Vehicle-to-vehicle (V2V) communication is a crucial component of the future autonomous driving systems since it enables improved awareness of the surrounding environment, even without extensive processing of sensory information. However, V2V communication is prone to failures and delays, so a distributed fault-tolerant approach is required for safe and efficient transportation. In this paper, we focus on the intersection crossing (IC) problem with autonomous vehicles that cooperate via V2V communications, and propose a novel distributed IC algorithm that can handle an unknown number of communication failures. Our analysis shows that both safety and liveness requirements are satisfied in all realistic situations. We also found, based on a real data set, that the crossing delay is only slightly increased even in the presence of highly correlated failures.
The work in @cite_11 develops reliable and efficient intersection protocols using V2V communication. The proposed solutions are able to avoid deadlocks and vehicle collisions at intersections. The protocols are fully distributed since they do not rely on any centralized unit such as intersection manager. The autonomous vehicles are equipped with a similar set of sensors as in @cite_6 , and also a DSRC unit for V2V communication. The vehicles interact with each other using standardized basic safety messages (BSM) adapted for intersection crossing. The proposed protocols are tested using AutoSim simulator emulator, which utilizes a real city topography. The results showed that the proposed protocols outperform the traditional traffic light protocols in terms of trip delay, especially with an asymmetric traffic volume.
@cite_6 @cite_11
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Autonomous driving will play an important role in the future of transportation. Various autonomous vehicles have been demonstrated at the DARPA Urban Challenge [3]. General Motors has recently unveiled their Electrical-Networked Vehicles (EN-V) in Shanghai, China [5]. One of the main challenges of autonomous driving in urban areas is transition through cross-roads and intersections. In addition to safety concerns, current intersection management technologies such as stop signs and traffic lights can introduce significant traffic delays even under light traffic conditions. Our goal is to design and develop efficient and reliable intersection protocols to avoid vehicle collisions at intersections and increase the traffic throughput. The focus of this paper is investigating vehicle-to-vehicle (V2V) communications as a part of co-operative driving in the context of autonomous vehicles. We study how our proposed V2V intersection protocols can be beneficial for autonomous driving, and show significant improvements in throughput. We also prove that our protocols avoid deadlock situations inside the intersection area. The simulation results show that our new proposed V2V intersection protocols provide both safe passage through the intersection and significantly decrease the delay at the intersection and our latest V2V intersection protocol yields over 85 overall performance improvement over the common traffic light models. 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. Autonomous driving is likely to be the heart of urban transportation in the future. Autonomous vehicles have the potential to increase the safety of passengers and also to make road trips shorter and more enjoyable. As the first steps toward these goals, many car manufacturers are investing in designing and equipping their vehicles with advanced driver-assist systems. Road intersections are considered to be serious bottlenecks of urban transportation, as more than 44 of all reported crashes in U.S. occur within intersection areas which in turn lead to 8,500 fatalities and approximately 1 million injuries every year. Furthermore, the impact of road intersections on traffic delays leads to enormous waste of human and natural resources. In this paper, we therefore focus on intersection management in Intelligent Transportation Systems (ITS) research. In the future, when dealing with autonomous vehicles, it is critical to address safety and throughput concerns that arise from autonomous driving through intersections and roundabouts. Our goal is to provide vehicles with a safe and efficient passage method through intersections and roundabouts. We have been investigating vehicle-to-vehicle (V2V) communications as a part of co-operative driving in the context of autonomous driving. We have designed and developed efficient and reliable intersection protocols to avoid vehicle collisions at intersections and increase traffic throughput. In this paper, we introduce new V2V intersection protocols to achieve the above goals. We show that, in addition to intersections, these protocols are also applicable to vehicle crossings at roundabouts. Additionally, we study the effects of position inaccuracy of commonly-used GPS devices on some of our V2V intersection protocols and suggest required modifications to guarantee their safety and efficiency despite these impairments. Our simulation results show that we are able to avoid collisions and also increase the throughput of the intersections up to 87.82 compared to common traffic-light signalized intersections. Recently, several artificial intelligence labs have suggested the use of fully driverless vehicles with the capability of sensing the surrounding environment to enhance the roadway safety. The idea of having fully automated vehicles running in streets was inapplicable for many years until recently when researchers succeeded in releasing fully automated vehicles (without human drivers). Consequently, the paper develops a heuristic optimization algorithm for driverless vehicles at unsignalized intersections using a multi-agent system. The proposed system models the driverless vehicles as autonomous agents controlled by the intersection controller (manager agent). The input information of the system consists of vehicles’ current location, speed and acceleration in addition to the surrounding environment (weather, intersection characteristics, etc.). The intersection controller processes the input information using a built-in simulator: “OSDI” (Optimization Simulator for Driverless vehicles at Intersections). The simulator objective is to optimize the movements of vehicles to reduce the total delay time for the entire intersection and prevent crashes simultaneously. Thereafter, the intersection controller uses the simulator output for controlling the speed profile of the driverless vehicles within the intersection study zone. The proposed system is compared to two different intersection control scenarios: an All-way stop control (AWSC) and an Intersection manager with built-in OSDI. For both scenarios, it is assumed that there are four driverless vehicles (one vehicle per approach) willing to cross a four-legged unsignalized intersection concurrently. The results show using Monte Carlo simulation show that the proposed system reduces the total delay by 35 seconds on average compared to traditional AWSC. This research is considered as a first step in developing an unmanned vehicle technology system.