Selected studies on intelligent driver assistance systems

智能驾驶辅助系统研究综述

• 批准号: 372061-2012
• 负责人: Rad, Ahmad
• 金额: $ 1.38万
• 依托单位: Simon Fraser University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2013
• 资助国家: 加拿大
• 起止时间: 2013-01-01 至 2014-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=528485
• 关键词: Selected; studies; intelligent; driver; assistance

The alarming worldwide statistics on traffic accidents suggest that human drivers are very much error-prone and are the main culprit to traffic accidents. Intelligent transportation as an umbrella vision and technology advocates that incorporating automation and building intelligent infrastructure increases the capacity and efficiency of highways and roads significantly and reduces the number of accidents. As human drivers are the single most contributing factor in causing traffic accidents, it is sensible to think that redefining the role of the human driver could be part of the final solution. This, of course, implies gradual diminishing of the role of the human from driving the car to supervising the task of driving. However, this imposes a multifaceted approach and solutions that complement each other. In this research proposal, we will focus on selected questions within this wide domain. We will study assisted driver systems, model human drivers, and develop intelligent situation awareness algorithms. In order to evaluate the effectiveness of the control strategies, an existing state-of-the art simulation platform will be used to conduct realistic experiments not on the roads but within the safe confine of a virtual environment. We will also address overriding driving systems for intoxicated drivers. The project duration is estimated to last five years and train three to five highly qualified personnel. Among the project outcomes are novel solutions to assist human drivers that ultimately lead to reducing injuries and loss of life due to traffic accidents. It is envisaged that the outcome of the project benefits Canada and the findings has an international impact.

令人震惊的全球交通事故统计数据表明，人类驾驶员非常容易出错，是交通事故的罪魁祸首。智能交通作为一种总体愿景和技术，主张将自动化和智能基础设施的建设结合起来，显著提高高速公路和道路的容量和效率，并减少事故数量。由于人类驾驶员是造成交通事故的最主要因素，因此认为重新定义人类驾驶员的角色可能是最终解决方案的一部分是明智的。当然，这意味着人类的角色从驾驶汽车逐渐减少到监督驾驶任务。 然而，这就要求采取多方面的办法和解决办法，这些办法和办法相辅相成。在本研究建议中，我们将集中讨论这一广泛领域内的选定问题。我们将研究辅助驾驶系统，模拟人类驾驶员，并开发智能态势感知算法。为了评估控制策略的有效性，现有的最先进的仿真平台将被用来进行现实的实验，而不是在道路上，但在虚拟环境的安全范围内。我们还将解决醉酒司机的驾驶系统。该项目预计持续五年，并培训三至五名高素质人员。项目成果包括帮助人类驾驶员的新解决方案，最终减少交通事故造成的伤害和生命损失。预计该项目的成果将使加拿大受益，其结论将产生国际影响。