An integrated framework for embedding large-scale dynamic traffic assignment models in advanced traveler information systems

In recent years, increasing attention has been drawn to the development of various applications of intelligent transportation systems (ITS), which are credited with the amelioration of traffic conditions in urban and regional environments. Advanced traveler information systems (ATIS) constitute an important element of ITS by providing potential travelers with information on the network's current performance both en-route and pre-trip. In order to tackle the complexity of such systems, derived from the difficulty of providing real-time estimations of current as well as forecasts of future traffic conditions, a series of models and algorithms have been initiated. This paper proposes the development of an integrated framework for real-time ATIS and presents its application on a large-scale network, that of Thessaloniki, Greece, concluding with a discussion on development and implementation challenges as well as on the advantages and limitations of such an effort.     

A dynamic traffic assignment model for a continuum transportation system

A predictive continuum dynamic user-optimal (PDUO-C) model is formulated in this study to investigate the dynamic characteristics of traffic flow and the corresponding route-choice behavior of travelers within a region with a dense urban road network. The modeled region is arbitrary in shape with a single central business district (CBD) and travelers continuously distributed over the region. Within this region, the road network is represented as a continuum and travelers patronize a two-dimensional continuum transportation system to travel to the CBD. The PDUO-C model is solved by a promising solution algorithm that includes elements of the finite volume method (FVM), the finite element method (FEM), and the explicit total variation diminishing Runge-Kutta (TVD-RK) time-stepping method. A numerical example is given to demonstrate the utility of the proposed model and the effectiveness of the solution algorithm in solving this PDUO-C problem.     

Multiple equilibria in a dynamic traffic network

This study provides an example in which the dynamic user equilibrium (DUE) assignment of a congested road network with bottlenecks is non-unique. In previous studies, the uniqueness of DUE assignments with the bottleneck model has been shown in limited cases such as single-origin and single-destination networks. Consequently, it is still an important issue whether or not uniqueness is a general property of DUE assignments. The present study describes a network in which multiple patterns of link travel time are found, thus providing a negative answer to this question. The network has a loopy structure with multiple bottlenecks and multiple origin-destination (OD) pairs. Given a certain demand pattern of departure times for vehicles leaving their origins, a non-convex set of equilibria with a non-unique pattern of link travel times is shown to exist.     

Multi-commodity traffic assignment by continuum approximation of network flow with variable demand

Consider a city with several highly compact central business districts (CBD), and the commuters’ destinations from each of them are dispersed over the whole city. Since at a particular location inside the city the traffic movements from different CBDs share the same space and do not cancel out each other as in conventional fluid flow problems albeit travelling in different directions, the traffic flows from a CBD to the destinations over the city are considered as one commodity. The interaction of the traffic flows among different commodities is governed by a cost–flow relationship. The case of variable demand is considered. The primal formulation of the continuum equilibrium model is given and proved to satisfy the user optimal conditions, and the dual formulation of the problem and its complementary conditions are also discussed. A finite element method is then employed to solve the continuum problem. A numerical example is given to illustrate the effectiveness of the proposed method.     

Validation of a schedule‐based capacity restraint transit assignment model for a large‐scale network

This paper describes the application of a capacity restraint trip assignment algorithm to a real, large‐scale transit network and the validation of the results. Unlike the conventional frequency‐based approach, the network formulation of the proposed model is dynamic and schedule‐based. Transit vehicles are assumed to operate to a set of pre‐determined schedules. Passengers are assumed to select paths based on a generalized cost function including in‐vehicle and out‐of‐vehicle time and line change penalty. The time‐varying passenger demand is loaded onto the network by a time increment simulation method, which ensures that the capacity restraint of each vehicle during passenger boarding is strictly observed. The optimal‐path and path‐loading algorithms are applied iteratively by the method of successive averages until the network converges to the predictive dynamic user equilibrium. The Hong Kong Mass Transit Railway network is used to validate the model results. The potential applications of the model are also discussed.     

An equilibrium algorithm for the spatial aggregation problem of traffic assignment

Present traffic assignment methods require that all possible origins and destinations of trips taking place within a study area be represented as if they were taking place to and from a small set of points or centroids. Each centroid is supposed to represent the location of all trip-ends within a given zone, and this necessarily misrepresents points located at the edges of the zone.In order to alleviate this problem (which we refer to as the spatial aggregation problem) one could use smaller zones and more centroids, but existing traffic assignment algorithms cannot efficiently handle many centroids.This paper introduces an algorithm procedure which is designed to handle a substantially larger number of centroids. In the paper that follows, the technique is further developed to take into account a continuous distribution of population.     

A cell-based Merchant-Nemhauser model for the system optimum dynamic traffic assignment problem

A cell-based variant of the Merchant-Nemhauser (M-N) model is proposed for the system optimum (SO) dynamic traffic assignment (DTA) problem. Once linearized and augmented with additional constraints to capture cross-cell interactions, the model becomes a linear program that embeds a relaxed cell transmission model (CTM) to propagate traffic. As a result, we show that CTM-type traffic dynamics can be derived from the original M-N model, when the exit-flow function is properly selected and discretized. The proposed cell-based M-N model has a simple constraint structure and cell network representation because all intersections and cells are treated uniformly. Path marginal costs are defined using a recursive formula that involves a subset of multipliers from the linear program. This definition is then employed to interpret the necessary condition, which is a dynamic extension of the Wardrop’s second principle. An algorithm is presented to solve the flow holding back problem that is known to exist in many discrete SO-DTA models. A numerical experiment is conducted to verify the proposed model and algorithm.     

An assignment model with modified Logit,which obviates enumeration and overlapping problems

One of the main components of stochastic assignment models is the route choice model solved with implicit or explicit path enumeration algorithms. Such models are used both for congested networks within equilibrium or dynamic models and for non-congested networks within static or pseudo-dynamic network loading models. This paper proposes a C-Logit model specification within a Dial algorithm structure for the implicit assignment of network flows. The model and its solution algorithm, called D-C-Logit, combine several positive features found in the literature for choice set generation and choices from a given choice set: generation of a set of alternatives with a selective approach; calculation of the path choice probability in a closed form; simulation of the overlapping effect among alternative paths; computation of just one tree for each origin avoiding explicit path enumeration.This paper has two main objectives: the proposition of a Dial-like algorithm to solve a C-Logit assignment model and application of the algorithm to different networks in order to demonstrate certain properties.     

Dynamic user equilibrium with side constraints for a traffic network: Theoretical development and numerical solution algorithm

This paper investigates a traffic volume control scheme for a dynamic traffic network model which aims to ensure that traffic volumes on specified links do not exceed preferred levels. The problem is formulated as a dynamic user equilibrium problem with side constraints (DUE-SC) in which the side constraints represent the restrictions on the traffic volumes. Travelers choose their departure times and routes to minimize their generalized travel costs, which include early/late arrival penalties. An infinite-dimensional variational inequality (VI) is formulated to model the DUE-SC. Based on this VI formulation, we establish an existence result for the DUE-SC by showing that the VI admits at least one solution. To analyze the necessary condition for the DUE-SC, we restate the VI as an equivalent optimal control problem. The Lagrange multipliers associated with the side constraints as derived from the optimality condition of the DUE-SC provide the traffic volume control scheme. The control scheme can be interpreted as additional travel delays (either tolls or access delays) imposed upon drivers for using the controlled links. This additional delay term derived from the Lagrange multiplier is compared with its counterpart in a static user equilibrium assignment model. If the side constraint is chosen as the storage capacity of a link, the additional delay can be viewed as the effort needed to prevent the link from spillback. Under this circumstance, it is found that the flow is incompressible when the link traffic volume is equal to its storage capacity. An algorithm based on Euler’s discretization scheme and nonlinear programming is proposed to solve the DUE-SC. Numerical examples are presented to illustrate the mechanism of the proposed traffic volume control scheme.     

多方式多类型交通分配模型(MMA)在收费型公路网中的应用研究

在对收费型公路运营模式进行研究的基础上,利用交通规划软件建立了基于广义费用的交通流量分配模型即多方式多类型交通分配模型,通过对模型参数的科学标定和网络的合理设置,得到各类车型在特定网络上的流量分配、路段饱和率以及通行费用,并对此模型的应用效果进行分析,最终为区域高速公路网规划、路段交通量预测提供依据。     

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.     

An improved cellular automata model for heterogeneous work zone traffic

This paper aims to develop an improved cellular automata (ICA) model for simulating heterogeneous traffic in work zone. The proposed ICA model includes the forwarding rules to update longitudinal speeds and positions of work zone vehicles. The randomization probability parameter used by the ICA is formulated as a function of the activity length, the transition length and the volumes of different types of vehicles traveling across work zone. Compared to the existing cellular automata models, the ICA model possesses a novel and realistic lateral speed and position updating rule so that the simulation of vehicle’s lateral movement in work zone is close to the reality. The ICA model is calibrated and validated microscopically and macroscopically by using the real work zone data. Comparisons of field data and ICA for trajectories, speed and speed–flow relationship in work zone show very close agreement. Finally, the proposed ICA model is applied to estimate traffic delay occurred in work zone.     

An investigation of the reliability of real-time information for route choice decisions in a congested traffic system

This paper investigates the reliability of information on prevailing trip times on the links of a network as a basis for route choice decisions by individual drivers. It considers a type of information strategy in which no attempt is made by some central controller or coordinating entity to predict what the travel times on each link would be by the time it is reached by a driver that is presently at a given location. A specially modified model combining traffic simulation and path assignment capabilities is used to analyze the reliability of the real-time information supplied to the drivers. This is accomplished by comparing the supplied travel times (at the link and path levels) to the actual trip times experienced in the network after the information has been given. In addition, the quality of the decisions made by drivers on the basis of this information (under alternative path switching rules) is evaluated ex-post by comparing the actually experienced travel time (given the decision made) to the time that the driver would have experienced without the real-time information. Results of a series of simulation experiments under recurrent congestion conditions are discussed, illustrating the interactions between information reliability and user response.     

Analyzing the impact of a planned transit-oriented development on mode share and traffic conditions

ABSTRACT

Transit-oriented development (TOD) is a popular planning strategy used to maximize accessibility to transit for various trip purposes. The quantitative effects of TOD on travel mode shift and traffic congestion have not been extensively tested in the current literature. This paper utilizes a seemingly unrelated regressions (SUR) mode share model and a mesoscopic dynamic traffic assignment (DTA) model to analyze the impact of a planned TOD in Maryland. The proposed model aims at improving the understanding of the quantitative impacts of such a TOD on mode share and traffic congestion. The main result of the mode share model indicates that the increase in transit ridership for a transit accessible shopping center is not that significant. Local traffic conditions will deteriorate due to a lack of investment in road infrastructure planned for the TOD area. The proposed method could be a valuable tool for other indicative land development or transportation policy analyses.     

An appraisal of a column-generation-based algorithm for centralized train-conflict resolution on a metropolitan railway network

In practice, a train-conflict resolution is decentralized around dispatchers each of whom controls a few segments in a global railway network with her rule-of-thumb to operational data. Conceptually, the global sub-optimality or infeasibility of the decentralized system is resolved by a network controller who coordinates the dispatchers and train operators at the lower layers on a real-time basis. However, such notion of a multi-layer system cannot be effectual unless the top layer is able to provide a global solution soon enough for the dynamic lower layers to adapt in a seamless manner. Unfortunately, a train-conflict resolution problem is NP-hard as formally established in this paper and an effective solution method traded off between computation time and solution quality has been lacking in literature. Thus, we propose a column-generation-based algorithm that exploits the separability of the problem. A key ingredient of the algorithm is an efficient heuristic for the pricing subproblem for column generation. Tested on the real data from the Seoul metropolitan railway network, the algorithm provides near-optimal conflict-free timetables in a few seconds for most cases. The performance of the proposed algorithm is compared to the ones of the previous MIP-based heuristic by Törnquist and Persson (2007) and the priority-based heuristic by Sahin (1999).     

First-best marginal cost toll for a traffic network with stochastic demand

First-best marginal cost pricing (MCP) in traffic networks has been extensively studied with the assumption of deterministic travel demand. However, this assumption may not be realistic as a transportation network is exposed to various uncertainties. This paper investigates MCP in a traffic network under stochastic travel demand. Cases of both fixed and elastic demand are considered. In the fixed demand case, travel demand is represented as a random variable, whereas in the elastic demand case, a pre-specified random variable is introduced into the demand function. The paper also considers a set of assumptions of traveler behavior. In the first case, it is assumed that the traveler considers only the mean travel time in the route choice decision (risk-neutral behavior), and in the second, both the mean and the variance of travel time are introduced into the route choice model (risk-averse behavior). A closed-form formulation of the true marginal cost toll for the stochastic network (SN-MCP) is derived from the variational inequality conditions of the system optimum and user equilibrium assignments. The key finding is that the calculation of the SN-MCP model cannot be made by simply substituting related terms in the original MCP model by their expected values. The paper provides a general function of SN-MCP and derives the closed-form SN-MCP formulation for specific cases with lognormal and normal stochastic travel demand. Four numerical examples are explored to compare network performance under the SN-MCP and other toll regimes.     

Hybrid artificial neural network and locally weighted regression models for lane-based short-term urban traffic flow forecasting

ABSTRACT

In recent years, there has been considerable research interest in short-term traffic flow forecasting. However, forecasting models offering a high accuracy at a fine temporal resolution (e.g. 1 or 5?min) and lane level are still rare. In this study, a combination of genetic algorithm, neural network and locally weighted regression is used to achieve optimal prediction under various input and traffic settings. The genetically optimized artificial neural network (GA-ANN) and locally weighted regression (GA-LWR) models are developed and tested, with the former forecasting traffic flow every 5-min within a 30-min period and the latter for forecasting traffic flow of a particular 5-min period of each for four lanes of an urban arterial road in Beijing, China. In particular, for morning peak and off-peak traffic flow prediction, the GA-ANN 5-min traffic flow model results in average errors of 3–5% and most 95th percentile errors of 7–14% for each of the four lanes; for the peak and off-peak time traffic flow predictions, the GA-LWR 5-min traffic flow model results in average errors of 2–4% and most 95th percentile errors are lower than 10% for each of the four lanes. When compared to previous models that usually offer average errors greater than 6–15%, such empirical findings should be of interest to and instrumental for transportation authorities to incorporate in their city- or state-wide Advanced Traveller Information Systems (ATIS).     

An epsilon-optimal algorithm considering greenhouse gas emissions for the management of a ship’s bunker fuel

This paper provides an algorithm to minimize the fixed ordering, purchase, and inventory-carrying costs associated with bunker fuel together with ship time costs; and environmental costs associated with greenhouse gas emissions. It determines the optimum ship speed, bunkering ports, and amounts of bunker fuel for a given ship’s route. To solve the problem, we use an epsilon-optimal algorithm by deriving a property. The algorithm is illustrated by applying it to typical sample data obtained and the effects of bunker prices, carbon taxes, and ship time costs on the ship speed are analyzed. The results indicate that the ship speed and CO₂ emissions are highly sensitive to the factors considered.