Cooperative Perception for Connected and Automated Vehicles: Evaluation and Impact of Congestion Control

Automated vehicles make use of multiple sensors to detect their surroundings. Sensors have significantly improved over the years but still face challenges due to the presence of obstacles or adverse weather conditions, among others. Cooperative or collective perception has been proposed to help mitigate these challenges through the exchange of sensor data among vehicles using V2X (Vehicle-to-Everything) communications. Recent studies have shown that cooperative perception can complement on-board sensors and increase the vehicle's awareness beyond its sensors field of view. However, cooperative perception significantly increases the amount of information exchanged by vehicles which can degrade the V2X communication performance and ultimately the effectiveness of cooperative perception. In this context, this study conducts first a dimensioning analysis to evaluate the impact of the sensors' characteristics and the market penetration rate on the operation and performance of cooperative perception. The study then investigates the impact of congestion control on cooperative perception using the Decentralized Congestion Control (DCC) framework defined by ETSI. The study demonstrates that congestion control can negatively impact the perception and latency of cooperative perception if not adequately configured. In this context, this study demonstrates for the first time that the combination of congestion control functions at the Access and Facilities layers can improve the perception achieved with cooperative perception and ensure a timely transmission of the information. The results obtained demonstrate the importance of an adequate configuration of DCC for the development of connected and automated vehicles

Collective Perception: A Safety Perspective

Vehicle-to-everything (V2X) communication is seen as one of the main enabling technol-ogies for automated vehicles. Collective perception is especially promising, as it allows connected traffic participants to “see through the eyes of others” by sharing sensor-detected objects via V2X communication. Its benefit is typically assessed in terms of the increased object update rate, redun-dancy, and awareness. To determine the safety improvement thanks to collective perception, the authors introduce new metrics, which quantify the environmental risk awareness of the traffic par-ticipants. The performance of the V2X service is then analyzed with the help of the test platform TEPLITS, using real traffic traces from German highways, amounting to over 100 h of total driving time. The results in the considered scenarios clearly show that collective perception not only con-tributes to the accuracy and integrity of the vehicles’ environmental perception, but also that a V2X market penetration of at least 25% is necessary to increase traffic safety from a “risk of serious traffic accidents” to a “residual hypothetical risk of collisions without minor injuries” for traffic participants equipped with non-redundant 360° sensor systems. These results support the ongoing world-wide standardization efforts of the collective perception service

Cooperative Perception for Social Driving in Connected Vehicle Traffic

The development of autonomous vehicle technology has moved to the center of automotive research in recent decades. In the foreseeable future, road vehicles at all levels of automation and connectivity will be required to operate safely in a hybrid traffic where human operated vehicles (HOVs) and fully and semi-autonomous vehicles (AVs) coexist. Having an accurate and reliable perception of the road is an important requirement for achieving this objective. This dissertation addresses some of the associated challenges via developing a human-like social driver model and devising a decentralized cooperative perception framework. A human-like driver model can aid the development of AVs by building an understanding of interactions among human drivers and AVs in a hybrid traffic, therefore facilitating an efficient and safe integration. The presented social driver model categorizes and defines the driver\u27s psychological decision factors in mathematical representations (target force, object force, and lane force). A model predictive control (MPC) is then employed for the motion planning by evaluating the prevailing social forces and considering the kinematics of the controlled vehicle as well as other operating constraints to ensure a safe maneuver in a way that mimics the predictive nature of the human driver\u27s decision making process. A hierarchical model predictive control structure is also proposed, where an additional upper level controller aggregates the social forces over a longer prediction horizon upon the availability of an extended perception of the upcoming traffic via vehicular networking. Based on the prediction of the upper level controller, a sequence of reference lanes is passed to a lower level controller to track while avoiding local obstacles. This hierarchical scheme helps reduce unnecessary lane changes resulting in smoother maneuvers. The dynamic vehicular communication environment requires a robust framework that must consistently evaluate and exploit the set of communicated information for the purpose of improving the perception of a participating vehicle beyond the limitations. This dissertation presents a decentralized cooperative perception framework that considers uncertainties in traffic measurements and allows scalability (for various settings of traffic density, participation rate, etc.). The framework utilizes a Bhattacharyya distance filter (BDF) for data association and a fast covariance intersection fusion scheme (FCI) for the data fusion processes. The conservatism of the covariance intersection fusion scheme is investigated in comparison to the traditional Kalman filter (KF), and two different fusion architectures: sensor-to-sensor and sensor-to-system track fusion are evaluated. The performance of the overall proposed framework is demonstrated via Monte Carlo simulations with a set of empirical communications models and traffic microsimulations where each connected vehicle asynchronously broadcasts its local perception consisting of estimates of the motion states of self and neighboring vehicles along with the corresponding uncertainty measures of the estimates. The evaluated framework includes a vehicle-to-vehicle (V2V) communication model that considers intermittent communications as well as a model that takes into account dynamic changes in an individual vehicle’s sensors’ FoV in accordance with the prevailing traffic conditions. The results show the presence of optimality in participation rate, where increasing participation rate beyond a certain level adversely affects the delay in packet delivery and the computational complexity in data association and fusion processes increase without a significant improvement in the achieved accuracy via the cooperative perception. In a highly dense traffic environment, the vehicular network can often be congested leading to limited bandwidth availability at high participation rates of the connected vehicles in the cooperative perception scheme. To alleviate the bandwidth utilization issues, an information-value discriminating networking scheme is proposed, where each sender broadcasts selectively chosen perception data based on the novelty-value of information. The potential benefits of these approaches include, but are not limited to, the reduction of bandwidth bottle-necking and the minimization of the computational cost of data association and fusion post processing of the shared perception data at receiving nodes. It is argued that the proposed information-value discriminating communication scheme can alleviate these adverse effects without sacrificing the fidelity of the perception

Survey on decentralized congestion control methods for vehicular communication

Vehicular communications have grown in interest over the years and are nowadays recognized as a pillar for the Intelligent Transportation Systems (ITSs) in order to ensure an efficient management of the road traffic and to achieve a reduction in the number of traffic accidents. To support the safety applications, both the ETSI ITS-G5 and IEEE 1609 standard families require each vehicle to deliver periodic awareness messages throughout the neighborhood. As the vehicles density grows, the scenario dynamics may require a high message exchange that can easily lead to a radio channel congestion issue and then to a degradation on safety critical services. ETSI has defined a Decentralized Congestion Control (DCC) mechanism to mitigate the channel congestion acting on the transmission parameters (i.e., message rate, transmit power and data-rate) with performances that vary according to the specific algorithm. In this paper, a review of the DCC standardization activities is proposed as well as an analysis of the existing methods and algorithms for the congestion mitigation. Also, some applied machine learning techniques for DCC are addressed

Infraestrutura de beira de estrada para apoio a sistemas cooperativos e inteligentes de transportes

The growing need of mobility along with the evolution of the automotive industry and the massification of the personal vehicle amplifies some of the road-related problems such as safety and traffic congestion. To mitigate such issues, the evolution towards cooperative communicating technologies and autonomous systems is considered a solution to overcome the human physical limitations and the limited perception horizon of on-board sensors. Short-range vehicular communications such as Vehicle-to-Vehicle or Vehicle-to-Infrastructure (ETSI ITS-G5) in conjunction with long-range cellular communications (LTE,5G) and standardized messages, emerge as viable solutions to amplify the benefits that standalone technologies can bring to the road environment, by covering a wide array of applications and use cases. In compliance with the standardization work from European Telecommunications Standards Institute (ETSI), this dissertation describes the implementation of the collective perception service in a real road infrastructure to assist the maneuvers of autonomous vehicles and provide information to a central road operator. This work is focused on building standardized collective perception messages (CPM) by retrieving information from traffic classification radars (installed in the PASMO project) for local dissemination using ETSI ITS-G5 radio technology and creating a redundant communication channel between the road infrastructure and a central traffic control centre, located at the Instituto de Telecomunicações - Aveiro, taking advantage of cellular, point-to-point radio links and optical fiber communications. The output of the messages are shown to the user by a mobile application. The service is further improved by building an algorithm for optimizing the message dissemination to improve channel efficiency in more demanding scenarios. The results of the experimental tests showed that the time delay between the production event of the collective perception message and the reception by other ITS stations is within the boundaries defined by ETSI standards. Moreover, the algorithm for message dissemination also shows to increase radio channel efficiency by limiting the number of objects disseminated by CPM messages. The collective perception service developed and the road infrastructure are therefore, a valuable asset to provide useful information for improving road safety and fostering the deployment of intelligent cooperative transportation systems.A crescente necessidade de mobilidade em paralelo com a evolução da indústria automóvel e com a massificação do uso de meios de transportes pessoais, têm vindo a amplificar alguns problemas dos transportes rodoviários, tais como a segurança e o congestionamento do tráfego. Para mitigar estas questões, a evolução das tecnologias de comunicação cooperativas e dos sistemas autónomos é vista como uma potencial solução para ultrapassar limitações dos condutores e do horizonte de perceção dos sensores veículares. Comunicações de curto alcance, tais como Veículo-a-Veículo ou Veículo-a-Infrastrutura (ETSI ITS-G5), em conjunto com comunicações móveis de longo alcance (LTE,5G) e mensagens padrão, emergem como soluções viáveis para amplificar todos os beneficios que tecnologias independentes podem trazer para o ambiente rodoviário, cobrindo um grande leque de aplicações e casos de uso da estrada. Em conformidade com o trabalho de padronização da European Telecommunications Standards Institute, esta dissertação descreve a implementação do serviço de perceção coletiva, numa infrastrutura rodoviária real, para suporte a manobras de veículos autónomos e para fornecer informações aos operadores de estradas. Este trabalho foca-se na construção de mensagens de perceção coletiva a partir de informação gerada por radares de classificação de tráfego (instalados no âmbito do projeto PASMO) para disseminação local usando a tecnologia rádio ETSI ITS-G5 e criando um canal de comunicação redundante entre a infraestrutura rodóviaria e um centro de controlo de tráfego localizado no Instituto de Telecomunicações - Aveiro, usando para isso: redes móveis, ligações rádio ponto a ponto e fibra ótica. O conteúdo destas messagens é mostrado ao utilizador através de uma aplicação móvel. O serviço é ainda melhorado, tendo-se para tal desenvolvido um algoritmo de otimização de disseminação das mensagens, tendo em vista melhorar a eficiência do canal de transmissão em cenários mais exigentes. Os resultados dos testes experimentais efetuados revelaram que o tempo de atraso entre o evento de produção de uma mensagem de perceção coletiva e a receção por outra estação ITS, usando comunicações ITS-G5, se encontra dentro dos limites definidos pelos padrões da ETSI. Além disso, o algoritmo para disseminação de mensagens também mostrou aumentar a eficiência do canal de rádio, limitando o número de objetos disseminados pelas mesmas. Assim, o serviço de perceção coletiva desenvolvido poderá ser uma ferramenta valiosa, contribuindo para o aumento da segurança rodóviaria e para a disseminação da utilização dos sistemas cooperativos de transporte inteligente.Mestrado em Engenharia Eletrónica e Telecomunicaçõe

From Social Simulation to Integrative System Design

As the recent financial crisis showed, today there is a strong need to gain "ecological perspective" of all relevant interactions in socio-economic-techno-environmental systems. For this, we suggested to set-up a network of Centers for integrative systems design, which shall be able to run all potentially relevant scenarios, identify causality chains, explore feedback and cascading effects for a number of model variants, and determine the reliability of their implications (given the validity of the underlying models). They will be able to detect possible negative side effect of policy decisions, before they occur. The Centers belonging to this network of Integrative Systems Design Centers would be focused on a particular field, but they would be part of an attempt to eventually cover all relevant areas of society and economy and integrate them within a "Living Earth Simulator". The results of all research activities of such Centers would be turned into informative input for political Decision Arenas. For example, Crisis Observatories (for financial instabilities, shortages of resources, environmental change, conflict, spreading of diseases, etc.) would be connected with such Decision Arenas for the purpose of visualization, in order to make complex interdependencies understandable to scientists, decision-makers, and the general public.Comment: 34 pages, Visioneer White Paper, see http://www.visioneer.ethz.c

Heterogeneous V2V Communications in Multi-Link and Multi-RAT Vehicular Networks

Connected and automated vehicles will enable advanced traffic safety and efficiency applications thanks to the dynamic exchange of information between vehicles, and between vehicles and infrastructure nodes. Connected vehicles can utilize IEEE 802.11p for vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications. However, a widespread deployment of connected vehicles and the introduction of connected automated driving applications will notably increase the bandwidth and scalability requirements of vehicular networks. This paper proposes to address these challenges through the adoption of heterogeneous V2V communications in multi-link and multi-RAT vehicular networks. In particular, the paper proposes the first distributed (and decentralized) context-aware heterogeneous V2V communications algorithm that is technology and application agnostic, and that allows each vehicle to autonomously and dynamically select its communications technology taking into account its application requirements and the communication context conditions. This study demonstrates the potential of heterogeneous V2V communications, and the capability of the proposed algorithm to satisfy the vehicles' application requirements while approaching the estimated upper bound network capacity

Multi-Agent Reinforcement Learning for Connected and Automated Vehicles Control: Recent Advancements and Future Prospects

Connected and automated vehicles (CAVs) have emerged as a potential solution to the future challenges of developing safe, efficient, and eco-friendly transportation systems. However, CAV control presents significant challenges, given the complexity of interconnectivity and coordination required among the vehicles. To address this, multi-agent reinforcement learning (MARL), with its notable advancements in addressing complex problems in autonomous driving, robotics, and human-vehicle interaction, has emerged as a promising tool for enhancing the capabilities of CAVs. However, there is a notable absence of current reviews on the state-of-the-art MARL algorithms in the context of CAVs. Therefore, this paper delivers a comprehensive review of the application of MARL techniques within the field of CAV control. The paper begins by introducing MARL, followed by a detailed explanation of its unique advantages in addressing complex mobility and traffic scenarios that involve multiple agents. It then presents a comprehensive survey of MARL applications on the extent of control dimensions for CAVs, covering critical and typical scenarios such as platooning control, lane-changing, and unsignalized intersections. In addition, the paper provides a comprehensive review of the prominent simulation platforms used to create reliable environments for training in MARL. Lastly, the paper examines the current challenges associated with deploying MARL within CAV control and outlines potential solutions that can effectively overcome these issues. Through this review, the study highlights the tremendous potential of MARL to enhance the performance and collaboration of CAV control in terms of safety, travel efficiency, and economy

A Survey on platoon-based vehicular cyber-physical systems

Vehicles on the road with some common interests can cooperatively form a platoon-based driving pattern, in which a vehicle follows another one and maintains a small and nearly constant distance to the preceding vehicle. It has been proved that, compared to driving individually, such a platoon-based driving pattern can significantly improve the road capacity and energy efficiency. Moreover, with the emerging vehicular adhoc network (VANET), the performance of platoon in terms of road capacity, safety and energy efficiency, etc., can be further improved. On the other hand, the physical dynamics of vehicles inside the platoon can also affect the performance of VANET. Such a complex system can be considered as a platoon-based vehicular cyber-physical system (VCPS), which has attracted significant attention recently. In this paper, we present a comprehensive survey on platoon-based VCPS. We first review the related work of platoon-based VCPS. We then introduce two elementary techniques involved in platoon-based VCPS: the vehicular networking architecture and standards, and traffic dynamics, respectively. We further discuss the fundamental issues in platoon-based VCPS, including vehicle platooning/clustering, cooperative adaptive cruise control (CACC), platoon-based vehicular communications, etc., and all of which are characterized by the tight coupled relationship between traffic dynamics and VANET behaviors. Since system verification is critical to VCPS development, we also give an overview of VCPS simulation tools. Finally, we share our view on some open issues that may lead to new research directions