Titlebook: Cooperatively Interacting Vehicles; Methods and Effects Christoph Stiller,Matthias Althoff,Frank Flemisch Book‘‘‘‘‘‘‘‘ 2024 The Editor(s)

信条

Interaction-Aware Motion Planning as a Gamehe complexity, state-of-the-art planning approaches often assume that the future motion of surrounding vehicles can be predicted independently of the AV’s plan. This separation can lead to suboptimal, overly conservative behavior especially in highly interactive traffic situations. In this work, we

同谋

Designing Maneuver Automata of Motion Primitives for Optimal Cooperative Trajectory Planningneuvers with structure-exploiting properties. Thereby, the trajectory planning problem can be reduced to finding an admissible/optimal sequence of motion primitives. In this chapter, we present ways to designing maneuver automata based on different system models and on either analytical or data-base

无关紧要

Prioritized Trajectory Planning for Networked Vehicles Using Motion Primitivesory planning for multiple networked vehicles with collision avoidance. In the centralized formulation, the optimization problem size increases with the number of vehicles in the networked control system (NCS), rendering the formulation unusable for experiments. We investigate two methods to decrease

heartburn

Maneuver-Level Cooperation of Automated Vehicles discusses a vehicle-to-vehicle communication-based negotiation and cooperation method for maneuver cooperation. The method is based on the negotiation about explicitly defined reservation areas on the road for the exclusive use of a particular traffic participant. It covers all standard traffic sit

Brochure

Hierarchical Motion Planning for Consistent and Safe Decisions in Cooperative Autonomous Driving as well as guarantees on safe motion and collision-avoidance. This contribution proposes a three-layer hierarchic decomposition of the task of automatically steering the autonomous car along a designated route in cooperation with neighbored vehicles. The upper layer of the hierarchy identifies coop

夹克怕包裹

Specification-Compliant Motion Planning of Cooperative Vehicles Using Reachable Setsely participate in mixed traffic. In addition to driving individually, there are many traffic situations in which cooperation between vehicles maximizes their collective benefits, including preventing collisions. To realize these benefits, we compute specification-compliant reachable sets for vehicl

Intuitive

AutoKnigge—Modeling, Evaluation and Verification of Cooperative Interacting Automobilesh respect to topics like traffic flow, vehicle safety and user comfort. The core concept of the presented solutions is the Local Traffic System (LTS). Following the messages defined in European Telecommunications Standards Institute (ETSI) Intelligent Transport Systems (ITS) G5 for Vehicle-to-everyt

火海

Implicit Cooperative Trajectory Planning with Learned Rewards Under Uncertaintyed driving systems have made remarkable progress in the past decade, they lack two critical abilities: anticipation and provision of cooperation between traffic participants without communication, i.e., implicit cooperation. Observing the behavior of other traffic participants, humans infer the need

monologue

Learning Cooperative Trajectories at Intersections in Mixed Traffic often limited by the intractable complexity resulting from the combinatorial explosion associated with increasing numbers of vehicles. Learning cooperative maneuver policies with deep neural networks from traffic data is a promising approach to address this issue. This chapter presents two approach

微粒

Diagnostics and Differential Diagnostics, by a high number of space-sharing conflicts, the issue of an appropriate interaction with other road users, especially with pedestrians and cyclists, becomes increasingly important. This chapter provides an overview of the research project “KIRa” (Cooperative Interaction with Cyclists in automated