Steering Autonomous Driving Agents Through Intersections in Virtual Urban Environments
نویسندگان
چکیده
This paper explores how autonomous driving agents drive through intersections in virtual urban environments. The knowledge about where a vehicle runs on an intersection is embedded in environment database. Control of how and when a vehicle runs through an intersection is provided by vehicle behaviors. Vehicle control for traversing an intersection is divided into cruising behavior, following behavior, and intersection behavior. The component behaviors are integrated together to steer an autonomous driving agent through intersections. Before a virtual vehicle enters an intersection, the driving agent should make a decision that the vehicle either goes forward to pass the intersection or stops before the intersection. The chosen action is then applied to vehicle control. Because the ambient traffic and the status of traffic control signals on the intersection are dynamic, the decision should also be made on each time step.
منابع مشابه
A market-inspired approach to reservation-based urban road traffic management
Urban road traffic management is an example of a socially relevant problem that can be modelled as a large-scale, open, distributed system, composed of many autonomous interacting agents, which need to be controlled in a decentralized manner. Most models for urban road traffic management rely on control elements that act on traffic flows. Dresner and Stone have put forward the idea of an advanc...
متن کاملDeveloping Autonomous Navigation Algorithms Using Photorealistic Simulation
One of the principal problems in developing an automated driver is deciding how to handle the plethora of different decisions that have to be made in tactical situations. Insight on these problems can be obtained by the concurrent development of a driving simulator that allows both human and automated driving. A unique feature of the driving simulator that we have built is the ability to track ...
متن کاملMap-Based Precision Vehicle Localization in Urban Environments
Many urban navigation applications (e.g., autonomous navigation, driver assistance systems) can benefit greatly from localization with centimeter accuracy. Yet such accuracy cannot be achieved reliably with GPS-based inertial guidance systems, specifically in urban settings. We propose a technique for high-accuracy localization of moving vehicles that utilizes maps of urban environments. Our ap...
متن کاملVirtual to Real Reinforcement Learning for Autonomous Driving
Reinforcement learning is considered as a promising direction for driving policy learning. However, training autonomous driving vehicle with reinforcement learning in real environment involves non-affordable trial-and-error. It is more desirable to first train in a virtual environment and then transfer to the real environment. In this paper, we propose a novel realistic translation network to m...
متن کاملDriving an autonomous car with eye tracking
This paper describes eyeDriver, a hardware and software setup to drive an autonomous car with eye movement. The movement of the operator’s iris is tracked with an infrared sensitive camera built onto a HED4 interface by SMI. The position of the iris is then propagated by eyeDriver to control the steering wheel of “Spirit of Berlin”, a completely autonomous car developed by the Free University o...
متن کامل