Development of Decision Support System for Active Traffic Management Systems Considering Travel Time Reliability

As traffic problems on roadways have been increasing, active traffic management systems (ATM) using proactive traffic management concept have been deployed on freeways and arterials. The ATM aims to integrate and automate various traffic control strategies such as variable speed limits, queue warning, and ramp metering through a decision support system (DSS). Over the past decade, there have been many efforts to integrate freeways and arterials for the efficient operation of roadway networks. It has been required that these systems should prove their effectiveness in terms of travel time reliability. Therefore, this study aims to develop a new concept of a decision support system integrating variable speed limits, queue warning, and ramp metering on the basis of travel time reliability of freeways and arterials. Regarding the data preparation, in addition to collecting multiple data sources such as traffic data, crash data and so on, the types of traffic data sources that can be applied for the analysis of travel time reliability were investigated. Although there are many kinds of real-time traffic data from third-party traffic data providers, it was confirmed that these data cannot represent true travel time reliability through the comparative analysis of measures of travel time reliability. Related to weather data, it was proven that nationwide land-based weather stations could be applicable. Since travel time reliability can be measured by using long-term periods for more than six months, it is necessary to develop models to estimate travel time reliability through real-time traffic data and event-related data. Among various matrix to measure travel time reliability, the standard deviation of travel time rate [minute/mile] representing travel time variability was chosen because it can represent travel time variability of both link and network level. Several models were developed to estimate the standard deviation of travel time rate through average travel time rate, the number of lanes, speed limits, and the amount of rainfall. Finally, a DSS using a model predictive control method to integrate multiple traffic control measures was developed and evaluated. As a representative model predictive control, METANET model was chosen, which can include variable speed limit, queue warning, and ramp metering, separately or combined. The developed DSS identified a proper response plan by comparing travel time reliability among multiple combinations of current and new response values of strategies. In the end, it was found that the DSS provided the reduction of travel time and improvement of its reliability for travelers through the recommended response plans

Real-time freeway network traffic surveillance: large-scale field testing results in Southern Italy

This paper reports on some large-scale field-testing results of a real-time freeway network traffic surveillance tool that has recently been developed to enable a number of real-time traffic surveillance tasks. This paper first introduces the related network traffic flow model and the approaches employed to traffic state estimation, traffic state prediction, and incident alarm. The field testing of the tool for these surveillance tasks in the A3 freeway of 100 km between Naples and Salerno in southern Italy is then reported in some detail. The results obtained are quite satisfactory and promising for further future implementations of the tool

Macroscopic Traffic Model Validation of Large Networks and the Introduction of a Gradient Based Solver

Traffic models are important for the evaluation of various Intelligent Transport Systems and the development of new traffic infrastructure. In order for this to be done accurately and with confidence the correct parameter values of the model must be identified. The focus of this thesis is the identification and confirmation of these parameters, which is model validation. Validation is performed on two different models; the first-order CTM and the second-order METANET model. The CTM is validated for two UK sites of 7.8 and 21.9 km and METANET for the same two sites using a variety of meta-heuristic algorithms. This is done using a newly developed method to allow for the optimisation method to determine the number of parameters to be used and the spatial extent of their application. This allows for the removal of expert engineering knowledge and ad-hoc decomposition of networks. This thesis also develops a methodology by use of Automatic Differentiation to allow gradient based optimisation to be used. This approach successfully validated the METANET model for the 21.9 km site and also a large network surrounding the city of Manchester of 186.9 km. This proves that gradient based optimisation can be used for the macroscopic traffic model validation problem. In fact the performance of the developed gradient method is superior to the meta-heuristics tested for the same sites. The methodology defined also allows for more data to be obtained from the model such as its Jacobian and the sensitivity of the objective function being used relative to the individual parameters. Space-Time contour plots of this newly acquired data show structures and shock waves that are not visible in the mean speed contour diagrams

WZ-speed harmonizer: an optimized active traffic and demand management system with speed harmonization for work zones

Speed harmonization, known as Variable Speed Limit (VSL), is implemented through a number of Changeable Message Signs (CMSs) spaced out over a stretch of highway. The CMSs display advisory speeds that may change over time and space to regulate travel speed and arrival time to a highway bottleneck and consequently reduce congestion impacts. Usually speed harmonization studies determine optimal dynamic advisory speeds to minimize travel time and delay. Delay and travel time can be further minimized if optimal location and number of CMSs are determined as well. Determining dynamic advisory speeds depends on the number and locations of CMSs; thus these variables have to be optimized simultaneously. This study is the first study which simultaneously optimized 1) dynamic advisory speeds, 2) number of CMSs, and 3) location of the CMSs to minimize total travel time and a penalty function for the number of CMSs. This problem is important as it reduces maintenance and installation costs of CMSs and enhances effectiveness of speed harmonization to reduce congestion impacts such as delay. Solving this problem is challenging because it is a large scale Mixed Integer Nonlinear Program (MINLP). Determining traffic speed and extend of queue is critical to develop a speed harmonization scheme to mitigate congestion. Past studies have used first order model or second order model as a constraint in the optimization program to determine speed and extend of queue. This study compared the first order model and the second order model versus field data and showed that the second order model was better in estimating average queue length and maximum queue length. To use the second order mode, it is necessary to calibrate the model parameters, which are relaxation time (τ) and anticipation coefficient (ϑ). This study calibrated the parameters using work zone field data to minimize error in speed and queue length estimates. The calibration is a complex process since there might be many local optimal points returning parameter values that are not physically justifiable. To overcome this issue, this study proposed a new calibration procedure. The methodology detected the behavior of the second order model in the τ- ϑ space and determined a search direction and its boundaries to avoid stopping at local minima. Although the second order model returned acceptable average and maximum queue lengths, it returned slower queue propagation pattern and faster queue dissipation pattern than field data. Thus the two- ϑ model was proposed to more maturely reflect asymmetric queue propagation and dissipation. The modification considered two different anticipation coefficients for queue propagation (ϑ_p) and queue shrinkage (ϑ_s). The two- ϑ model was calibrated using field data and results showed that the ratio of ϑ_s/ϑ_p ranges from 1.86 to 2.6 and both of them are greater than single ϑ. The solutions for the optimization program mainly tackled integrality. One source of integrality is piecewise speed-density models. Previous studies have used single-regime (single piece) models, but these models are not generally sufficient to describe congested conditions. Thus this study included the piecewise models as constraints to enhance accuracy of traffic state prediction in congested conditions. A continuous transformation approach was proposed to eliminate relevant integer variables. The methodology was used to optimize speed harmonization for a 12.5-mile roadway and a 50-min analysis duration where locations of the CMSs were given. For this problem, the methodology eliminated 30,000 binary variables and solved the problem in 23 minutes when the program included roughly 158,000 variables and 186,000 constraints. The results showed that WZSH can reduce delay by 15.7% and maximum queue length by 37.5% compared to the no speed harmonization condition. Another source of integrality is binary variables to determine location and number of CMSs. To solve the problem, three solution methods were proposed: 1) Greedy algorithm, 2) Augmented-Cut and Branch (AC&B) method, and 3) Approximate Decomposition method. The three solution methods were compared using a benchmark problem and results showed that the three methods return very close objective function values (within 1%), but the Approximate Decomposition method requires less computational resources. In particular, the Approximate Decomposition method reduced the number of WZSH solution by factors of 14.1 and 6.6 compared with Greedy Algorithm and AC&B method, respectively

Benelux meeting on systems and control, 23rd, March 17-19, 2004, Helvoirt, The Netherlands

Book of abstract

2nd Symposium on Management of Future motorway and urban Traffic Systems (MFTS 2018): Booklet of abstracts: Ispra, 11-12 June 2018

The Symposium focuses on future traffic management systems, covering the subjects of traffic control, estimation, and modelling of motorway and urban networks, with particular emphasis on the presence of advanced vehicle communication and automation technologies. As connectivity and automation are being progressively introduced in our transport and mobility systems, there is indeed a growing need to understand the implications and opportunities for an enhanced traffic management as well as to identify innovative ways and tools to optimise traffic efficiency. In particular the debate on centralised versus decentralised traffic management in the presence of connected and automated vehicles has started attracting the attention of the research community. In this context, the Symposium provides a remarkable opportunity to share novel ideas and discuss future research directions.JRC.C.4-Sustainable Transpor

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

Modeling present and future freeway management strategies : variable speed limits, lane-changing and platooning of connected autonomous vehicles

Premi Extraordinari de Doctorat, promoció 2018-2019. Àmbit d’Enginyeria Civil i AmbientalFreeway traffic management is necessary to improve capacity and reduce congestion, especially in metropolitan freeways where the rush period lasts several hours per day. Traffic congestion implies delays and an increase in air pollutant emissions, both with harmful effects to society. Active management strategies imply regulating traffic demand and improving freeway capacity. While both aspects are necessary, the present thesis only addresses the supply side. Part of the research in traffic flow theory is grounded on empirical data. Today, in order to extend our knowledge on traffic dynamics, detailed and high-quality data is needed. To that end, the thesis presents a pioneering data collection campaign, which was developed in a freeway accessing Barcelona. In a Variable Speed Limits (VSL) environment, different speed limits where posted, in order to observe their real and detailed effects on traffic. All the installed surveillance instruments were set to capture data in the highest possible level of detail, including video recordings, from where to count lane-changing maneuvers. With this objective, a semi-automatic method to reliably count lane changes form video recordings was developed and is presented in the thesis. Data analysis proved that the speed limit fulfillment was only relevant in sections with enforcement devices. In these sections, it is confirmed that, the lower the speed limit, the higher the occupancy to achieve a given flow. In contrast, the usually assumed mainline metering effect of low speed limits was not relevant. This might be different in case of stretch enforcement. These findings mean that, on the one hand, VSL strategies aiming to restrict the mainline flow on a freeway by using low speed limits will need to be applied carefully, avoiding conditions as the ones presented here. On the other hand, VSL strategies trying to get the most from the increased vehicle storage capacity of freeways under low speed limits might be rather promising. Results also show that low speed limits increase the speed differences across lanes for moderate demands. This, in turn, also increases the lane changing rates. In contrast, lower speed limits widen the range of flows under uniform lane flow distributions, so that, even for moderate to low demands, the under-utilization of any lane can be avoided. Further analysis of lane-changing activity allowed unveiling that high lane-changing rates prevent achieving the highest flows. This inverse relationship is modeled in the thesis using a stochastic model based on Bayesian inference. This model could be used as a control tool, in order to determine which level of lane-changing activity can be allowed to achieve a desired capacity with some level of reliability. Previous results identify drivers' fulfillment of traffic regulations as a weak point in order to maximize the benefits of current management strategies, like VSL or lane-changing control. This is likely to change in the near future with the irruption of Autonomous Vehicles (AV) in freeways. V2X communications will allow directly actuating on individual vehicles with high accuracy. This will open the door to new management strategies based on simultaneous communication to groups of AVs and extremely short reaction times, like platooning, which stands out as a strategy with a huge potential to improve freeway traffic. Strings of AVs traveling at extremely short gaps (i.e. platoons) allow achieving higher capacities and lower energy consumption rates. In this context, the thesis presents a parsimonious macroscopic model for AVs platooning in mixed traffic (i.e. platoons of AVs travelling together with human driven vehicles). The model allows determining the average platoon length and reproducing the overall traffic dynamics leading to higher capacities. Results prove that with a 50% penetration rate of AVs in the lane, capacity could reach 3400 veh/h/lane under a cooperative platooning strategy.Per tal de millorar la capacitat i reduir la congestió a les autopistes cal gestionar el trànsit de manera activa. Les estratègies de gestió activa del trànsit són d’especial importància en autopistes metropolitanes. La congestió provoca retards i un increment del consum de combustible que va lligat a unes majors emissions de gasos contaminants, tots amb efectes perniciosos per la societat. La gestió activa del transit requereix regular la demanda i millorar la capacitat de la via. Encara que tots dos aspectes son necessaris, la present tesis només analitza la gestió de l’oferta. Part de la recerca en l’anàlisi i la teoria del trànsit es basa en dades empíriques. Per satisfer el requeriment de dades detallades i d’alta qualitat, aquesta tesis presenta una campanya pionera de recol·lecció de dades. Les dades es van recollir a l’autopista B-23 d’accés a Barcelona. Tots els instruments de mesura es van configurar per tal de registrar les dades amb el major nivell de detall possible, incloent les càmeres de videovigilància, d’on es varen extreure els comptatges de canvi de carril. Amb aquest objectiu, es va desenvolupar una metodologia semiautomàtica per comptar canvis de carril a partir de gravacions de trànsit, que es presenta en el cos de la tesi. L’anàlisi de les dades obtingudes ha demostrat que el compliment dels límits de velocitat només resulta rellevant en aquelles seccions que compten amb un radar. És en aquestes seccions on s’ha confirmat que com menor és el límit de velocitat, major es l’ocupació per a un flux donat. Per contra, la hipòtesi habitual de que uns límits de velocitat baixos produeixen una restricció del flux no es va observar de forma rellevant. Aquest comportament podria esser diferent en el cas d’implantar un radar de tram. Els resultats obtinguts també mostren com les diferències de velocitats entre carrils s’incrementen per a límits de velocitat baixos i en condicions de demanda moderada. Això, alhora, incrementa el nombre de canvis de carril. Per contra, els límits de velocitat baixos contribueixen a una distribució de flux més uniforme entre carrils, de forma que es pot evitar la infrautilització de carrils. L’anàlisi més detallat de l’activitat de canvi de carril demostra que una taxa elevada de canvis de carril impedeix assolir fluxos grans de circulació. En la tesi, aquesta relació inversa entre la taxa de canvis de carril i el flux màxim de trànsit a l’autopista s’ha modelat de forma estocàstica utilitzant un model basat en la inferència Bayesiana. Aquest model es pot utilitzar com una eina de control, per tal de determinar quina taxa de canvi de carril es pot permetre si es vol assolir una capacitat determinada amb una determinada probabilitat de compliment. En vista dels resultats previs, la falta de compliment de les normes de trànsit per part dels conductors s’identifica com un punt dèbil a l’hora de maximitzar els beneficis de les actuals estratègies de gestió del transit. Això probablement canviarà en el futur pròxim amb la irrupció dels Vehicles Autònoms (VA) a les autopistes. Els sistemes de comunicació V2X permetran actuar individualment sobre cada vehicle amb una gran precisió. Això obrirà la porta a noves estratègies de gestió, basades en la comunicació simultània entre diferents grups de VA i en temps de reacció extremadament curts, com per exemple és el “platooning”, que destaca pel seu gran potencial per millorar el trànsit en autopista. Els “platons” son cadenes de VA viatjant amb uns espaiaments extremadament curts que permeten assolir capacitats mes elevades i un menor consum energètic. En aquest context, la tesi presenta un model macroscòpic parsimoniós per a “platons” de VA en condicions de transit mixt, és a dir, compartint la infraestructura amb vehicles tradicionals. El model permet determinar la longitud mitjana del “platons” i reproduir el trànsit global dinàmiques que condueixen a majors capacitats. Els resultats demostren que amb un 50% la velocitat de penetració dels AV al carril, la capacitat podria arribar als 3.400 vehicles / h / carril sota una estratègia cooperativa de “platooning”Award-winningPostprint (published version

Modeling present and future freeway management strategies : variable speed limits, lane-changing and platooning of connected autonomous vehicles

Freeway traffic management is necessary to improve capacity and reduce congestion, especially in metropolitan freeways where the rush period lasts several hours per day. Traffic congestion implies delays and an increase in air pollutant emissions, both with harmful effects to society. Active management strategies imply regulating traffic demand and improving freeway capacity. While both aspects are necessary, the present thesis only addresses the supply side. Part of the research in traffic flow theory is grounded on empirical data. Today, in order to extend our knowledge on traffic dynamics, detailed and high-quality data is needed. To that end, the thesis presents a pioneering data collection campaign, which was developed in a freeway accessing Barcelona. In a Variable Speed Limits (VSL) environment, different speed limits where posted, in order to observe their real and detailed effects on traffic. All the installed surveillance instruments were set to capture data in the highest possible level of detail, including video recordings, from where to count lane-changing maneuvers. With this objective, a semi-automatic method to reliably count lane changes form video recordings was developed and is presented in the thesis. Data analysis proved that the speed limit fulfillment was only relevant in sections with enforcement devices. In these sections, it is confirmed that, the lower the speed limit, the higher the occupancy to achieve a given flow. In contrast, the usually assumed mainline metering effect of low speed limits was not relevant. This might be different in case of stretch enforcement. These findings mean that, on the one hand, VSL strategies aiming to restrict the mainline flow on a freeway by using low speed limits will need to be applied carefully, avoiding conditions as the ones presented here. On the other hand, VSL strategies trying to get the most from the increased vehicle storage capacity of freeways under low speed limits might be rather promising. Results also show that low speed limits increase the speed differences across lanes for moderate demands. This, in turn, also increases the lane changing rates. In contrast, lower speed limits widen the range of flows under uniform lane flow distributions, so that, even for moderate to low demands, the under-utilization of any lane can be avoided. Further analysis of lane-changing activity allowed unveiling that high lane-changing rates prevent achieving the highest flows. This inverse relationship is modeled in the thesis using a stochastic model based on Bayesian inference. This model could be used as a control tool, in order to determine which level of lane-changing activity can be allowed to achieve a desired capacity with some level of reliability. Previous results identify drivers' fulfillment of traffic regulations as a weak point in order to maximize the benefits of current management strategies, like VSL or lane-changing control. This is likely to change in the near future with the irruption of Autonomous Vehicles (AV) in freeways. V2X communications will allow directly actuating on individual vehicles with high accuracy. This will open the door to new management strategies based on simultaneous communication to groups of AVs and extremely short reaction times, like platooning, which stands out as a strategy with a huge potential to improve freeway traffic. Strings of AVs traveling at extremely short gaps (i.e. platoons) allow achieving higher capacities and lower energy consumption rates. In this context, the thesis presents a parsimonious macroscopic model for AVs platooning in mixed traffic (i.e. platoons of AVs travelling together with human driven vehicles). The model allows determining the average platoon length and reproducing the overall traffic dynamics leading to higher capacities. Results prove that with a 50% penetration rate of AVs in the lane, capacity could reach 3400 veh/h/lane under a cooperative platooning strategy.Per tal de millorar la capacitat i reduir la congestió a les autopistes cal gestionar el trànsit de manera activa. Les estratègies de gestió activa del trànsit són d’especial importància en autopistes metropolitanes. La congestió provoca retards i un increment del consum de combustible que va lligat a unes majors emissions de gasos contaminants, tots amb efectes perniciosos per la societat. La gestió activa del transit requereix regular la demanda i millorar la capacitat de la via. Encara que tots dos aspectes son necessaris, la present tesis només analitza la gestió de l’oferta. Part de la recerca en l’anàlisi i la teoria del trànsit es basa en dades empíriques. Per satisfer el requeriment de dades detallades i d’alta qualitat, aquesta tesis presenta una campanya pionera de recol·lecció de dades. Les dades es van recollir a l’autopista B-23 d’accés a Barcelona. Tots els instruments de mesura es van configurar per tal de registrar les dades amb el major nivell de detall possible, incloent les càmeres de videovigilància, d’on es varen extreure els comptatges de canvi de carril. Amb aquest objectiu, es va desenvolupar una metodologia semiautomàtica per comptar canvis de carril a partir de gravacions de trànsit, que es presenta en el cos de la tesi. L’anàlisi de les dades obtingudes ha demostrat que el compliment dels límits de velocitat només resulta rellevant en aquelles seccions que compten amb un radar. És en aquestes seccions on s’ha confirmat que com menor és el límit de velocitat, major es l’ocupació per a un flux donat. Per contra, la hipòtesi habitual de que uns límits de velocitat baixos produeixen una restricció del flux no es va observar de forma rellevant. Aquest comportament podria esser diferent en el cas d’implantar un radar de tram. Els resultats obtinguts també mostren com les diferències de velocitats entre carrils s’incrementen per a límits de velocitat baixos i en condicions de demanda moderada. Això, alhora, incrementa el nombre de canvis de carril. Per contra, els límits de velocitat baixos contribueixen a una distribució de flux més uniforme entre carrils, de forma que es pot evitar la infrautilització de carrils. L’anàlisi més detallat de l’activitat de canvi de carril demostra que una taxa elevada de canvis de carril impedeix assolir fluxos grans de circulació. En la tesi, aquesta relació inversa entre la taxa de canvis de carril i el flux màxim de trànsit a l’autopista s’ha modelat de forma estocàstica utilitzant un model basat en la inferència Bayesiana. Aquest model es pot utilitzar com una eina de control, per tal de determinar quina taxa de canvi de carril es pot permetre si es vol assolir una capacitat determinada amb una determinada probabilitat de compliment. En vista dels resultats previs, la falta de compliment de les normes de trànsit per part dels conductors s’identifica com un punt dèbil a l’hora de maximitzar els beneficis de les actuals estratègies de gestió del transit. Això probablement canviarà en el futur pròxim amb la irrupció dels Vehicles Autònoms (VA) a les autopistes. Els sistemes de comunicació V2X permetran actuar individualment sobre cada vehicle amb una gran precisió. Això obrirà la porta a noves estratègies de gestió, basades en la comunicació simultània entre diferents grups de VA i en temps de reacció extremadament curts, com per exemple és el “platooning”, que destaca pel seu gran potencial per millorar el trànsit en autopista. Els “platons” son cadenes de VA viatjant amb uns espaiaments extremadament curts que permeten assolir capacitats mes elevades i un menor consum energètic. En aquest context, la tesi presenta un model macroscòpic parsimoniós per a “platons” de VA en condicions de transit mixt, és a dir, compartint la infraestructura amb vehicles tradicionals. El model permet determinar la longitud mitjana del “platons” i reproduir el trànsit global dinàmiques que condueixen a majors capacitats. Els resultats demostren que amb un 50% la velocitat de penetració dels AV al carril, la capacitat podria arribar als 3.400 vehicles / h / carril sota una estratègia cooperativa de “platooning