A Framework for and Empirical Study of Algorithms for Traffic Assignment

Traffic congestion is an issue in most cities worldwide. Transportation engineers and urban planners develop various tra c management projects in order to solve this issue. One way to evaluate such projects is traffic assignment (TA). The goal of TA is to predict the behaviour of road users for a given period of time (morning and evening peaks, for example). Once such a model is created, it can be used to analyse the usage of a road network and to predict the impact of implementing a potential project. The most commonly used TA model is known as user equilibrium, which is based on the assumption that all drivers minimise their travel time or generalised cost. In this study, we consider the static deterministic user equilibrium TA model. The constant growth of road networks and the need of highly precise solutions (required for select link analysis, network design, etc) motivate researchers to propose numerous methods to solve this problem. Our study aims to provide a recommendation on what methods are more suitable depending on available computational resources, time and requirements on the solution. In order to achieve this goal, we implement a flexible software framework that maximises usage of common code and, hence, ensures comparison of algorithms on common ground. In order to identify similarities and differences of the methods, we analyse groups of algorithms that are based on common principles. In addition, we implement and compare several different methods for solving sub-problems and discuss issues related to accumulated numerical errors that might occur when highly accurate solutions are required

A three-objective user equilibrium model:Time surplus maximisation under uncertainty

In this paper, we propose a user equilibrium model considering the three most important factors influencing route choice behaviour in a road network, namely, travel time, travel time reliability and monetary cost. We further develop the time surplus maximisation bi-objective user equilibrium (TSmaxBUE) model and incorporate the concept of travel time budget to model how users might react to uncertainty induced by day-to-day variability in travel time caused by traffic incidents. This results in a three-objective user equilibrium model, which has a possibly infinite set of equilibrium flows. To compute equilibrium flows, we introduce time budget surplus (TBS) defined as the maximum travel time a user is willing to spend minus the actual time budget required for a desired level of travel time reliability. At equilibrium, for each origin-destination (O-D) pair, all individuals are travelling on the path with the highest TBS value among all the efficient paths between this O-D pair. This becomes a time budget surplus maximisation three-objective user equilibrium model (TBSmaxTUE). We show that the TBSmaxTUE model is a special case of three-objective user equilibrium considering minimisation of expected travel time, travel time variance and toll (monetary cost) as objectives. We illustrate the model and our results on a small network

Potenciales beneficios del diseño de un sistema de rutas de transporte público colectivo urbano formulado a partir de un modelo matemático multiobjetivo aplicando algoritmos genéticos. Caso de estudio: Neiva, Huila

The urban collective public transport systems of the intermediate cities of Colombia have a strong risk trend in recent decades due, among other things, to structural and operational problems, generating significant damages for users, operators and society in general. Despite the above, the methods currently used in the medium for the design of these systems are "trial and error" test heuristics, which do not require that the solutions provided have adequate use of the resources available for the provision of a quality service. From this, the present research work proposed a multiobjective mathematical model, solved through the use of a genetic algorithm, through which it was possible to support the thesis that more optimized designs can be obtained through this type of tools , generating systems of greater operational efficiency and user service.Los sistemas de transporte público colectivo urbano de las ciudades intermedias de Colombia presentan una fuerte tendencia al deterioro en las últimas décadas debido, entre otros, a problemas de tipo estructural y operacional, generando importantes perjuicios para los usuarios, los operadores y la sociedad en general. A pesar de lo anterior, los métodos que actualmente se emplean en el medio para el diseño de estos sistemas son heurísticas de ensayo de “prueba y error”, que no garantizan que las soluciones brindadas permitan un aprovechamiento adecuado de los recursos disponibles para la prestación de un servicio de calidad. A partir de esto, el presente trabajo de investigación propuso un modelo matemático multiobjetivo, solucionado a través del uso de un algoritmo genético, mediante el cual fue posible sustentar la tesis de que se logran obtener diseños más optimizados a través de este tipo de herramientas, generando sistemas de mayor eficiencia operacional y de servicio al usuario.Línea de Investigación: Planificación del TransporteMaestrí

This is a repository copy of A Framework for and Empirical Study of Algorithms for Traffic Assignment. A Framework for and Empirical Study of Algorithms for Traffic Assignment

Abstract Traffic congestion is an issue in most cities worldwide. Transportation engineers and urban planners develop various traffic management projects in order to solve this issue. One way to evaluate such projects is traffic assignment (TA). The goal of TA is to predict the behaviour of road users for a given period of time (morning and evening peaks, for example). Once such a model is created, it can be used to analyse the usage of a road network and to predict the impact of implementing a potential project. The most commonly used TA model is known as user equilibrium, which is based on the assumption that all drivers minimise their travel time or generalised cost. In this study, we consider the static deterministic user equilibrium TA model. The constant growth of road networks and the need of highly precise solutions (required for select link analysis, network design, etc) motivate researchers to propose numerous methods to solve this problem. Our study aims to provide a recommendation on what methods are more suitable depending on available computational resources, time and requirements on the solution. In order to achieve this goal, we implement a flexible software framework that maximises usage of common code and, hence, ensures comparison of algorithms on common ground. In order to identify similarities and differences of the methods, we analyse groups of algorithms that are based on common principles. In addition, we implement and compare several different methods for solving sub-problems and discuss issues related to accumulated numerical errors that might occur when highly accurate solutions are required