Showing papers in "Transportation Research Part B-methodological in 2010"

Pre-positioning of emergency supplies for disaster response

Abstract: Pre-positioning of emergency supplies is one mechanism of increasing preparedness for natural disasters. The goal of this research is to develop an emergency response planning tool that determines the location and quantities of various types of emergency supplies to be pre-positioned, under uncertainty about if, or where, a natural disaster will occur. The paper presents a two-stage stochastic mixed integer program (SMIP) that provides an emergency response pre-positioning strategy for hurricanes or other disaster threats. The SMIP is a robust model that considers uncertainty in demand for the stocked supplies as well as uncertainty regarding transportation network availability after an event. Due to the computational complexity of the problem, a heuristic algorithm referred to as the Lagrangian L-shaped method (LLSM) is developed to solve large-scale instances of the problem. A case study focused on hurricane threat in the Gulf Coast area of the US illustrates application of the model.

Hypothetical bias, choice experiments and willingness to pay

Abstract: There is growing interest in establishing the extent of differences in willingness to pay (WTP) for attributes, such as travel time savings, that are derived from real market settings and hypothetical (to varying degrees) settings. Non-experiment external validity tests involving observation of choice activity in a natural environment, where the individuals do not know they are in an experiment, are rare. In contrast the majority of tests are a test of external validity between hypothetical and actual experiments. Deviation from real market evidence is referred to in the literature broadly as hypothetical bias. The challenge is to identify such bias, and to the extent to which it exists, establishing possible ways to minimise it. This paper reviews the efforts to date to identify and ‘calibrate’ WTP derived from one or more methods that involve assessment of hypothetical settings, be they (i) contingent valuation methods, (ii) choice experiments involving trading attributes between multiple alternatives, with or without referencing, or (iii) methods involving salient or non-salient incentives linked to actual behaviour. Despite progress in identifying possible contributions to differences in marginal WTP, there is no solid evidence, although plenty of speculation, to explain the differences between all manner of hypothetical experiments and non-experimental evidence. The absence of non-experimental evidence from natural field experiments remains a major barrier to confirmation of under or over-estimation. We find, however, that the role of referencing of an experiment relative to a real experience (including evidence from revealed preference (RP) studies), in the design of choice experiments, appears to offer promise in the derivation of estimates of WTP that have a meaningful link to real market activity, closing the gap between RP and SC WTP outputs.

The value of reliability

Abstract: We derive the value of reliability in the scheduling of an activity of random duration, such as travel under congested conditions. Using a simple formulation of scheduling utility, we show that the maximal expected utility is linear in the mean and standard deviation of trip duration, regardless of the form of the standardised distribution of trip durations. This insight provides a unification of the scheduling model and models that include the standard deviation of trip duration directly as an argument in the cost or utility function. The results generalise approximately to the case where the mean and standard deviation of trip duration depend on the starting time. An empirical illustration is provided.

Construction of experimental designs for mixed logit models allowing for correlation across choice observations

Abstract: In each stated choice (SC) survey, there is an underlying experimental design from which the hypothetical choice situations are determined. These designs are constructed by the analyst, with several different ways of constructing these designs having been proposed in the past. Recently, there has been a move from so-called orthogonal designs to more efficient designs. Efficient designs optimize the design such that the data will lead to more reliable parameter estimates for the model under consideration. The main focus has been on the multinomial logit model, however this model is unable to take the dependency between choice situations into account, while in a stated choice survey usually multiple choice situations are presented to a single respondent. In this paper, we extend the literature by focusing on the panel mixed logit (ML) model with random parameters, which can take the above mentioned dependency into account. In deriving the analytical asymptotic variance-covariance matrix for the panel ML model, used to determine the efficiency of a design, we show that it is far more complex than the cross-sectional ML model (assuming independent choice observations). Case studies illustrate that it matters for which model the design is optimized, and that it seems that a panel ML model SC experiment needs less respondents than a cross-sectional ML experiment for the same level of reliability of the parameter estimates.

A tabu search algorithm for rerouting trains during rail operations

Abstract: This paper addresses the problem of train conflict detection and resolution, which is dealt every day by traffic controllers to adapt the timetable to delays and other unpredictable events occurring in real-time. We describe a number of algorithmic improvements implemented in the real-time traffic management system ROMA (Railway traffic Optimization by Means of Alternative graphs), achieved by incorporating effective rescheduling algorithms and local rerouting strategies in a tabu search scheme. We alternate a fast heuristic and a truncated branch and bound algorithm for computing train schedules within a short computation time, and investigate the effectiveness of using different neighborhood structures for train rerouting. The computational experiments are based on practical size instances from a dispatching area of the Dutch railway network and include complex disturbances with multiple late trains and blocked tracks. Several small instances are solved to optimality in order to compare the heuristic solutions with the optimum. For small instances, the new tabu search algorithms find optimal solutions. For large instances, the solutions generated by the new algorithms after 20 s of computation are up to more than 15% better than those achieved within 180 s by the previous version of ROMA.

Induced demand and rebound effects in road transport

Abstract: This paper analyzes aggregate personal motor-vehicle travel within a simultaneous model of aggregate vehicle travel, fleet size, fuel efficiency, and congestion formation. We measure the impacts of driving costs on congestion, and two other well-known feedback effects affecting motor-vehicle travel: its responses to aggregate road capacity ("induced demand") and to driving costs including those caused by fuel-economy improvements ("rebound effect"). We measure these effects using cross-sectional time series data at the level of US states for 1966 through 2004. Results show that congestion affects the demand for driving negatively, as expected, and more strongly when incomes are higher. We decompose induced demand into effects from increasing overall accessibility of destinations and those from increasing urban capacity, finding the two elasticities close in magnitude and totaling about 0.16, somewhat smaller than most previous estimates. We confirm previous findings that the magnitude of the rebound effect decreases with income and increases with fuel cost, and find also that it increases with the level of congestion.

Incorporation of Lagrangian measurements in freeway traffic state estimation

Abstract: Cell-phones equipped with a global positioning system (GPS) provide new opportunities for location-based services and traffic estimation. When traveling on-board vehicles, these phones can be used to accurately provide position and velocity of the vehicle as probe traffic sensors. This article presents a new technique to incorporate mobile probe measurements into highway traffic flow models, and compares it to a Kalman filtering approach. These two techniques are both used to reconstruct traffic density. The first technique modifies the Lighthill–Whitham–Richards partial differential equation (PDE) to incorporate a correction term which reduces the discrepancy between the measurements (from the probe vehicles) and the estimated state (from the model). This technique, called Newtonian relaxation, “nudges” the model to the measurements. The second technique is based on Kalman filtering and the framework of hybrid systems, which implements an observer equation into a linearized flow model. Both techniques assume the knowledge of the fundamental diagram and the conditions at both boundaries of the section of interest. The techniques are designed in a way in which does not require the knowledge of on- and off-ramp detector counts, which in practice are rarely available. The differences between both techniques are assessed in the context of the Next Generation Simulation program (NGSIM), which is used as a benchmark data set to compare both methods. They are finally tested with data from the Mobile Century experiment obtained from 100 Nokia N95 mobile phones on I-880 in California on February 8, 2008. The results are promising, showing that the proposed methods successfully incorporate the GPS data in the estimation of traffic.

Structure of Competitive Transit Networks

Abstract: This paper describes the network shapes and operating characteristics that allow a transit system to deliver an accessibility level competitive with that of the automobile. To provide exhaustive results for service regions of different sizes and demographics, the paper idealizes these regions as squares with uniform demand, and their possible networks as a broad and realistic family that combines the grid and the hub-and-spoke concepts. The paper also shows how to use these results to generate master plans of transit systems for real cities. The analysis reveals which network structure and technology (Bus, Bus Rapid Transit, or Metro) delivers the desired performance with the least cost. It is found that the more expensive the system's infrastructure, the more it should tilt toward the hub-and-spoke concept. Bus Rapid Transit (BRT) competes effectively with the automobile unless a city is big and its demand low. This happens despite the uniform demand assumption, which penalizes collective transport. It is also found that if a city has enough suitable streets on which to run Bus and BRT systems, these outperform Metro even if the city is large and the demand high. Agency costs are always small compared with user costs; and both decline with the demand density. In all cases, increasing the spatial concentration of stops beyond a critical level increases both, the user and agency costs. Too much spatial coverage is counterproductive.

The α-reliable mean-excess traffic equilibrium model with stochastic travel times

Abstract: In this paper, we propose a new model called the α-reliable mean-excess traffic equilibrium (METE) model that explicitly considers both reliability and unreliability aspects of travel time variability in the route choice decision process. In contrast to the travel time budget (TTB) models that consider only the reliability aspect defined by TTB, this new model hypothesizes that travelers are willing to minimize their mean-excess travel times (METT) defined as the conditional expectation of travel times beyond the TTB. As a route choice criterion, METT can be regarded as a combination of the buffer time measure that ensures the reliability aspect of on-time arrival at a confidence level α , and the tardy time measure that represents the unreliability aspect of encountering worst travel times beyond the acceptable travel time allowed by TTB in the distribution tail of 1 − α . It addresses both questions of “ how much time do I need to allow? ” and “ how bad should I expect from the worse cases? ” Therefore, travelers’ route choice behavior can be considered in a more accurate and complete manner in a network equilibrium framework to reflect their risk preferences under an uncertain environment. The METE model is formulated as a variational inequality problem and solved by a route-based traffic assignment algorithm via the self-adaptive alternating direction method. Some qualitative properties of the model are rigorously proved. Illustrative examples are also presented to demonstrate the characteristics of the model as well as its differences compared to the recently proposed travel time budget models.

High-Speed Rail and Air Transport Competition: Game Engineering as Tool for Cost-Benefit Analysis

Abstract: This research develops a methodology to assess infrastructure investments and their effects on transport equilibria taking into account competition between multiple privatized transport operator types. The operators, including high-speed rail, hub-and-spoke legacy airlines and regional low-cost carriers, maximize best response functions via prices, frequency and train/plane sizes, given infrastructure provision, cost functions and environmental charges. The methodology is subsequently applied to all 27 European Union countries, specifically analyzing four of the prioritized Trans-European networks. The general conclusions suggest that the European Union, if interested in maximizing overall social welfare, should encourage the development of the high-speed rail network across Europe.

A Continuum Approximation Approach to Reliable Facility Location Design under Correlated Probabilistic Disruptions

Abstract: This paper studies the reliable uncapacitated fixed charge location problem (RUFL) where facilities are subject to spatially correlated disruptions that occur with location-dependent probabilities (due to reasons such as natural or man-made disasters). If a facility fails, its customers are diverted to other facilities and incur excessive transportation cost. We develop a continuum approximation (CA) model to minimize the sum of initial facility construction costs and expected customer transportation costs under normal and failure scenarios. The paper presents ways to formulate the correlation among adjacent facility disruptions, and incorporates such correlations into the CA model. Numerical experiments are conducted to illustrate how the proposed model can be used to optimize facility location design, and how the correlations influence the total system cost.

Three-phase traffic theory and two-phase models with a fundamental diagram in the light of empirical stylized facts

Abstract: Despite the availability of large empirical data sets and the long history of traffic modeling, the theory of traffic congestion on freeways is still highly controversial. In this contribution, we compare Kerner’s three-phase traffic theory with the phase diagram approach for traffic models with a fundamental diagram. We discuss the inconsistent use of the term “traffic phase” and show that patterns demanded by three-phase traffic theory can be reproduced with simple two-phase models, if the model parameters are suitably specified and factors characteristic for real traffic flows are considered, such as effects of noise or heterogeneity or the actual freeway design (e.g. combinations of off- and on-ramps). Conversely, we demonstrate that models created to reproduce three-phase traffic theory create similar spatiotemporal traffic states and associated phase diagrams, no matter whether the parameters imply a fundamental diagram in equilibrium or non-unique flow-density relationships. In conclusion, there are different ways of reproducing the empirical stylized facts of spatiotemporal congestion patterns summarized in this contribution, and it appears possible to overcome the controversy by a more precise definition of the scientific terms and a more careful comparison of models and data, considering effects of the measurement process and the right level of detail in the traffic model used.

Using Conditioning on Observed Choices to Retrieve Individual-Specific Attribute Processing Strategies

Abstract: With the growing reliance on Stated Choice (SC) data, researchers are increasingly interested in understanding how respondents process the information presented to them in such surveys. Specifically, it has been argued that some respondents may simplify the choice tasks by consistently ignoring one or more of the attributes describing the alternatives, and direct questions put to respondents after the completion of SC surveys support this hypothesis. However, in the general context of issues with response quality in SC data, there are certainly grounds for questioning the reliability of stated attribute processing strategies. In this paper, we take a different approach by attempting to infer attribute processing strategies through the analysis of respondent-specific coefficient distributions obtained through conditioning on observed choices. Our results suggest that a share of respondents do indeed ignore a subset of explanatory variables. However, there is also some evidence that the inferred attribute processing strategies are not necessarily consistent with the stated attribute processing strategies. Additionally, there is some evidence that respondents who claim to have ignored a certain attribute may simply have assigned it lesser importance. The results produced by the inferring approach not only lead to slightly better fit but also more consistent results.

Modeling and Solving the Tactical Berth Allocation Problem

Abstract: In this paper we integrate at the tactical level two decision problems arising in container terminals: the berth allocation problem, which consists of assigning and scheduling incoming ships to berthing positions, and the quay crane assignment problem, which assigns to incoming ships a certain QC profile (i.e. number of quay cranes per working shift). We present two formulations: a mixed integer quadratic program and a linearization which reduces to a mixed integer linear program. The objective function aims, on the one hand, to maximize the total value of chosen QC profiles and, on the other hand, to minimize the housekeeping costs generated by transshipment flows between ships. To solve the problem we developed a heuristic algorithm which combines tabu search methods and mathematical programming techniques. Computational results on instances based on real data are presented and compared to those obtained through a commercial solver.

Scheduling extra freight trains on railway networks

Abstract: We study the problem of freight transportation in railway networks, where both passenger and freight trains are run. While the passenger trains have a prescribed timetable that cannot be changed, freight train operators send the infrastructure manager requests to insert new freight trains. For each freight train, the associated train operator specifies a preferred ideal timetable , which can be modified by the infrastructure manager in order to respect safeness operational constraints. In particular, this modification may correspond to routing the train along a path which is different with respect to the one in the ideal timetable. Roughly speaking, the objective is to introduce as many new freight trains as possible by assigning them timetables that are as close as possible to the ideal ones. For this timetabling problem on a generic railway network, we present an integer linear programming formulation, that generalizes some formulations already presented for the case of a single railway line, and a Lagrangian heuristic based on this formulation. Computational results on real-world instances are reported.

Equilibria of Bilateral Taxi-customer Searching and Meeting on Networks

Abstract: This paper proposes an equilibrium model to characterize the bilateral searching and meeting between customers and taxis on road networks. A taxi driver searches or waits for a customer by considering both the expected searching or waiting time cost and ride revenue, and a customer seeks a taxi ride to minimize full trip price. We suppose that the bilateral taxi–customer searching and meeting occurs anywhere in residential and commercial zones or at prescribed taxi stands, such as an airport or a railway station. We propose a meeting function to spell out the search and meeting frictions that arise endogenously as a result of the distinct spatial feature of the area and the taxi–customer moving decisions. With the proposed meeting function and the assumptions underlying taxi–customer search behaviors, the stationary competitive equilibrium achieved at fixed fare prices is determined when the demand of the customers matches the supply of taxis or there is market clearing at the prevailing searching and waiting times in every meeting location. We establish the existence of such an equilibrium by virtue of Brouwer’s fixed-point theorem and demonstrate its principal operational characteristics with a numerical example.

Global Optimum of the Linearized Network Design Problem with Equilibrium Flows

Abstract: The road network design problem, typically formulated as a bi-level program or a mathematical program with equilibrium constraints, is generally non-convex. The non-convexity stems from both the traffic assignment equilibrium conditions and the non-linear travel time function. In this study, we formulate the network design problem as a single-level optimization problem with equilibrium constraints, and then we transform the equilibrium constraints into a set of mixed-integer constraints and linearize the travel time function. The final result is that we cast the network design problem with equilibrium flows into a mixed-integer linear program, whose solution possesses the desirable property of global optimality, subject to the resolution of the linearization scheme adopted.

Traffic Assignment by Paired Alternative Segments

Abstract: The static user-equilibrium (UE) traffic assignment model is widely used in practice. One main computational challenge in this model is to obtain sufficiently precise solutions suitable for scenario comparisons, as quickly as possible. An additional computational challenge stems from the need in practice to perform analyses based on route flows, which are not uniquely determined by the UE condition. Past research focused mainly on the first aspect. The purpose of this paper is to describe an algorithm that addresses both issues. The traffic assignment by paired alternative segments (TAPAS) algorithm, focuses on pairs of alternative segments as the key building block to the UE solution. A condition of proportionality, which is practically equivalent to entropy maximization, is used to choose one stable route flow solution. Numerical results for five publicly available networks, including two large-scale realistic networks, show that the algorithm can identify highly precise solutions that maintain proportionality in relatively short computation times.

A kinematic wave theory of lane-changing traffic flow

Abstract: Frequent lane-changes in highway merging, diverging, and weaving areas could disrupt traffic flow and, even worse, lead to accidents. In this paper, we propose a simple model for studying bottleneck effects of lane-changing traffic and aggregate traffic dynamics of a roadway with lane-changing areas. Based on the observation that, when changing its lane, a vehicle affects traffic on both its current and target lanes, we propose to capture such lateral interactions by introducing a new lane-changing intensity variable. With a modified fundamental diagram, we are able to study the impacts of lane-changing traffic on overall traffic flow. In addition, the corresponding traffic dynamics can be described with a simple kinematic wave model. For a location-dependent lane-changing intensity variable, we discuss kinematic wave solutions of the Riemann problem of the new model and introduce a supply-demand method for its numerical solutions. With both theoretical and empirical analysis, we demonstrate that lane-changes could have significant bottleneck effects on overall traffic flow. In the future, we will be interested in studying lane-changing intensities for different road geometries, locations, on-ramp/off-ramp flows, as well as traffic conditions. The new modeling framework could be helpful for developing ramp-metering and other lane management strategies to mitigate the bottleneck effects of lane-changes.

Assessing Spatial Equity and Efficiency Impacts of Transport Infrastructure Projects

Abstract: Policy decisions on transport infrastructure investments often require knowledge of welfare effects generated from using these infrastructures on a detailed regional level. This is in particular true for the EU initiative promoting the development of the trans-European transport (TEN-T) networks. As projects within this initiative affect regions in different countries, incentive compatible financing schemes cannot be designed without knowing where the benefits accrue. Furthermore, this initiative is also intended to contribute to the cohesion objective on a community scale, and only with regional impact studies one can assess to which extent these objectives are attained. As standard cost-benefit analysis is unable to assign benefits to eventual beneficiaries in the economy, we develop and apply a spatial computable general equilibrium (SCGE) model as a suitable alternative. The model has a household sector and a production sector with two industries, one producing local goods, the other producing tradables. Regions interact through costly trade, with trade costs depending, among others, on the state of the infrastructure. New links reduce trade costs, which changes trade flows, production, goods prices and factor prices and thus eventually the welfare of households in different regions. We present the formal structure of the model, the calibration procedure and the data sources for calibrating the model and estimating the trade cost reductions stemming from new transport links. As the model is only able to quantify effects related to trade in goods we also suggest a simplified approach to add effects stemming from passenger transport. We apply the methods to a policy experiment related to the TEN-T priority list of projects. We quantify project by project the social return, check whether significant benefit spillovers to countries not involved in financing might prevent realization of projects in spite of their respective profitability from European wide point of view, and finally we evaluate the contribution of each project to the spatial cohesion objective. Our results confirm sceptical views on EU involvement in infrastructure policy that have been expressed in the literature.

A link-based day-to-day traffic assignment model

Abstract: Existing day-to-day traffic assignment models are all built upon path flow variables. This paper demonstrates two essential shortcomings of these path-based models. One is that their application requires a given initial path flow pattern, which is typically unidentifiable, i.e. mathematically nonunique and practically unobservable. In particular, we show that, for the path-based models, different initial path flow patterns constituting the same link flow pattern generally gives different day-to-day link flow evolutions. The other shortcoming of the path-based models is the path-overlapping problem. That is, the path-based models ignore the interdependence among paths and thus can give very unreasonable results for networks with paths overlapping with each other. These two path-based problems exist for most (if not all) deterministic day-to-day dynamics whose fixed points are the classic Wardrop user equilibrium. To avoid the two path-based problems, we propose a day-to-day traffic assignment model that directly deals with link flow variables. Our link-based model captures travelers’ cost-minimization behavior in their path finding as well as their inertia. The fixed point of our link-based dynamical system is the classic Wardrop user equilibrium.

Robust congestion pricing under boundedly rational user equilibrium

Abstract: This paper investigates congestion pricing strategies in static networks with boundedly rational route choice behavior. Under such behavior, users do not necessarily choose a shortest or cheapest route when doing so does not reduce their travel times by a significant amount. A general path-based definition and a more restrictive link-based representation of boundedly rational user equilibrium (BRUE) are presented. The set of BRUE flow distributions is generally non-convex and non-empty. The problems of finding best- and worst-case BRUE flow distributions are formulated and solved as mathematical programs with complementarity constraints. Because alternative tolled BRUE flow distributions exist, our congestion pricing models seek a toll vector or pattern that minimizes the system travel time of the worst-case tolled BRUE flow distribution. As formulated, the models are generalized semi-infinite min–max problems and we propose a heuristic algorithm based on penalization and a cutting-plane scheme to solve them. Numerical examples are presented to illustrate key concepts and results.

Design of limited-stop services for an urban bus corridor with capacity constraints

Abstract: In high-demand bus networks, limited-stop services promise benefits for both users and operators, and have proven their attractiveness in systems such as Transmilenio (Bogota, Colombia) and Transantiago (Santiago, Chile). The design of these services involves defining their itinerary, frequency and vehicle size, yet despite the importance of these factors for the network’s efficiency, no published works appear to provide the tools for designing high-frequency unscheduled services on an urban bus corridor, minimizing social costs. This paper presents an optimization approach that minimizes these costs in terms of wait time, in-vehicle travel time and operator cost. Various optimization models are formulated that can accommodate the operating characteristics of a bus corridor, given an origin–destination trip matrix and a set of services that are a priori attractive. The models then determine which of these services should be offered at what frequencies and with which type of vehicles. A case study in which the model is applied to a real-world case of a bus corridor in the city of Santiago, Chile, is presented and the results are analyzed. Finally, the model is used on two different demand scenarios establishing which type of services tend to be good candidates on each case and providing preliminary insights on the impact of some key parameters.

A Multiple Discrete-Continuous Nested Extreme Value (MDCNEV) Model: Formulation and Application to Non-worker Activity Time-Use and Timing Behavior on Weekdays

Abstract: This paper develops a multiple discrete-continuous nested extreme value (MDCNEV) model that relaxes the independently distributed (or uncorrelated) error terms assumption of the multiple discrete-continuous extreme value (MDCEV) model proposed by Bhat [Bhat, C.R., 2005. A multiple discrete-continuous extreme value model: formulation and application to discretionary time-use decisions. Transportation Research Part B 39 (8), 679-707; Bhat, C.R., 2008. The multiple discrete-continuous extreme value (MDCEV) model: role of utility function parameters, identification considerations, and model extensions. Transportation Research Part B 42 (3), 274-303]. The MDCNEV model captures inter-alternative correlations among alternatives in mutually exclusive subsets (or nests) of the choice set, while maintaining the closed-form of probability expressions for any (and all) consumption pattern(s). The MDCNEV model is applied to analyze non-worker out-of-home discretionary activity time-use and activity timing decisions on weekdays using data from the 2000 San Francisco Bay Area data. This empirical application contributes to the literature on activity time-use and activity timing analysis by considering daily activity time-use behavior and activity timing preferences in a unified utility maximization-based framework. The model estimation results provide several insights into the determinants of non-workers' activity time-use and timing decisions. The MDCNEV model performs better than the MDCEV model in terms of goodness of fit. However, the nesting parameters are very close to 1, indicating low levels of correlation. Nonetheless, even with such low correlation levels, empirical policy simulations indicate non-negligible differences in policy predictions and substitution patterns exhibited by the two models. Experiments conducted using simulated data also corroborate this result.

Optimal traffic plate scanning location for OD trip matrix and route estimation in road networks

Abstract: During the last decade, there has been a substantial interest in how to determine the optimal number and locations of traffic counters for origin-destination (OD) trip matrices estimation. On the contrary, the optimal allocation of plate scanning devices has received very limited attention, even though several authors have demonstrated that plate scanning (route identification) techniques are much more informative than those based on traditional link count information. This paper provides techniques for obtaining the optimal number and location of plate scanning devices for a given prior OD distribution pattern under different situations, i.e. maximum route identifiability or budget constraints. Two rules analogous to the counting location problem are developed, and several integer linear programming models fulfilling these rules are proposed. The proposed methods are finally illustrated by their application into Nguyen-Dupuis and Cuenca networks.

Measurement and estimation of traffic oscillation properties

Abstract: The paper proposes a frequency spectrum analysis approach to improve measurements of traffic oscillation properties (e.g., periodicity, magnitude) from field data. The approach builds on standard signal processing techniques to effectively distinguish useful oscillation information from noise and nonstationary traffic trends. Compared with conventional time-domain methods, the proposed methodology systematically provides a range of information on oscillation properties. This paper also shows how to estimate oscillations experienced by drivers using detector data. Applications to real-world data from two sites show that the dominant oscillation period remains relatively invariant at each site when an oscillation propagates. Although the average oscillation periods displayed in detector data significantly vary across sites, the range of oscillations experienced by drivers are found to be more consistent.

Stability and attraction domains of traffic equilibria in a day-to-day dynamical system formulation

Abstract: We formulate the traffic assignment problem from a dynamical system approach. All exogenous factors are considered to be constant over time and user equilibrium is being pursued through a day-to-day adjustment process. The traffic dynamics is represented by a recurrence function, which governs the system evolution over time. Equilibrium stability and attraction domain are then analyzed by studying the topological properties of the system evolution. Stability is important because unstable equilibrium is transient. Even for stable equilibrium, only points within its attraction domain are attracted to the equilibrium. We show that the attraction domain of a stable equilibrium is always open. Furthermore, its boundary is formed by trajectories towards unstable equilibria. Through an understanding of these properties, computation schemes can be devised to determine the ranges of the attraction domains, as demonstrated in this study. Once this is accomplished, a partition chart can be drawn on the state space where each part represents the attraction domain of an equilibrium point. We trust that charting the attraction domains of user equilibria, as presented in this paper, will open up innovative ways for transportation network management.

Revenue sharing with multiple airlines and airports

Abstract: This paper investigates the effects of concession revenue sharing between an airport and its airlines. It is found that the degree of revenue sharing will be affected by how airlines’ services are related to each other (complements, independent, or substitutes). In particular, when carriers provide strongly substitutable services to each other, the airport has incentive to charge airlines, rather than to pay airlines, a share of concession revenue. In these situations, while revenue sharing improves profit, it reduces social welfare. It is further found that airport competition results in a higher degree of revenue sharing than would be had in the case of single airports. The airport–airline chains may nevertheless derive lower profits through the revenue-sharing rivalry, and the situation is similar to a Prisoners’ Dilemma. As the chains move further away from their joint profit maximum, welfare rises beyond the level achievable by single airports. The (equilibrium) revenue-sharing proportion at an airport is also shown to decrease in the number of its carriers, and to increase in the number of carriers at competing airports. Finally, the effects of a ‘pure’ sharing contract are compared to those of the two-part sharing contract. It is found that whether an airport is subject to competition is critical to the welfare consequences of alternative revenue sharing arrangements.

An improved ant colony optimization based algorithm for the capacitated arc routing problem

Abstract: The capacitated arc routing problem is a well-studied problem in the Transportation/Logistics/OR literature. The problem consists of identifying the minimum cost routes required to service (e.g., pickup or deliver) demand located along the edges of a network. Unfortunately, the problem belongs to the set of NP-Hard problems; consequently, numerous heuristic and metaheuristic solution approaches have been developed to solve it. In this article, an ant colony optimization based metaheuristic is presented. Modifications are introduced for various components of the ant colony metaheuristics; specifically for those associated with the “initial population”, the “ant decision rule” and the “local search procedure”. The new metaheuristic was tested on seven standard test networks for the capacitated arc routing problem. The results demonstrate that the proposed approach performs extremely well vis-a-vis the state-of-the-art metaheuristics for the problem.

A class of bush-based algorithms for the traffic assignment problem

Abstract: This paper studies a class of bush-based algorithms (BA) for the user equilibrium (UE) traffic assignment problem, which promise to produce highly precise solutions by exploiting acyclicity of UE flows. Each of the two building blocks of BA, namely the construction of acyclic sub-networks (bush) and the solution of restricted master problems (RMP), is examined and further developed. Four Newton-type algorithms for solving RMP, which can be broadly categorized as route flow and origin flow based, are presented, of which one is newly developed in this paper. Similarities and differences between these algorithms, as well as the relevant implementation issues are discussed in great details. A comprehensive numerical study is conducted using both real and randomly generated networks, which reveals that the relative performance of the algorithms is consistent with the analysis. In particular, the results suggest that swapping flows between shortest and longest route segments consistently outperforms other RMP solution techniques.