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: 2012
• 资助国家: 加拿大
• 起止时间: 2012-01-01 至 2013-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=508960
• 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，并且是交通事故的主要罪魁祸首。智能运输作为伞形愿景和技术提倡，并提倡结合自动化和建设智能基础设施，从而大大提高了高速公路和道路的能力和效率，并减少了事故的数量。由于人类驾驶员是导致交通事故的最大贡献因素，因此认为重新定义人驾驶员的作用可能是最终解决方案的一部分是明智的。当然，这意味着人类从驾驶汽车到监督驾驶任务的作用逐渐减少。 但是，这实施了一种相互补充的多方面方法和解决方案。在这项研究建议中，我们将重点关注这个广泛领域的选定问题。我们将研究辅助驾驶员系统，建模人类驾驶员，并发展智能状况意识算法。为了评估控制策略的有效性，现有的最新模拟平台将用于进行现实的实验，而不是在道路上，而是在虚拟环境的安全范围内进行。我们还将解决醉酒驾驶员的驾驶系统。该项目持续时间估计持续五年，并培训三到五名高素质的人员。在项目成果中，有新的解决方案，以帮助人类驾驶员，最终导致由于交通事故而减少伤害和生命损失。可以预见，该项目的结果受益于加拿大，调查结果具有国际影响。