Design and evaluation of safety-critical applications based on inter-vehicle communication

Inter-vehicle communication has a potential to improve road traffic safety and efficiency. Technical feasibility of communication between vehicles has been extensively studied, but due to the scarcity of application-level research, communication\u27s impact on the road traffic is still unclear. This thesis addresses this uncertainty by designing and evaluating two fail-safe applications, namely, Rear-End Collision Avoidance and Virtual Traffic Lights

Coordination and Self-Adaptive Communication Primitives for Low-Power Wireless Networks

The Internet of Things (IoT) is a recent trend where objects are augmented with computing and communication capabilities, often via low-power wireless radios. The Internet of Things is an enabler for a connected and more sustainable modern society: smart grids are deployed to improve energy production and consumption, wireless monitoring systems allow smart factories to detect faults early and reduce waste, while connected vehicles coordinate on the road to ensure our safety and save fuel. Many recent IoT applications have stringent requirements for their wireless communication substrate: devices must cooperate and coordinate, must perform efficiently under varying and sometimes extreme environments, while strict deadlines must be met. Current distributed coordination algorithms have high overheads and are unfit to meet the requirements of today\u27s wireless applications, while current wireless protocols are often best-effort and lack the guarantees provided by well-studied coordination solutions. Further, many communication primitives available today lack the ability to adapt to dynamic environments, and are often tuned during their design phase to reach a target performance, rather than be continuously updated at runtime to adapt to reality.In this thesis, we study the problem of efficient and low-latency consensus in the context of low-power wireless networks, where communication is unreliable and nodes can fail, and we investigate the design of a self-adaptive wireless stack, where the communication substrate is able to adapt to changes to its environment. We propose three new communication primitives: Wireless Paxos brings fault-tolerant consensus to low-power wireless networking, STARC is a middleware for safe vehicular coordination at intersections, while Dimmer builds on reinforcement learning to provide adaptivity to low-power wireless networks. We evaluate in-depth each primitive on testbed deployments and we provide an open-source implementation to enable their use and improvement by the community

Collaborative, Intelligent, and Adaptive Systems for the Low-Power Internet of Things

With the emergence of the Internet of Things (IoT), more and more devices are getting equipped with communication capabilities, often via wireless radios. Their deployments pave the way for new and mission-critical applications: cars will communicate with nearby vehicles to coordinate at intersections; industrial wireless closed-loop systems will improve operational safety in factories; while swarms of drones will coordinate to plan collision-free trajectories. To achieve these goals, IoT devices will need to communicate, coordinate, and collaborate over the wireless medium. However, these envisioned applications necessitate new characteristics that current solutions and protocols cannot fulfill: IoT devices require consistency guarantees from their communication and demand for adaptive behavior in complex and dynamic environments.In this thesis, we design, implement, and evaluate systems and mechanisms to enable safe coordination and adaptivity for the smallest IoT devices. To ensure consistent coordination, we bring fault-tolerant consensus to low-power wireless communication and introduce Wireless Paxos, a flavor of the Paxos algorithm specifically tailored to low-power IoT. We then present STARC, a wireless coordination mechanism for intersection management combining commit semantics with synchronous transmissions. To enable adaptivity in the wireless networking stack, we introduce Dimmer and eAFH. Dimmer combines Reinforcement Learning and Multi-Armed Bandits to adapt its communication parameters and counteract the adverse effects of wireless interference at runtime while optimizing energy consumption in normal conditions. eAFH provides dynamic channel management in Bluetooth Low Energy by excluding and dynamically re-including channels in scenarios with mobility. Finally, we demonstrate with BlueSeer that a device can classify its environment, i.e., recognize whether it is located in a home, office, street, or transport, solely from received Bluetooth Low Energy signals fed into an embedded machine learning model. BlueSeer therefore increases the intelligence of the smallest IoT devices, allowing them to adapt their behaviors to their current surroundings

A comprehensive survey on cooperative intersection management for heterogeneous connected vehicles

Nowadays, with the advancement of technology, world is trending toward high mobility and dynamics. In this context, intersection management (IM) as one of the most crucial elements of the transportation sector demands high attention. Today, road entities including infrastructures, vulnerable road users (VRUs) such as motorcycles, moped, scooters, pedestrians, bicycles, and other types of vehicles such as trucks, buses, cars, emergency vehicles, and railway vehicles like trains or trams are able to communicate cooperatively using vehicle-to-everything (V2X) communications and provide traffic safety, efficiency, infotainment and ecological improvements. In this paper, we take into account different types of intersections in terms of signalized, semi-autonomous (hybrid) and autonomous intersections and conduct a comprehensive survey on various intersection management methods for heterogeneous connected vehicles (CVs). We consider heterogeneous classes of vehicles such as road and rail vehicles as well as VRUs including bicycles, scooters and motorcycles. All kinds of intersection goals, modeling, coordination architectures, scheduling policies are thoroughly discussed. Signalized and semi-autonomous intersections are assessed with respect to these parameters. We especially focus on autonomous intersection management (AIM) and categorize this section based on four major goals involving safety, efficiency, infotainment and environment. Each intersection goal provides an in-depth investigation on the corresponding literature from the aforementioned perspectives. Moreover, robustness and resiliency of IM are explored from diverse points of view encompassing sensors, information management and sharing, planning universal scheme, heterogeneous collaboration, vehicle classification, quality measurement, external factors, intersection types, localization faults, communication anomalies and channel optimization, synchronization, vehicle dynamics and model mismatch, model uncertainties, recovery, security and privacy

How to Stop Disagreeing and Start Cooperatingin the Presence of Asymmetric Packet Loss

We consider the design of a disagreement correction protocol in multi-vehicle systems. Vehicles broadcast in real-time vital information such as position, direction, speed, acceleration, intention, etc. This information is then used to identify the risks and adapt their trajectory to maintain the highest performance without compromising the safety. To minimize the risk due to the use of inconsistent information, all cooperating vehicles must agree whether to use the exchanged information to operate in a cooperative mode or use the only local information to operate in an autonomous mode. However, since wireless communications are prone to failures, it is impossible to deterministically reach an agreement. Therefore, any protocol will exhibit necessary disagreement periods. In this paper, we investigate whether vehicles can still cooperate despite communication failures even in the scenario where communication is suddenly not available. We present a deterministic protocol that allows all participants to either operate a cooperative mode when vehicles can exchange all the information in a timely manner or operate in autonomous mode when messages are lost. We show formally that the disagreement time is bounded by the time that the communication channel requires to deliver messages and validate our protocol using NS-3 simulations. We explain how the proposed solution can be used in vehicular platooning to attain high performance and still guarantee high safety standards despite communication failures