An Emulation Framework for Evaluating V2X Communications in C-ITS Applications

C-ITS enhances transportation systems with advanced communication tech, enabling vehicle-to-vehicle and vehicle-to-infrastructure data exchange for real-time decision-making. The thesis explores C-ITS concepts, DSRC, and C-V2X tech, and proposes a versatile C-ITS framework for app prototyping and communication evaluation. Real-world tests and simulations validate its potential to improve road safety and efficiency, suggesting integration opportunities for stakeholders and promoting a smarter, sustainable transportation ecosystem

Proceedings of the 4th Symposium on Management of Future Motorway and Urban Traffic Systems 2022

The 4th Symposium on Management of Future Motorway and Urban Traffic Systems (MFTS) was held in Dresden, Germany, from November 30th to December 2nd, 2022. Organized by the Chair of Traffic Process Automation (VPA) at the “Friedrich List” Faculty of Transport and Traffic Sciences of the TU Dresden, the proceedings of this conference are published as volume 9 in the Chair’s publication series “Verkehrstelematik” and contain a large part of the presented conference extended abstracts. The focus of the MFTS conference 2022 was cooperative management of multimodal transport and reflected the vision of the professorship to be an internationally recognized group in ITS research and education with the goal of optimizing the operation of multimodal transport systems. In 14 MFTS sessions, current topics in demand and traffic management, traffic control in conventional, connected and automated transport, connected and autonomous vehicles, traffic flow modeling and simulation, new and shared mobility systems, digitization, and user behavior and safety were discussed. In addition, special sessions were organized, for example on “Human aspects in traffic modeling and simulation” and “Lesson learned from Covid19 pandemic”, whose descriptions and analyses are also included in these proceedings.:1 Connected and Automated Vehicles 1.1 Traffic-based Control of Truck Platoons on Freeways 1.2 A Lateral Positioning Strategy for Connected and Automated Vehicles in Lane-free Traffic 1.3 Simulation Methods for Mixed Legacy-Autonomous Mainline Train Operations 1.4 Can Dedicated Lanes for Automated Vehicles on Urban Roads Improve Traffic Efficiency? 1.5 GLOSA System with Uncertain Green and Red Signal Phases 2 New Mobility Systems 2.1 A New Model for Electric Vehicle Mobility and Energy Consumption in Urban Traffic Networks 2.2 Shared Autonomous Vehicles Implementation for a Disrupted Public Transport Network 3 Traffic Flow and Simulation 3.1 Multi-vehicle Stochastic Fundamental Diagram Consistent with Transportations Systems Theory 3.2 A RoundD-like Roundabout Scenario in CARLA Simulator 3.3 Multimodal Performance Evaluation of Urban Traffic Control: A Microscopic Simulation Study 3.4 A MILP Framework to Solve the Sustainable System Optimum with Link MFD Functions 3.5 On How Traffic Signals Impact the Fundamental Diagrams of Urban Roads 4 Traffic Control in Conventional Traffic 4.1 Data-driven Methods for Identifying Travel Conditions Based on Traffic and Weather Characteristics 4.2 AI-based Multi-class Traffic Model Oriented to Freeway Traffic Control 4.3 Exploiting Deep Learning and Traffic Models for Freeway Traffic Estimation 4.4 Automatic Design of Optimal Actuated Traffic Signal Control with Transit Signal Priority 4.5 A Deep Reinforcement Learning Approach for Dynamic Traffic Light Control with Transit Signal Priority 4.6 Towards Efficient Incident Detection in Real-time Traffic Management 4.7 Dynamic Cycle Time in Traffic Signal of Cyclic Max-Pressure Control 5 Traffic Control with Autonomous Vehicles 5.1 Distributed Ordering and Optimization for Intersection Management with Connected and Automated Vehicles 5.2 Prioritization of an Automated Shuttle for V2X Public Transport at a Signalized Intersection – a Real-life Demonstration 6 User Behaviour and Safety 6.1 Local Traffic Safety Analyzer (LTSA) - Improved Road Safety and Optimized Signal Control for Future Urban Intersections 7 Demand and Traffic Management 7.1 A Stochastic Programming Method for OD Estimation Using LBSN Check-in Data 7.2 Delineation of Traffic Analysis Zone for Public Transportation OD Matrix Estimation Based on Socio-spatial Practices 8 Workshops 8.1 How to Integrate Human Aspects Into Engineering Science of Transport and Traffic? - a Workshop Report about Discussions on Social Contextualization of Mobility 8.2 Learning from Covid: How Can we Predict Mobility Behaviour in the Face of Disruptive Events? – How to Investigate the Mobility of the FutureDas 4. Symposium zum Management zukünftiger Autobahn- und Stadtverkehrssysteme (MFTS) fand vom 30. November bis 2. Dezember 2022 in Dresden statt und wurde vom Lehrstuhl für Verkehrsprozessautomatisierung (VPA) an der Fakultät Verkehrswissenschaften„Friedrich List“ der TU Dresden organisiert. Der Tagungsband erscheint als Band 9 in der Schriftenreihe „Verkehrstelematik“ des Lehrstuhls und enthält einen Großteil der vorgestellten Extended-Abstracts des Symposiums. Der Schwerpunkt des MFTS-Symposiums 2022 lag auf dem kooperativen Management multimodalen Verkehrs und spiegelte die Vision der Professur wider, eine international anerkannte Gruppe in der ITS-Forschung und -Ausbildung mit dem Ziel der Optimierung des Betriebs multimodaler Transportsysteme zu sein. In 14 MFTS-Sitzungen wurden aktuelle Themen aus den Bereichen Nachfrage- und Verkehrsmanagement, Verkehrssteuerung im konventionellen, vernetzten und automatisierten Verkehr, vernetzte und autonome Fahrzeuge, Verkehrsflussmodellierung und -simulation, neue und geteilte Mobilitätssysteme, Digitalisierung sowie Nutzerverhalten und Sicherheit diskutiert. Darüber hinaus wurden Sondersitzungen organisiert, beispielsweise zu „Menschlichen Aspekten bei der Verkehrsmodellierung und -simulation“ und „Lektionen aus der Covid-19-Pandemie“, deren Beschreibungen und Analysen ebenfalls in diesen Tagungsband einfließen.:1 Connected and Automated Vehicles 1.1 Traffic-based Control of Truck Platoons on Freeways 1.2 A Lateral Positioning Strategy for Connected and Automated Vehicles in Lane-free Traffic 1.3 Simulation Methods for Mixed Legacy-Autonomous Mainline Train Operations 1.4 Can Dedicated Lanes for Automated Vehicles on Urban Roads Improve Traffic Efficiency? 1.5 GLOSA System with Uncertain Green and Red Signal Phases 2 New Mobility Systems 2.1 A New Model for Electric Vehicle Mobility and Energy Consumption in Urban Traffic Networks 2.2 Shared Autonomous Vehicles Implementation for a Disrupted Public Transport Network 3 Traffic Flow and Simulation 3.1 Multi-vehicle Stochastic Fundamental Diagram Consistent with Transportations Systems Theory 3.2 A RoundD-like Roundabout Scenario in CARLA Simulator 3.3 Multimodal Performance Evaluation of Urban Traffic Control: A Microscopic Simulation Study 3.4 A MILP Framework to Solve the Sustainable System Optimum with Link MFD Functions 3.5 On How Traffic Signals Impact the Fundamental Diagrams of Urban Roads 4 Traffic Control in Conventional Traffic 4.1 Data-driven Methods for Identifying Travel Conditions Based on Traffic and Weather Characteristics 4.2 AI-based Multi-class Traffic Model Oriented to Freeway Traffic Control 4.3 Exploiting Deep Learning and Traffic Models for Freeway Traffic Estimation 4.4 Automatic Design of Optimal Actuated Traffic Signal Control with Transit Signal Priority 4.5 A Deep Reinforcement Learning Approach for Dynamic Traffic Light Control with Transit Signal Priority 4.6 Towards Efficient Incident Detection in Real-time Traffic Management 4.7 Dynamic Cycle Time in Traffic Signal of Cyclic Max-Pressure Control 5 Traffic Control with Autonomous Vehicles 5.1 Distributed Ordering and Optimization for Intersection Management with Connected and Automated Vehicles 5.2 Prioritization of an Automated Shuttle for V2X Public Transport at a Signalized Intersection – a Real-life Demonstration 6 User Behaviour and Safety 6.1 Local Traffic Safety Analyzer (LTSA) - Improved Road Safety and Optimized Signal Control for Future Urban Intersections 7 Demand and Traffic Management 7.1 A Stochastic Programming Method for OD Estimation Using LBSN Check-in Data 7.2 Delineation of Traffic Analysis Zone for Public Transportation OD Matrix Estimation Based on Socio-spatial Practices 8 Workshops 8.1 How to Integrate Human Aspects Into Engineering Science of Transport and Traffic? - a Workshop Report about Discussions on Social Contextualization of Mobility 8.2 Learning from Covid: How Can we Predict Mobility Behaviour in the Face of Disruptive Events? – How to Investigate the Mobility of the Futur

Hardware-in-the-Loop Simulation to Evaluate the Performance and Constraints of the Red-light Violation Warning Application on Arterial Roads

Understanding the safety and mobility impacts of Connected Vehicle (CV) applications is critical for ensuring effective implementations of these applications. This dissertation provides an assessment of the safety and mobility impacts of the Red-Light Violation Warning (RLVW), a CV-based application at signalized intersections, under pre-timed signal control and semi-actuated signal control utilizing Emulator-in-the-loop (EILS), Software-in-the-loop (SILS), and Hardware-in-the-loop simulation (HILS) environments. Modern actuated traffic signal controllers contain several features with which controllers can provide varying green intervals for actuated phases, skip phases, and terminate phases depending on the traffic demand fluctuation from cycle to cycle. With actuated traffic signal operations, there is uncertainty in the end-of-green information provided to the vehicles using CV messages. The RLVW application lacks accurate input information about when exactly a phase is going to be terminated since this termination occurs when a gap of a particular length is encountered at the detector. This study compares the results obtained with the use of these three aforementioned simulation platforms and how the use of the platforms impacts the assessed performance of the modeled CV application. In addition, the study investigates using HILS and a method to provide an Assured Green Period (AGP) which is a definitive time when the green interval will end to mitigate the uncertainties associated with the green termination and to improve the performance of the CV application. The study results showed that in the case of pre-timed signal control, there are small differences in the assessed performance when using the three simulated platforms. However, in the case of the actuated control, the utilization of EILS showed significantly different results compared to the utilization of the SILS and the HILS platforms. The use of the SILS and the HILS platforms produced similar results. The differences can be attributed to the variations in the time lag between vehicle detection and the use of this information between the EILS and the other two platforms. In addition, the results showed that the reduction in red-light running due to RLVW was significantly higher with pre-timed control compared to the reduction with semi-actuated control. The reason is the uncertainty in the end-of-green intervals provided in the messages communicated to the vehicles, as stated above. In the case of semi-actuated control, the results showed that the safety benefits of the RLVW without the use of AGP were limited. On the other hand, the study results showed that by introducing the AGP, the RLVW can reduce the number of red-light running events at signalized intersections by approximately 92% with RLVW utilization of 100%. However, the results show that the application of the AGP, as applied and assessed in this dissertation, can have increased stopped delay and approach delay under congested traffic conditions. This issue will need to be further investigated to determine the optimal setting of the AGP considering both mobility and safety impacts

Development and Performance Evaluation of Urban Mobility Applications and Services

L'abstract è presente nell'allegato / the abstract is in the attachmen

Cooperative Autonomous Vehicle Speed Optimization near Signalized Intersections

Road congestion in urban environments, especially near signalized intersections, has been a major cause of significant fuel and time waste. Various solutions have been proposed to solve the problem of increasing idling times and number of stops of vehicles at signalized intersections, ranging from infrastructure-based techniques, such as dynamic traffic light control systems, to vehicle-based techniques that rely on optimal speed computation. However, all of the vehicle-based solutions introduced to solve the problem have approached the problem from a single vehicle point of view. Speed optimization for vehicles approaching a traffic light is an individual decision-making process governed by the actions/decisions of the other vehicles sharing the same traffic light. Since the optimization of other vehicles’ speed decisions is not taken into consideration, vehicles selfishly compete over the available green light; as a result, some of them experience unnecessary delay which may lead to increasing congestion. In addition, the integration of dynamic traffic light control system with vehicle speed optimization such that coordination and cooperation between the traffic light and vehicles themselves has not yet been addressed. As a step toward technological solutions to popularize the use of autonomous vehicles, this thesis introduces a game theoretic-based cooperative speed optimization framework to minimize the idling times and number of stops of vehicles at signalized intersections. This framework consists of three modules to cover issues of autonomous vehicle individual speed optimization, information acquisition and conflict recognition, and cooperative speed decision making. It relies on a linear programming optimization technique and game theory to allow autonomous vehicles heading toward a traffic light cooperate and agree on certain speed actions such that the average idling times and number of stops are minimized. In addition, the concept of bargaining in game theory is introduced to allow autonomous vehicles trade their right of passing the traffic light with less or without any stops. Furthermore, a dynamic traffic light control system is introduced to allow the cooperative autonomous vehicles cooperate and coordinate with the traffic light to further minimize their idling times and number of stops. Simulation has been conducted in MATLAB to test and validate the proposed framework under various traffic conditions and results are reported showing significant reductions of average idling times and number of stops for vehicles using the proposed framework as compared to a non-cooperative speed optimization algorithm. Moreover, a platoon-based autonomous vehicle speed optimization scheme is posed to minimize the average idling times and number of stops for autonomous vehicles connected in platoons. This platoon-based scheme consists of a linear programming optimization technique and intelligent vehicle decision-making algorithm to allow vehicles connected in a platoon and approaching a signalized intersection decide in a decentralized manner whether it is efficient to be part of the platoon or not. Simulation has been conducted in MATLAB to investigate the performance of this platoon-based scheme under various traffic conditions and results are reported, showing that vehicles using the proposed scheme achieve lower average values of idling times and number of stops as compared to two other platoon scenarios

Open Platforms for Connected Vehicles

L'abstract è presente nell'allegato / the abstract is in the attachmen

The application of vehicle classification, vehicle-to-infrastructure communication and a car-following model to single intersection traffic signal control

On-line responsive traffic signal optimization strategies most commonly use data received from loop detectors to feed information into an underlying traffic model. The limited data available from conventional detection systems has dictated the way that current ‘state-of-the-art’ traffic signal control systems have been developed. Such systems tend to consider traffic as having homogenous properties to avoid the requirement for more detailed knowledge of individual vehicle properties. However, a consequence of this simplification is to limit an optimizer in achieving its objectives. The first element of this study investigates whether additional data regarding vehicle type can be reliably extracted from conventional detection to improve optimizer performance using existing infrastructure. A single detector classification algorithm is developed and it is shown that, using a modification of an existing state-of-the-art optimization method, a modest improvement in performance can be achieved. The emergence of connected vehicle technology and, in particular, Vehicle-to-Infrastructure (V2I) communications promises more comprehensive data. V2I-based optimization methods proposed in literature require a minimum penetration rate of V2I equipped vehicles before performance matches existing systems. To address this problem, the second part of the study focuses on the development of a hybrid detection model that is capable of simultaneously using information from conventional and V2I detection. It is demonstrated that the hybrid detection model can begin to realise benefits as soon as V2I data becomes available. V2I-based vehicle classification is then applied to the developed hybrid model and significant benefits are demonstrated for HGVs. The final section of the thesis introduces the use of a more sophisticated internal traffic model and a new optimization method is developed to implement it. The car-following model based optimization method addresses the lack of modelled interaction between vehicles and is shown to be capable of reducing vehicle stops over and above the developed (vertical queue based) hybrid model

Contrôle de Congestion dans les Réseaux Véhiculaires

Cette thèse analyse la possibilité d'utiliser des communications sans fil inter-véhiculaires pour améliorer la sécurité routière. Les performances du nouveau réseau ainsi créé (réseau ad-hoc véhiculaire) sont étudiées analytiquement et par des simulations dans un environnement réaliste. La thèse se concentre surtout sur des scénarios avec une forte densité de véhicules. Dans ce cas, l'accès au support devient un problème essentiel, en principal pour les applications de sécurité routière qui nécessitent une qualité de service élevée pour fonctionner dans un tel contexte. Ce travail montre que la version actuelle du standard IEEE 802.11, proposé comme méthode d'accès dans les réseaux véhiculaires, ne peut pas résoudre ce problème de passage à l'échelle pour supporter correctement les applications de sécurité routière. Plusieurs améliorations possibles sont analysées, liées à l'utilisation optimale de certains paramètres du protocole comme la taille de la fenêtre de contention ou bien le seuil de détection de la porteuse. Des nouveaux mécanismes adaptatifs visant ces paramètres sont proposés et les améliorations ainsi obtenues sont non-négligeables. Finalement, une nouvelle méthode d'accès est définie, en tenant compte des caractéristiques des applications de sécurité routière. Toujours basée sur des techniques CSMA, cette technique donne des résultats largement supérieurs à la version standard actuelle. ABSTRACT : The equipment of vehicles with wireless communication devices in order to improve road safety is a major component of a future intelligent transportation system. The success and availability of IEEE 802.11-based products make this technology the main competitor for the Medium Access Control (MAC) layer used in vehicle-to-vehicle communication. The IEEE 802.11p amendment has been specially designed in this special context of wireless access in vehicular environments. However, as all the other approaches based on Carrier Sense Multiple Access (CSMA), this protocol presents scalability problems, which leads to poor performance in high density scenarios, quite frequent in the case of a vehicular ad hoc network (VANET). This thesis studies the congestion control problem in the context of safety vehicular communications, with a special focus on the back-off mechanism and the carrier sense function. First of all, a number of important characteristics presented by the safety messages are discovered and understood by the means of an analytical framework. Second, the lessons learned from the analytical study are put into practice with the design of two adaptive mechanisms (one for the contention window and the other one for the carrier sense threshold) that take into account the local vehicular density. These mechanisms remain simple, but highly efficient, while also being straightforward to integrate in IEEE 802.11 devices. Finally, by taking into account the most important properties of a safety VANET, a new CSMA-based MAC protocol is proposed. This new access method, named Safety Range CSMA (SR-CSMA), relies on the idea that collisions can not be avoided in a high density network. However, by increasing the number of simultaneous transmissions between geographically distant nodes, SR-CSMA manages to better protect the immediate neighborhood, the most important area for safety applications