program results in a statistically significant increase in both earned income and the probability of employment.     

The relative contribution of transportation to supply chain greenhouse gas emissions: A case study of American wheat

This life cycle assessment case study puts the supply chain contribution of transportation to greenhouse gas emissions in context with other contributors using American wheat grain as a representative product. Multiple locations, species and routes to market are investigated. Transportation contributes 39–56% of the supply chain emissions, whereas there is a 101% intra-species and 62% inter-species variation in greenhouse gas emissions from production, demonstrating that transportation is both of smaller magnitude, and less sensitive than other factors, in particular, field sequestration.     

Energy-efficient operation of rail vehicles

This paper describes an analytical process that computes the optimal operating successions of a rail vehicle to minimize energy consumption. Rising energy prices and environmental concerns have made energy conservation a high priority for transportation operations. The cost of energy consumption makes up a large portion of the Operation and Maintenance (O&M) costs of transit especially rail transit systems. Energy conservation or reduction in energy cost may be one of the effective ways to reduce transit operating cost, therefore improve the efficiency of transit operations.From a theoretical point of view, the problem of energy efficient train control can be formulated as one of the functions of Optimal Control Theory. However, the classic numerical optimization methods such as discrete method of optimum programming are too slow to be used in an on-board computer even with the much improved computation power, today. The contribution of this particular research is the analytical solution that gives the sequence of optimal controls and equations to find the control change points. As a result, a calculation algorithm and a computer program for energy efficient train control has been developed. This program is also capable of developing energy efficient operating schedules by optimizing distributions of running time for an entire route or any part of rail systems.We see the major application of the proposed algorithms in fully or partially automated Train Control Systems. The modern train control systems, often referred as “positive” train control (PTC), have collected a large amount of information to ensure safety of train operations. The same data can be utilized to compute the optimum controls on-board to minimize energy consumption based on the algorithms proposed in this paper. Most of the input data, such as track plan, track profile, traction and braking characteristics, speed limits and required trip time are located in an on-board database and/or they can be transmitted via radio link to be processed by the proposed algorithm and program.     

A time series analysis of monthly ridership for an urban rail rapid transit line

This paper presents two time series regression models, one in linear form and the other in logarithmic form, to estimate the monthly ridership of a single urban rail rapid transit line. The model was calibrated for a time period of about six and a half years (from 1978–1984) based on ridership data provided by a transit authority, gasoline prices provided by a state energy department, and other data.The major findings from these models are: (1) seasonal variations of ridership are –6.26%, or –6.20% for the summer period, and 4.77%, or 4.62% for the October period; (2) ridership loss due to a station closure is 2.46% or 2.41%; and (3) elasticities of monthly ridership are –0.233 or –0.245 with respect to real fare, 0.113 or 0.112 with respect to real gasoline price, and 0.167 or 0.185 with respect to real bridge tolls for the competing automobile trips. Such route specific application results of this inexpensive approach provide significant implications for policymaking of individual programs in pricing, train operation, budgeting, system changes, etc., as they are in the case reported herein and would be in many other cities.