Vehicle-to-vehicle (V2V) communication is a key component of the future autonomous driving systems. V2V can provide an improved awareness of the surrounding environment, and the knowledge about the future actions of nearby vehicles. However, V2V communication is subject to different kind of failures and delays, so a distributed fault-tolerant approach is required for safe and efficient transportation. This work considers fully autonomous vehicles that operates using local sensory information, and aided with fault-tolerant V2V communication. The sensors provide all basic functionality, but are overridden by V2V whenever is possible to increase the efficiency. As an example scenario, we consider intersection crossing (IC) with autonomous vehicles that cooperate via V2V communication, and propose a fully distributed and a fault-tolerant algorithm for this problem. According to our numerical results, based on a real data set, we show the crossing delay is only slightly increased in the presence of a burst of V2V failures, and that V2V can be successfully used in most scenarios.
The work in @cite_12 focuses on semi-autonomous vehicles with the controller that can override the driver and prevent potential collision at the intersections. They define this problem as a scheduling problem and then solve it by determining the largest set of states for which there exists a control that guarantees collision avoidance (known as maximal controlled invariant set). The original problem is NP-complete, but the proposed approximation has a polynomial complexity.
@cite_12
2085865324 2255404673 2010725166 2120423655
We consider the problem of synthesising the least restrictive controller for collision avoidance of multiple vehicles at an intersection. The largest set of states for which there exists a control that avoids collisions is known as the maximal controlled invariant set. Exploiting results from the scheduling literature we prove that, for a general model of vehicle dynamics at an intersection, the problem of checking membership in the maximal controlled invariant set is NP-hard. We then describe an algorithm that solves this problem approximately and with provable error bounds. The approximate solution is used to design a supervisor for collision avoidance whose complexity scales polynomially with the number of vehicles. The supervisor is based on a hybrid algorithm that employs a dynamic model of the vehicles and periodically solves a scheduling problem. In earlier work, we addressed the problem of coordinating online an increasing number of connected and automated vehicles (CAVs) crossing two adjacent intersections in an urban area. The analytical solution, however, did not consider the state and control constraints. In this paper, we present the complete Hamiltonian analysis including state and control constraints. In addition, we present conditions that do not allow the rear-end collision avoidance constraint to become active at any time inside the control zone. The complete analytical solution, when it exists, allows the vehicles to cross the intersection without the use of traffic lights and under the hard constraint of collision avoidance. The effectiveness of the proposed solution is validated through simulation in a single intersection and it is shown that coordination of CAVs can reduce significantly both fuel consumption and travel time. In this paper, we leverage vehicle-to-vehicle (V2V) communication technology to implement computationally efficient decentralized algorithms for two-vehicle cooperative collision avoidance at intersections. Our algorithms employ formal control theoretic methods to guarantee a collision-free (safe) system, whereas overrides are only applied when necessary to prevent a crash. Model uncertainty and communication delays are explicitly accounted for by the model and by the state estimation algorithm. The main contribution of this work is to provide an experimental validation of our method on two instrumented vehicles engaged in an intersection collision avoidance scenario in a test track. The automation of driving tasks is of increasing interest for highway traffic management. The emerging technologies of global positioning and intervehicular wireless communications, combined with in-vehicle computation and sensing capabilities, can potentially provide remarkable improvements in safety and efficiency. We address the problem of designing intelligent in-tersections, where traffic lights and stop signs are removed, and cars negotiate the intersection through an interaction of centralized and distributed decision making. Intelligent intersections are representative of complex hybrid systems that are increasingly of interest, where the challenge is to design tractable distributed algorithms that guarantee safety and provide good performance. Systems of automatically driven vehicles will need an under lying collision avoidance system with provable safety properties to be acceptable. This condition raises several challenges. We need to ensure perpetual collision avoidance so that cars do not get into future problematic positions to avoid an immediate collision. The architecture needs to allow distributed freedom of action to cars yet should guard against worst-case behavior of other cars to guarantee collision avoidance. The algorithms should be tractable both computationally and in information requirements and robust to uncertainties in sensing and communication. To address these challenges, we propose a hybrid architecture with an appropriate interplay between centralized coordination and distributed freedom of action. The approach is built around a core where each car has an infinite horizon contingency plan, which is updated at each sampling instant and distributed by the cars, in a computationally tractable manner. We also define a dynamically changing partial-order relation between cars, which specifies, for each car, a set of cars whose worst-case behaviors it should guard against. The architecture is hybrid, involving a centralized component that coordinates intersection traversals. We prove the safety and liveness of the overall scheme. The mathematical challenge of accurately quantifying performance remains as a difficult challenge; therefore, we conduct a simulation study that shows the benefits over stop signs and traffic lights. It is hoped that our effort can provide methodologies for the design of tractable solutions for complex distributed systems that require safety and liveness guarantees.