Conflict Analysis for Cooperative Maneuvering using Vehicle-to-everything (V2X) Communication
Wang, Hao
2024
Abstract
Conflicts between traffic participants may arise when their spatio-temporal trajectories come sufficiently close. Without timely detection and appropriate management, these conflicts may lead to safety hazards and compromise traffic efficiency. Emerging technologies in vehicular automation and vehicle-to-everything (V2X) communication opened up new opportunities to resolve conflicts between vehicles in a cooperative manner. On the other hand, a mixed-autonomy environment consisting of vehicles with different automation and cooperation capabilities is expected to bring additional challenges to conflict resolution over the next few decades. In this dissertation we construct a framework of conflict analysis to detect, manage, and resolve conflicts arising in cooperative maneuvers between vehicles at different levels of automation and cooperation. Two different classes of cooperation, enabled by V2X communication, are considered as means to prevent conflicts: status sharing and intent sharing. Status sharing allows vehicles to exchange their instantaneous states (e.g., current velocity and position), whereas intent sharing enables further information exchange regarding the intended future motion of vehicles (e.g., velocity and acceleration bounds). In conflict analysis, we interpret the dynamical information encoded in status and intent messages by means of conflict charts, where the state space is partitioned into the so called no-conflict, uncertain, and conflict domains. This allows for efficient decision making and controller design. We first establish the concept of conflict analysis to prevent conflicts between two vehicles. Conflict-free maneuvering strategies are developed and communication requirements for the existence of such strategies are determined. We then extend the established conflict analysis framework to study conflicts between multiple vehicles, while considering two types of time delays, one in vehicle dynamics and the other in V2X communication. Using reachability theory, conflict analysis allows us to examine the merits of communication in conflict prevention in the presence of delays. It is revealed that receiving status information can facilitate conflict-free maneuvers, but time delays can compromise such opportunities. It is also shown that receiving intent information compensates the effects of delays, removes unnecessary conservatism from decision making, and improves the efficiency of controllers of connected vehicles. We design a goal-oriented controller for connected automated vehicles to pursue conflict-free maneuvers, and demonstrate the framework using simulations with real highway data. Our analysis is brought to practice by generalizing the representation of vehicles' motion intent from a dynamical systems viewpoint. This enables us to extend conflict analysis by incorporating intent information. Such an extension is used to assist the decision-making of intent-receiving vehicles, and can be tailored to both automated and human-driven cases. We create intent messages using commercially available V2X devices, and experimentally demonstrate the benefits of sharing intent in cooperative maneuvering. Furthermore, we test intent messages on public highways and evaluate the performance in terms of packet delivery ratio. The collected data are fed into simulations to investigate the effects of intent transmission conditions (e.g., sending frequency, intent horizon, and packet drops) on conflict resolution. In summary, this dissertation presents state-of-the-art results on V2X-based conflict management in cooperative maneuvering under mixed autonomy. The novel framework of conflict analysis provides a rigorous yet scalable means to enhance traffic safety and efficiency. This dissertation is among the very first efforts to systematically study the communication impact on conflicts in mixed traffic. Our theoretical study and experimental evaluation on intent sharing cooperation are expected to benefit the on-going standardization and future real-world deployment.Deep Blue DOI
Subjects
Connected and automated vehicles Vehicle-to-everything (V2X) communication Conflict analysis Cooperative maneuvering Intent sharing cooperation
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