Event-Triggered Extended State Observer Based Distributed Control of Nonlinear Vehicle Platoons

We study the platoon control of vehicles with third-order nonlinear dynamics under the constant spacing policy. We consider a vehicle model with parameter uncertainties and external disturbances and propose a distributed control law based on an event-triggered extended state observer (ESO). First, an event-triggered ESO is designed to estimate the unmodeled dynamics in the vehicle model. Then based on the estimate of the unmodeled dynamics, a distributed control law is designed by using a modified dynamic surface control method. The control law of each follower vehicle only uses the information obtained by on-board sensors, including its own velocity, acceleration, the velocity of the preceding vehicle and the inter-vehicle distance. Finally, we give the range of the control parameters to ensure the stability of the vehicle platoon system. It is shown that the control parameters can be properly designed to make the observation errors of the ESOs bounded and ensure the string stability and closed-loop stability. We prove that the Zeno behavior is avoided under the designed event-triggered mechanism. The joint simulations of CarSim and MATLAB are given to demonstrate the effectiveness of the proposed control law

Event-Triggered Multi-Lane Fusion Control for 2-D Vehicle Platoon Systems with Distance Constraints

This paper investigates the event-triggered fixedtime multi-lane fusion control for vehicle platoon systems with distance keeping constraints where the vehicles are spread in multiple lanes. To realize the fusion of vehicles in different lanes, the vehicle platoon systems are firstly constructed with respect to a two-dimensional (2-D) plane. In case of the collision and loss of effective communication, the distance constraints for each vehicle are guaranteed by a barrier function-based control strategy. In contrast to the existing results regarding the command filter techniques, the proposed distance keeping controller can constrain the distance tracking error directly and the error generated by the command filter is coped with by adaptive fuzzy control technique. Moreover, to offset the impacts of the unknown system dynamics and the external disturbances, an unknown input reconstruction method with asymptotic convergence is developed by utilizing the interval observer technique. Finally, two relative threshold triggering mechanisms are utilized in the proposed fixed-time multi-lane fusion controller design so as to reduce the communication burden. The corresponding simulation results also verify the effectiveness of the proposed strategy

Control and Perception for Autonomous Driving

Autonomous driving requires perception and control. The first part of the dissertation is focused on an aspect of control related to automatic vehicle following that is not well understood, namely, the influence of imperfect wireless connectivity in vehicle platooning applications. The primary goal of most research in vehicle platooning is to enable the shortest inter vehicular spacing while maintaining safety, since short following distances are known to improve fuel efficiency and traffic mobility. It is also known that wireless connectivity can be exploited to achieve tighter platoon formations, but the effect of imperfections of wireless links on platoon stability were not well understood. This work proposes an algorithm to estimate the smallest time headway that guarantees safety based on the average packet reception rate. The algorithm has been corroborated using Model in Loop (MIL) simulations as well as test runs with a hybrid car. This thesis also develops a method to estimate the maximum perturbation in spacing error of any vehicle in a string stable platoon based on the lead vehicle's acceleration maneuver. This allows a designer to pick a safe standstill distance. The second part of this dissertation explores the challenges of environment perception and sensor fusion under adverse visibility conditions for autonomous driving. The sensor stack for autonomous vehicles usually consists of on one or more of radars, visible spectrum/RGB (Red-Green-Blue) cameras and lidars. RGB cameras perform poorly in low light conditions (at night) as well as in direct sunlight. While automotive radars are resilient to environmental conditions, they only offer a low resolution output. In this thesis, we explore the benefits of combining a Long Wavelength Infrared (LWIR) thermal camera with a radar sensor for detection and tracking of vehicles/pedestrians in poor visibility conditions. A modified Joint Probabilistic Data Association (JPDA) filter is implemented on real-world data to demonstrate the feasibility of the proposed system

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

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

A Resilient Control Approach to Secure Cyber Physical Systems (CPS) with an Application on Connected Vehicles

The objective of this dissertation is to develop a resilient control approach to secure Cyber Physical Systems (CPS) against cyber-attacks, network failures and potential physical faults. Despite being potentially beneficial in several aspects, the connectivity in CPSs poses a set of specific challenges from safety and reliability standpoint. The first challenge arises from unreliable communication network which affects the control/management of overall system. Second, faulty sensors and actuators can degrade the performance of CPS and send wrong information to the controller or other subsystems of the CPS. Finally, CPSs are vulnerable to cyber-attacks which can potentially lead to dangerous scenarios by affecting the information transmitted among various components of CPSs. Hence, a resilient control approach is proposed to address these challenges. The control approach consists of three main parts:(1) Physical fault diagnostics: This part makes sure the CPS works normally while there is no cyber-attacks/ network failure in the communication network; (2) Cyber-attack/failure resilient strategy: This part consists of a resilient strategy for specific cyber-attacks to compensate for their malicious effects ; (3) Decision making algorithm: The decision making block identifies the specific existing cyber-attacks/ network failure in the system and deploys corresponding control strategy to minimize the effect of abnormality in the system performance. In this dissertation, we consider a platoon of connected vehicle system under Co-operative Adaptive Cruise Control (CACC) strategy as a CPS and develop a resilient control approach to address the aforementioned challenges. The first part of this dissertation investigates fault diagnostics of connected vehicles assuming ideal communication network. Very few works address the real-time diagnostics problem in connected vehicles. This study models the effect of different faults in sensors and actuators, and also develops fault diagnosis scheme for detectable and identifiable faults. The proposed diagnostics scheme is based on sliding model observers to detect, isolate and estimate faults in the sensors and actuators. One of the main advantages of sliding model approach lies in applicability to nonlinear systems. Therefore, the proposed method can be extended for other nonlinear cyber physical systems as well. The second part of the proposed research deals with developing strategies to maintain performance of cyber-physical systems close to the normal, in the presence of common cyber-attacks and network failures. Specifically, the behavior of Dedicated Short-Range Communication (DSRC) network is analyzed under cyber-attacks and failures including packet dropping, Denial of Service (DOS) attack and false data injection attack. To start with, packet dropping in network communication is modeled by Bernoulli random variable. Then an observer based modifying algorithm is proposed to modify the existing CACC strategy against the effect of packet dropping phenomena. In contrast to the existing works on state estimation over imperfect communication network in CPS which mainly use either holding previous received data or Kalman filter with intermittent observation, a combination of these two approaches is used to construct the missing data over packet dropping phenomena. Furthermore, an observer based fault diagnostics based on sliding mode approach is proposed to detect, isolate and estimate sensor faults in connected vehicles platoon. Next, Denial of Service (DoS) attack is considered on the communication network. The effect of DoS attack is modeled as an unknown stochastic delay in data delivery in the communication network. Then an observer based approach is proposed to estimate the real data from the delayed measured data over the network. A novel approach based on LMI theory is presented to design observer and estimate the states of the system via delayed measurements. Next, we explore and alternative approach by modeling DoS with unknown constant time delay and propose an adaptive observer to estimate the delay. Furthermore, we study the effects of system uncertainties on the DoS algorithm. In the third algorithm, we considered a general CPS with a saturated DoS attack modeled with constant unknown delay. In this part, we modeled the DoS via a PDE and developed a PDE based observer to estimate the delay as well as states of the system while the only available measurements are delayed. Furthermore, as the last cyber-attack of the second part of the dissertation, we consider false data injection attack as the fake vehicle identity in the platoon of vehicles. In this part, we develop a novel PDE-based modeling strategy for the platoon of vehicles equipped with CACC. Moreover, we propose a PDE based observer to detect and isolate the location of the false data injection attack injected into the platoon as fake identity. Finally, the third part of the dissertation deals with the ongoing works on an optimum decision making strategy formulated via Model Predictive Control (MPC). The decision making block is developed to choose the optimum strategy among available strategies designed in the second part of the dissertation

Verbesserung des Verkehrsflusses durch lokale Methoden

For many decades congestion on highways and arterial roads has been a major problem of vehicular traffic worldwide. It is impossible to build and extend roads to keep up with the increase of traffic. Traffic congestion has a major impact on the environment, the economy and last but not least on the individual driving comfort. Congestion is caused by large-enough perturbations in dense traffic. We developed a driving strategy using Car-to-Car (C2C) communication to prevent congestion, which we call Jam-ADS (ADS = Advanced Distributed Strategy). C2C communication provides information about current positions and velocities of the vehicles ahead to a Jam-ADS processor in each vehicle. Jam-ADS aggregates this information and computes a velocity recommendation, which is presented to the driver. If sufficiently many drivers follow the recommendations congestion does not occur. In this work, we tested and evaluated several variants of Jam-ADS by simulating different scenarios. To do this, we developed our own traffic simulator CircSim to be able to influence the simulation and freely evaluate the results. CircSim simulates a closed road system consisting of a circular road of arbitrary length with arbitrary many lanes. To validate the results, we performed the same simulations with the established open-source traffic simulator SUMO and the communication network simulator Shawn. To make the simulations more realistic, we also performed our simulations in an open system consisting of a section of a highway with an on-ramp, because on-ramps are a major source of congestion-causing perturbations. Such a scenario is often used for the simulation of traffic congestion. In both scenarios we performed simulations, which showed that Jam-ADS improves the flow of traffic. To support the effectiveness of Jam-ADS beyond numerical simulations, we analyzed it mathematically as well by applying methods of control engineering. They confirmed that Jam-ADS damps all perturbations.Schon seit einigen Jahrzehnten sind Staus auf Autobahnen und Hauptverkehrsstraßen ein großes Problem im Straßenverkehr. Staus haben bedeutenden Einfluss auf die Umwelt, die Wirtschaft und nicht zuletzt auf den individuellen Fahrkomfort. Wir haben eine Strategie namens Jam-ADS (ADS = Advanced Distributed Strategy) entwickelt, welche Fahrzeug-zu-Fahrzeug-Kommunikation (C2C-Kommunikation) nutzt, um Staus zu verhindern. C2C-Kommunikation liefert laufend Informationen über Positionen und Geschwindigkeiten von vorausfahrenden Fahrzeugen an den Jam-ADS-Prozessor in jedem Fahrzeug. Jam-ADS fasst diese zusammen und berechnet daraus eine Geschwindigkeitsempfehlung, die dem Fahrer angezeigt wird. Wenn hinreichend viele Fahrer und Fahrerinnen der Empfehlung folgen, tritt kein Stau auf. In dieser Arbeit haben wir mehrere Varianten von Jam-ADS durch Simulationen von verschiedener Szenarien getestet und ausgewertet. Dafür haben wir einen eigenen Verkehrssimulator namens CircSim entwickelt. CircSim simuliert ein geschlossenes Straßennetz bestehend aus einer Ringstraße beliebiger Länge mit beliebiger Anzahl Spuren. Um die Ergebnisse zu validieren, haben wir die gleichen Simulationen auch mit dem etablierten Verkehrssimulator SUMO und dem Kommunikationsnetzwerksimulator Shawn durchgeführt. Um die Simulationen realistischer zu gestalten, haben wir weitere Simulationen mit einem offenen System bestehend aus einem Autobahnabschnitt mit einer Einfahrt durchgeführt, da an Einfahrten häufig stauauslösende Störungen entstehen. Mit beiden Szenarien führten wir zahlreiche Simulationsläufe durch, welche zeigten, dass Jam-ADS den Verkehrsfluss verbessert und so Staus vermeidet. Schließlich haben wir Jam-ADS auch mathematisch analysiert, um die Effektivität von Jam-ADS auch jenseits von numerischen Simulationen nachzuweisen. Mithilfe von etablierten Analysemethoden aus der Regelungstechnik haben wir nachgewiesen, dass Jam-ADS Störungen dämpft