A bi-level programming approach for trip matrix estimation and traffic control problems with stochastic user equilibrium link flows

This paper deals with two mathematically similar problems in transport network analysis: trip matrix estimation and traffic signal optimisation on congested road networks. These two problems are formulated as bi-level programming problems with stochastic user equilibrium assignment as the second-level programming problem. We differentiate two types of solutions in the combined matrix estimation and stochastic user equilibrium assignment problem (or, the combined signal optimisation and stochastic user equilibrium assignment problem): one is the solution to the bi-level programming problem and the other the mutually consistent solution where the two sub-problems in the combined problem are solved simultaneously. In this paper, we shall concentrate on the bi-level programming approach although we shall also consider mutually consistent solutions so as to contrast the two types of solutions. The purpose of the paper is to present a solution algorithm for the two bi-level programming problems and to test the algorithm on several networks

Microsimulation models incorporating both demand and supply dynamics

There has been rapid growth in interest in real-time transport strategies over the last decade, ranging from automated highway systems and responsive traffic signal control to incident management and driver information systems. The complexity of these strategies, in terms of the spatial and temporal interactions within the transport system, has led to a parallel growth in the application of traffic microsimulation models for the evaluation and design of such measures, as a remedy to the limitations faced by conventional static, macroscopic approaches. However, while this naturally addresses the immediate impacts of the measure, a difficulty that remains is the question of how the secondary impacts, specifically the effect on route and departure time choice of subsequent trips, may be handled in a consistent manner within a microsimulation framework. The paper describes a modelling approach to road network traffic, in which the emphasis is on the integrated microsimulation of individual trip-makers’ decisions and individual vehicle movements across the network. To achieve this it represents directly individual drivers’ choices and experiences as they evolve from day-to-day, combined with a detailed within-day traffic simulation model of the space–time trajectories of individual vehicles according to car-following and lane-changing rules and intersection regulations. It therefore models both day-to-day and within-day variability in both demand and supply conditions, and so, we believe, is particularly suited for the realistic modelling of real-time strategies such as those listed above. The full model specification is given, along with details of its algorithmic implementation. A number of representative numerical applications are presented, including: sensitivity studies of the impact of day-to-day variability; an application to the evaluation of alternative signal control policies; and the evaluation of the introduction of bus-only lanes in a sub-network of Leeds. Our experience demonstrates that this modelling framework is computationally feasible as a method for providing a fully internally consistent, microscopic, dynamic assignment, incorporating both within- and between-day demand and supply dynamic

Selected node-pair analysis in dial's assignment algorithm

An algorithm is proposed to calculate the matrix of trips which use a particular link in a road network or alternatively pass through a particular set of nodes given the route-splitting assumptions inherent in the Dial assignment algorithm.

A model of air pollution from road traffic, based on the characteristics of interrupted flow and junction control: Part II -- model results

In Part I of this paper (Matzoros and Van Vliet, 1992) the theoretical basis of a model which predicts air pollution emissions and concentrations from urban road networks was presented. In this part that model's results and sensitivity analysis are laid out. The model was tested under a wide range of conditions to pinpoint the variables that most affect its results in single links and real networks. Both pollutant concentrations at a range of receptor points and total link/network emissions were calculated and used in the comparisons. Link flow and capacity were identified as the two variables with the greatest effect. The location of the receptors with respect to both their distance from the roadway centerline as well as from the junction stop line was also found to be critical. Other important variables were wind speed and direction, while input emission rates had a linear effect on computed concentrations. The cycle time of signalised junctions had a variable effect on concentrations. Comparisons of modelled and observed values were made and are briefly reported here. The peakiness of the emission and concentration distributions of the pollutants was demonstrated using appropriate figures for both signalised and priority intersections. The model is intended to be used by traffic managers and transport analysts for scheme design and evaluation and for pollution prediction from road networks.

A model of air pollution from road traffic, based on the characteristics of interrupted flow and junction control: Part I -- model description

A computer model has been developed to tackle the problem of transport air pollution from urban networks. It consists of queueing, emission and dispersion models and takes vehicle operating modes (cruise, deceleration, queueing and acceleration) and their variable emission rates into account. Queue lengths at signalised, priority and roundabout intersections are specifically modelled. In this way the model predicts the spatial variability of emissions on urban roads: high pollution near junctions, levelling off towards mid-link points. The dispersion model uses empirical modifications to gaussian diffusion theory in order to account for the effects of moving vehicles on the turbulence of the air masses surrounding the roads. The model takes traffic data, emission rates and meteorological data and outputs air pollutant concentrations throughout a network in numerical and graphical form. The modelled pollutants are carbon monoxide, hydrocarbons, nitrogen oxides and lead. The model does not handle photochemical pollution.

Microsimulation models incorporating both demand and supply dynamics

There has been rapid growth in interest in real-time transport strategies over the last decade, ranging from automated highway systems and responsive traffic signal control to incident management and driver information systems. The complexity of these strategies, in terms of the spatial and temporal interactions within the transport system, has led to a parallel growth in the application of traffic microsimulation models for the evaluation and design of such measures, as a remedy to the limitations faced by conventional static, macroscopic approaches. However, while this naturally addresses the immediate impacts of the measure, a difficulty that remains is the question of how the secondary impacts, specifically the effect on route and departure time choice of subsequent trips, may be handled in a consistent manner within a microsimulation framework. The paper describes a modelling approach to road network traffic, in which the emphasis is on the integrated microsimulation of individual trip-makers' decisions and individual vehicle movements across the network. To achieve this it represents directly individual drivers' choices and experiences as they evolve from day-to-day, combined with a detailed within-day traffic simulation model of the space-time trajectories of individual vehicles according to car-following and lane-changing rules and intersection regulations. It therefore models both day-to-day and within-day variability in both demand and supply conditions, and so, we believe, is particularly suited for the realistic modelling of real-time strategies such as those listed above. The full model specification is given, along with details of its algorithmic implementation. A number of representative numerical applications are presented, including: sensitivity studies of the impact of day-to-day variability; an application to the evaluation of alternative signal control policies; and the evaluation of the introduction of bus-only lanes in a sub-network of Leeds. Our experience demonstrates that this modelling framework is computationally feasible as a method for providing a fully internally consistent, microscopic, dynamic assignment, incorporating both within- and between-day demand and supply dynamics.

A bi-level programming approach for trip matrix estimation and traffic control problems with stochastic user equilibrium link flows

This paper deals with two mathematically similar problems in transport network analysis: trip matrix estimation and traffic signal optimisation on congested road networks. These two problems are formulated as bi-level programming problems with stochastic user equilibrium assignment as the second-level programming problem. We differentiate two types of solutions in the combined matrix estimation and stochastic user equilibrium assignment problem (or the combined signal optimisation and stochastic user equilibrium assignment problem): one is the solution to the bi-level programming problem and the other the mutually consistent solution where the two sub-problems in the combined problem are solved simultaneously. In this paper, we shall concentrate on the bi-level programming approach, although we shall also consider mutually consistent solutions so as to contrast the two types of solutions. The purpose of the paper is to present a solution algorithm for the two bi-level programming problems and to test the algorithm on several networks.