A mesoscopic traffic simulation based dynamic traffic assignment

XII Premio Abertis en gestión de infraestructuras de Transporte en la modalidad de tesis doctoral, 2014In terms of sustainability, traffic is currently a significant challenge for urban areas, where the pollution, congestion and accidents are negative externalities which have strongly impacted the health and economy of cities. The increasing use of private vehicles has further exacerbated these problems. In this context, the development of new strategies and policies for sustainable urban transport has made transport planning more relevant than ever before. Mathematical models have helped greatly in identifying solutions, as well as in enriching the process of making decisions and planning. In particular, dynamic network models provide a means for representing dynamic traffic behavior; in other words, they provide a temporally coherent means for measuring the interactions between travel decisions, traffic flows, travel time and travel cost. This thesis focuses on dynamic traffic assignment (DTA) models. DTA has been studied extensively for decades, but much more so in the last twenty years since the emergence of Intelligent Transport Systems (ITS). The objective of this research is to study and analyze the prospects for improving this problem. In an operational context, the objective of DTA models is to represent the evolution of traffic on a road network as conditions change. They seek to describe the assignment of the demand on different paths which connect every OD pair in a state of equilibrium. The behaviour following each individual decision during a trip is a time-dependent generalization of Wardrop's First Principle, the Dynamic User Equilibrium (DUE). This hypothesis is based on the following idea: When current travel times are equal and minimal for vehicles that depart within the same time interval , the dynamic traffic flow through the network is in a DUE state based on travel times for each OD pair at each instant of time ([ran-1996]). This work begins with the time-continuous variational inequalities model proposed by [friesz-1993] for solving the DUE problem. Different solutions can be used on the proposed DUE formulation. On the one hand, there are the so-called analytical approaches which use known mathematical optimization techniques for solving the problem directly. On the other hand, there are simulation-based formulations that approximate heuristic solutions at a reasonable computational cost. While analytical models concentrate mainly on deriving theoretical insights, simulation-based models focus on trying to build practical models for deployment in real networks. Thus, because the simulation-based formulation holds the most promise, we work on that approach in this thesis. In the field of simulation-based DTA models, significant progress has been made by many researchers in recent decades. Our simulation-based formulation separates the proposed iterative process into two main components: - A method for determining the new time dependent path flows by using the travel times on these paths experienced in the previous iteration. - A dynamic network loading (DNL) method, which determines how these paths flow propagate along the corresponding paths. However, it is important to note that not all computer implementations based on this algorithmic framework provide solutions that obtain DUE. Therefore, while we analyze both proposals in this thesis we focus on the preventive methods of flow reassignment because only those can guarantee DUE solutions. Our proposed simulation-based DTA method requires a DNL component that can reproduce different vehicle classes, traffic light controls and lane changes. Therefore, this thesis develops a new multilane multiclass mesoscopic simulation model with these characteristics, which is embedded into the proposed DUE framework. Finally, the developed mesoscopic simulation-based DTA approach is validated accordingly. The results obtained from the computational experiments demonstrate that the developed methods perform well.En los últimos tiempos, el problema del tráfi co urbano ha situado a las áreas metropolitanas en una difícil situación en cuanto a sostenibilidad se refi ere (en términos de la congestión, los accidentes y la contaminación). Este problema se ha visto acentuado por la creciente movilidad promovida por el aumento del uso del vehículo privado. Además, debido a que la mayor parte del trá fico es canalizada a través de los modos de carretera, el tiempo perdido por los usuarios al realizar sus viajes tiene un importante efecto económico sobre las ciudades. En este contexto, la plani cación de transporte se vuelve relevante a través del desarrollo de nuevas estrategias y políticas para conseguir un transporte urbano sostenible. Los modelos matemáticos son de gran ayuda ya que enriquecen las decisiones de los gestores de trá fico en el proceso de plani ficación. En particular podemos considerar los modelos de trá fico para la predicción, como por ejemplo los modelos de asignación dinámica de tráfi co (ADT), los cuales proveen de una representación temporal coherente de las interacciones entre elecciones de trá fico, fl ujos de trá fico y medidas de tiempo y coste. Esta tesis se centra en los modelos ADT. Durante las últimas décadas, los modelos ADT han sido intensamente estudiados. Este proceso se ha acelerado particularmente en los últimos veinte años debido a la aparición de los Sistemas Inteligentes de Transporte. El objetivo de esta investigación es estudiar y analizar diferentes posibilidades de mejorar la resolución del problema. En un contexto operacional, el objetivo de los modelos ADT es representar la evolución de la red urbana cuando las condiciones de trá fico cambian. Estos modelos tratan de describir la asignación de la demanda en los diferentes caminos que conectan los pares OD siguiendo un estado de equilibrio. En este caso se ha considerado que el comportamiento de los conductores en cada una de sus decisiones individuales tomadas durante el viaje es una generalización dependiente del tiempo del Primer Principio de Wardrop, denominada Equilibrio Dinámico de Usuario (EDU). Esta hipótesis se basa en la siguiente idea: para cada par OD para cada instante de tiempo, si los tiempos de viaje de todos los usuarios que han partido en ese intervalo de tiempo son iguales y mínimos, entonces el ujo dinámico de trá fico en la red se encuentra en un estado de EDU basado en los tiempos de viaje (Ran and Boyce (1996)). El presente trabajo toma como punto de partida el modelo de inecuaciones variacionales continuo en el tiempo propuesto por Friesz et al. (1993) para resolver el problema de equilibrio dinámico de usuario. Por un lado, se encuentran los denominados enfoques analíticos que utilizan técnicas matemáticas de optimización para resolver el problema directamente. Por otro lado, están los modelos cuyas formulaciones están basadas en simulación que aproximan soluciones heurísticas con un coste computacional razonable. Mientras que modelos analíticos se concentran principalmente en demostrar las propiedades teóricas, los modelos basados en simulación se centran en intentar construir modelos que sean prácticos para su utilización en redes reales. Así pues, debido a que las formulaciones basadas en simulación son las que se muestran más prometedoras a la práctica, en esta tesis se ha elegido este enfoque para tratar el problema ADT. En los últimos tiempos, el campo de los modelos ADT basados en simulación ha sido de especial interés. Nuestra formulación basada en simulación consiste en un proceso iterativo que consta de dos componentes principales, sistematizadas por Florian et al. (2001) como sigue: Un método para determinar los nuevos ujos (dependientes del tiempo) en los caminos utilizando los tiempos de viaje experimentados en esos caminos en la iteración previa. Un procedimiento de carga dinámica de la red (CDR) que determine cómo esos fl ujos se propagan a través de sus correspondientes caminos. Los algoritmos de reasignación de flujo pueden ser agrupados en dos categorías: preventivos y reactivos. Es importante notar aquí que no todas las implementaciones computacionales basadas en el marco algorítmico propuesto proporcionan una solución EDU. Por lo tanto, aunque en esta tesis analizamos ambas propuestas, nos centraremos en los métodos preventivos de reasignación de flujo porque son los que nos garantizan alcanzar la hipótesis considerada (EDU). Además, nuestro modelo ADT basado en simulación requiere de una componente de CDR que pueda reproducir diferentes clases de vehículos, controles semafóricos y cambios de carril. Así, uno de los objetivos de esta tesis es desarrollar un nuevo modelo de simulación de trá fico con dichas características (multiclase y multicarril), teniendo en cuenta que será una de las componentes principales del marco ADT propuesto.Award-winningPostprint (published version

Analysis and operational challenges of dynamic ride sharing demand responsive transportation models

There is a wide body of evidence that suggests sustainable mobility is not only a technological question, but that automotive technology will be a part of the solution in becoming a necessary albeit insufficient condition. Sufficiency is emerging as a paradigm shift from car ownership to vehicle usage, which is a consequence of socio-economic changes. Information and Communication Technologies (ICT) now make it possible for a user to access a mobility service to go anywhere at any time. Among the many emerging mobility services, Multiple Passenger Ridesharing and its variants look the most promising. However, challenges arise in implementing these systems while accounting specifically for time dependencies and time windows that reflect users’ needs, specifically in terms of real-time fleet dispatching and dynamic route calculation. On the other hand, we must consider the feasibility and impact analysis of the many factors influencing the behavior of the system – as, for example, service demand, the size of the service fleet, the capacity of the shared vehicles and whether the time window requirements are soft or tight. This paper analyzes - a Decision Support System that computes solutions with ad hoc heuristics applied to variants of Pick Up and Delivery Problems with Time Windows, as well as to Feasibility and Profitability criteria rooted in Dynamic Insertion Heuristics. To evaluate the applications, a Simulation Framework is proposed. It is based on a microscopic simulation model that emulates real-time traffic conditions and a real traffic information system. It also interacts with the Decision Support System by feeding it with the required data for making decisions in the simulation that emulate the behavior of the shared fleet. The proposed simulation framework has been implemented in a model of Barcelona’s Central Business District. The obtained results prove the potential feasibility of the mobility concept.Postprint (published version

Analysis and operational challenges of dynamic ride sharing demand responsive transportation models

© . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/There is a wide evidence that sustainable mobility is not only a technological question, automotive technology will be part of the solution as a necessary but not sufficient condition, sufficiency is emerging as a combination of a paradigm shift from car ownership to vehicle usage consequence of socio-economic changes, withthe application of Information and Communication Technologies (ICT) that make possible for a userto have access to a mobility service from anywhere to anywhere at any time. Among the many emergent mobility services Multiple Passenger Ridesharing and its variants look the more promising. However, implementations of these systems accounting specifically for time dependencies, and time windows reflecting users’ needs raise challenges in terms of real-time fleet dispatching and dynamic route calculation. On the other handthe feasibility and impacts analysis in terms of the many factors influencing the behavior of the system, as for example the service demand, the size of the service fleet, the capacity of the shared vehicles, the time windows requirements, soft or tight. This paper analyzes both aspects. The first is approached in terms of a Decision Support System whose solutions are computed in terms of ad hoc heuristics of variants of Pick Up and Delivery Problems with Time Windows and Feasibility and Profitability criteria rooted on Dynamic Insertion Heuristics. For the evaluation of the applications a Simulation Framework is proposed based on a microscopic simulation model thatemulates real-time traffic conditions and a real traffic information system, and interacts with the Decision Support System feeding it with the required data to make the decisions that are implemented in the simulation to emulate the behavior of the shared fleet. The proposed simulation framework has been implemented in a model of Barcelona’s Central Business District. The paper is completed with the discussion of the achieved resultsPeer ReviewedPostprint (published version

A traffic simulation tool for assessing smart city policies (CitScale)

Over the last century, cities have developed as a function of increased usage of automobiles as the standard transport mode. The number of cars increased along with the population as highways and parking spots became essential in city planning. Now, there is more focus on how the existing infrastructure could be used as efficiently as possible rather than increasing capacity by merely building new roads. An important part of traffic planning is a sustainable transport system, which thereby reduces congestion and emissions by using the available capacity in a more efficient way. Traffic simulation models are tools for assessing new mobility solutions and analysing changes in the infrastructure, such as rearranging intersections and building new roads. Transportation is undergoing a profound and significant transformation as it seeks to fulfil the promise of connected mobility for people and goods while limiting its carbon footprint. Physical changes to the road network mean large investments that must be comprehensively considered before acting. Modelling different scenarios of infrastructural changes allows making forecasts without any physical changes. Autonomous vehicles are potentially changing the economics of ownership as well as the use of the transportation networks, which will likely accelerate trends towards greater use of app-based ride hailing and/or sharing by private transportation network companies. American and European cities are seeing a rise in several potential business models with varying degrees of ride sharing and public vs. private involvement in delivering mobility services (MaaS). Implications for transit agencies and mobility service providers must be evaluated, and this can be done by traffic simulation models that provide a model-based framework for evaluating the mobility impact of new services.Peer ReviewedPostprint (author's final draft

The BIG IoT API: semantically enabling IoT interoperability

Today, internet of things (IoT) platforms offer proprietary interfaces and protocols. To enable interoperable interaction with those platforms we present the generic BIG IoT API that employs a novel approach for self-description and semantic annotation to fully adapt arbitrary IoT platforms. We have deployed this approach for multiple platforms from the mobility domain.Peer ReviewedPostprint (author's final draft

The detection layout problem

The main traffic models, either for planning or operational purposes, use as major data input Origin-Destination (OD) trip matrices describing the patterns of traffic behavior across the network. OD matrices become in this way a critical requirement of Advanced Traffic Management or Information Systems supported by Dynamic Traffic Assignment models. However, as far as OD matrices are not directly observable, the current practice consist of adjusting an initial or seed matrix from link flow counts provided by an existing layout of traffic counting stations. The adequacy of the detection layout strongly determines the quality of the adjusted OD. Usual approaches to the Detection Layout problem assume that detectors are located at network links but some of the Information and Communication Technologies specially those based on the detection of the electronic signature of on board devices, as for example Bluetooth devices, allow the location of sensor at intersections. This paper proposes a reformulation of the link detection layout problem adapting the classical set covering approaches with side constraints and solving it efficiently by a tabu search metaheuristic. For the intersection layout covering problem a reformulation is proposed in terms of a node covering problem with side constraints that for practical purposes can be efficiently solved with standard professional solvers.Peer ReviewedPostprint (published version

Axisymmetric smoothed particle magnetohydrodynamics

Many astrophysical and terrestrial scenarios involving magnetic fields can be approached in axial geometry. Although the smoothed particle hydrodynamics (SPH) technique has been successfully extended to magneto-hydrodynamics (MHD), a well-verified, axisymmetric MHD scheme based on such technique does not exist yet. In this work we fill that gap in the scientific literature and propose and check a novel axisymmetric MHD hydrodynamic code, that can be applied to physical problems which display the adequate geometry. We show that the hydrodynamic code built following these axisymmetric hypothesis is able to produce similar results than standard 3D-SPMHD codes with equivalent resolution but with much lesser computational load.Peer ReviewedPostprint (author's final draft

Exploring link covering and node covering formulations of detection layout problem

The primary data input used in principal traffic models comes from Origin-Destination (OD) trip matrices, which describe the patterns of traffic behavior across the network. In this way, OD matrices become a critical requirement in Advanced Traffic Management and/or Information Systems that are supported by Dynamic Traffic Assignment models. However, because OD matrices are not directly observable, the current practice consists of adjusting an initial or seed matrix from link flow counts which are provided by an existing layout of traffic counting stations. The adequacy of the detection layout strongly determines the quality of the adjusted OD. The usual approaches to the Detection Layout problem assume that detectors are located at network links. The first contribution of this paper proposes a modified set that formulates the link detection layout problem with side constraints. It also presents a new metaheuristic tabu search algorithm with high computational efficiency. The emerging Information and Communication Technologies, especially those based on the detection of the electronic signature of on-board devices (such as Bluetooth devices) allow the location of sensors at intersections. To explicitly take into account how these ICT sensors operate, this paper proposes a new formulation in terms of a node covering problem with side constraints that, for practical purposes, can be efficiently solved with standard professional solvers such as CPLEX.Peer ReviewedPostprint (author's final draft

Barcelona Virtual Mobility Lab: the multimodal transport simulation testbed for emerging mobility concepts evaluation

New sustainable mobility concepts and smart resilient ideas are arising every day. However, there is not an easy way to bring these ideas into reality, or to test how good they are as mobility solutions. Virtual Mobility Lab offers the opportunity to evaluate the impact of new mobility concepts before taking them to the real world. In this work, a multimodal macroscopic traffic simulation model of the Barcelona Metropolitan Area is developed, including both public and private transport network. This paper explains the remarkable features developed for this model, such as the network hierarchy and the multimodal public network interchangers, allowing demand to exchange between public transportation modes along their origin-destination paths.Peer ReviewedPostprint (author's final draft

A visualization tool based on traffic simulation for the analysis and evaluation of smart city policies, innovative vehicles and mobility concepts

© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The CitScale tool is a software platform for visualizing, analyzing and comparing the impacts of smart city policies based on innovative mobility concepts in urban areas. It places emphasis on new automotive vehicles aimed at reducing traffic or environmental impacts. This paper introduces this traffic simulation-based tool, and two case studies developed for different scenarios in Barcelona City are briefly presented to demonstrate the capabilities of the tool when it is combined with microscopic traffic simulation software. The first case presents an extensive evaluation of new innovative vehicles (electric vehicles, bikes and three-wheeled scooters) and mobility concepts (trip-sharing). In the second one, data provided by connected cars is analyzed in order to compare different developed navigation strategies and how they affect the city. Finally, some of the obtained results from both cases are concisely presented in order to show the potential of the proposed tool.Peer ReviewedPostprint (author's final draft