Task analysis of autonomous on-road driving
نویسندگان
چکیده
The Real-time Control System (RCS) Methodology has evolved over a number of years as a technique to capture task knowledge and organize it into a framework conducive to implementation in computer control systems. The fundamental premise of this methodology is that the present state of the task activities sets the context that identifies the requirements for all of the support processing. In particular, the task context at any time determines what is to be sensed in the world, what world model states are to be evaluated, which situations are to be analyzed, what plans should be invoked, and which behavior generation knowledge is to be accessed.
منابع مشابه
Simulated Autonomous Driving on Realistic Road Networks using Deep Reinforcement Learning
Using Deep Reinforcement Learning (DRL) can be a promising approach to handle various tasks in the field of (simulated) autonomous driving. However, recent publications mainly consider learning in unusual driving environments. This paper presents Driving School for Autonomous Agents (DSA2), a software for validating DRL algorithms in more usual driving environments based on artificial and reali...
متن کاملDeveloping World Model Data Specifications as Metrics for Sensory Processing for On-Road Driving Tasks
Building knowledge-intensive real-time intelligent control systems is one of the most difficult tasks that humans attempt. It is motivated by the desire to create an artificial reasoning system that displays intelligent behavior (i.e. that can act on the world and successfully accomplish activities that are only possible with the levels of knowledge processing exhibited by human beings). Measur...
متن کاملبررسی تاثیر محتوا و سطح دشواری تکلیف شنیداری کلامی بر عملکرد حافظه کوتاه مدت در رانندگی با شبیهساز
Background and aims:Traffic safety has been influenced by mobile phone induced distractionwhile driving and related car crashes. The effects of audio-verbal tasks on driving performances likebreak reaction time, hazard detection time and deviation from lane have been studied by manyresearchers. But driver’s audio-verbal performance in has not received more attention. The effect ofdriving task o...
متن کاملHuman-like Driving for Autonomous Vehicles using Vision-based Road Curvature Modeling
Most autonomous vehicles use GPS to determine vehicle location and heading. Using GPS for vehicle autonomous driving posts a few challenges. It does not look far ahead of the vehicle and requires frequent adjustment of vehicle heading. This results in an unstable control system and increases the chance of unstable driving behavior. Unlike this kind of passive or reactive control system, human d...
متن کاملEvolving Collective Driving Behaviors
Recently there has been increased research interest in developing autonomous, adaptive control systems of self-driving vehicles. However, there has been little work on synthesizing collective behaviours for autonomous vehicles that must safely interact and coordinate so as traffic throughput on any given road network is maximized. This work uses neuro-evolution to automate car controller design...
متن کاملIssn 2348-375x Advanced Driver Assistance Systems for Automobiles Using Wpan
Road sign detection is important to a robotic vehicle that drives on roads automatically. In this paper, road signs are detected by means of rules that restrict and require signs to appear only in limited regions using wireless. They are then recognized using a PAN ID matching method. The method is fast and can easily be modified to include new classes of signs. As with any vehicle, an autonomo...
متن کامل