A bi‐level programming approach — Optimal transit fare under line capacity constraints

The fare of a transit line is one of the important decision variables for transit network design. It has been advocated as an efficient means of coordinating the transit passenger flows and of alleviating congestion in the transit network. This paper shows how transit fare can be optimized so as to balance the passenger flow on the transit network and to reduce the overload delays of passengers at transit stops. A bi‐level programming method is developed to optimize the transit fare under line capacity constraints. The upper‐level problem seeks to minimize the total network travel time, while the lower‐level problem is a stochastic user equilibrium transit assignment model with line capacity constraints. A heuristic solution algorithm based on sensitivity analysis is proposed. Numerical example is used to illustrate the application of the proposed model and solution algorithm.     

A capacity restraint transit assignment with elastic line frequency

This paper proposes a new formulation for the capacity restraint transit assignment problem with elastic line frequency, in which the line frequency is related to the passenger flows on transit lines. A stochastic user equilibrium transit assignment model with congestion and elastic line frequency is proposed and the equivalent mathematical programming problem is also formulated. Since the passenger waiting time and the line capacity are dependent on the line frequency, a fixed point problem with respect to the line frequency is devised accordingly. The existence of the fixed point problem has been proved. A solution algorithm for the proposed model is presented. Finally, a numerical example is used to illustrate the application of the proposed model and solution algorithm.     

Link choice proportions from trip distribution and assignment models: An overview and comparison

A number of estimation procedures have been suggested for the situation where a prior estimate of an origin-destination matrix is to be updated on the basis of recently-acquired traffic counts. These procedures assume that both the link flows and the proportionate usage of each link made by each origin-destination flow (referred to collectively as the link choice proportions) are known. This paper examines the possibility and methods for estimating the link choice proportions. Three methods are presented: (1) using ad hoc iteration between trip distribution and traffic assignment; (2) combining trip distribution and assignment in one step; (3) solving a new optimization problem in which the path flows are directly considered as variables and its optimal solution is governed by a logit type formula. The algorithms, covergencies and computational efficiencies of these methods are investigated. Results of testing the three methods on example networks are discussed.     

A regression model for bus running times in suburban areas of winnipeg

To plan new bus routes in suburban areas, expected bus running times on these routes are needed. Using most readily available relevant variables, a regression model is developed for estimating bus running times. The model is conceptually reasonable and it was tested using data other than that used for estimation.     

An empirical comparison of disaggregate category and regression trip generation analysis techniques

Category and regression household trip generation analysis techniques were compared and contrasted. The comparative research was facilitated through a discussion that revealed the interchangeability of two methods of calibrating a category model. While the cell mean method is simple to implement, it does not readily yield statistical indexes for comparison with regression models. The general linear model analysis of variance (GLANOVA) readily provides statistical indexes for the comparison of category and regression trip generation models, and it produces identical empirical results to the simpler cell mean approach of calibrating a category model.The empirical comparison supports the widespread use of category models for trip generation analysis in transportation planning studies. It was found that regression and category models yielded equivalent results for typical planning applications at the district level of aggregation. In addition, both techniques estimated overall trip rate with equal accuracy in the calibration phase, and the two approaches were indistinguishable with respect to sample size sensitivity. However, households with extremely large trip rates were underestimated to a greater degree by category models than regression models. This tendency, in turn, resulted in larger calibration coefficients of determination for regression models. Since the cell mean method of calibrating a model is simpler and easier to understand than a regression model representation, category models can be recommended over regression models for planning studies.     

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     

Modelling heavy vehicle car‐following behaviour in congested traffic conditions

This study develops a car‐following model in which heavy vehicle behaviour is predicted separately from passenger car. Heavy vehicles have different characteristics and manoeuvrability compared with passenger cars. These differences could create problems in freeway operations and safety under congested traffic conditions (level of service E and F) particularly when there is high proportion of heavy vehicles. With increasing numbers of heavy vehicles in the traffic stream, model estimates of the traffic flow could be degrades because existing car‐following models do not differentiate between these vehicles and passenger cars. This study highlighted some of the differences in car‐following behaviour of heavy vehicle and passenger drivers and developed a model considering heavy vehicles. In this model, the local linear model tree approach was used to incorporate human perceptual imperfections into a car‐following model. Three different real world data sets from a stretch of freeway in USA were used in this study. Two of them were used for the training and testing of the model, and one of them was used for evaluation purpose. The performance of the model was compared with a number of existing car‐following models. The results showed that the model, which considers the heavy vehicle type, could predict car‐following behaviour of drivers better than the existing models. Copyright © 2013 John Wiley & Sons, Ltd.     

Benthic community patterns reflect water column processes in the Northeast Water polynya (Greenland)

Benthic community patterns were investigated in the Northeast Water polynya (Greenland) during the summers of 1992 and 1993 to elucidate to what extent the bottom fauna is influenced by the dynamics of the overlying water. Five different fractions of the benthos (foraminiferans, nematodes, polychaetes, peracarid crustaceans, and epibenthic megafauna), ranging in average adult body size over 6 orders of magnitude (from about 100 μm to about 10 cm), were sampled quantitatively at 69 stations in water depths from 40 to 515 m. Total abundances of nematodes, polychaetes and peracarid crustaceans were found to be primarily correlated with parameters characterizing the potential benthic food supply (water column pigment and nitrate concentrations, sediment bound pigments and sediment biological activity), whereas abundances of foraminiferans and megabenthos were largely associated with seabed properties. Four benthic zones were distinguished by separately analyzing the faunistic composition and distribution of the five community fractions for Ob Bank, Western Westwind Trough, Eastern Westwind Trough, and Belgica Trough. This pattern was shown principally to reflect pelagic regimes differing in surface water hydrography, ice cover and euphotic productivity. This is the first time that a synoptic study of several benthic community portions spanning such a range in sizes and life styles has been performed in a polar shelf ecosystem. Our results indicate that abundances as well as composition of Arctic benthos are largely influenced by mesoscale pelagic processes, and thus provide further evidence for the importance of the benthic-pelagic coupling in high latitude seas.