In-Car Technology to Alert Attention-Imparied Drivers

用于提醒注意力不集中的驾驶员的车载技术

• 批准号: 7391640
• 负责人: MATTHEW RIZZO
• 金额: $ 31.25万
• 依托单位: UNIVERSITY OF IOWA
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-05-15 至 2010-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7391640
• 关键词: Address; Adult; Affect; Age; Appetitive Behavior; Arts; Attention; Automobile Driving; Automobiles; Behavior; Biometry; Clinical Trials; Cognitive; Cognitive Science; Computer Graphics; Conflict (Psychology); Cues; Data; Devices; Elderly; Engineering; Goals; Human; Impaired cognition; Impairment; Intervention; Lead; Licensing; Measures; Medical; Monitor; Neurology; Outcome; Outcome Study; Pattern; Performance; Randomized; Reaction; Recommendation; Research; Research Project Grants; Risk; Risk Factors; Running; Safety; Sensory; Side; Signal Transduction; Solutions; Technology; Testing; Time; Training; Vehicle crash; Visual; Visual Fields; age related; design; human old age (65+); human very old age (85+); improved; instrument; member; older driver; processing speed; research study; tool; trafficking

The broad goals of this research project are to identify patterns of driving performance and safety errors resulting from age-related impairments in the useful field of view (UFOV), and to develop in-vehicle countermeasures that decrease crash risk and increase safety and mobility. The specific aims are to 1) determine optimal signal parameters for a driver alerting and collision warning device, 2) test the efficacy of the device in improving driver reactions in challenging situations in a high- fidelity driving simulator and on-road in an instrumented vehicle (IV); 3) characterize on-road driving performance, and search behavior and compensatory strategies, in at-risk drivers with UFOV impairments and comparison subjects operating an IV; 4) assess the effects of the safety intervention in at-risk drivers and comparison subjects on the road in the IV; and 5) estimate the benefits of the proposed safety interventions across the U.S. in terms of crashes averted. The research addresses these aims by testing 150 drivers ages 65 to 85 years, including 75 drivers with UFOV impairment and 75 comparison drivers without impairment. The groups will be randomized so than two-thirds receive the intervention and one-third act as controls. The experiments utilize ahigh-fidelity driving simulator, a state-of-the art instrumented vehicle, and sophisticated cognitive testing tools to systematically address driver impairments with in-vehicle solutions that improve a driver's ability to monitor information, allocate attention, and make accurate and timely decisions. The research team members are experts in human factors engineering, neurology, biostatistics, computer graphics, and cognitive science. As an outcome of these studies, we expect to (1) make recommendations on promising collision warning devices for at-risk drivers with UFOV loss, (2) develop basic information on real-world driving strategies in people at risk for collisions, (3) understand the efficacy of basic warning signal parameters and how they differ in cognitively impaired and normal drivers, (4) develop tools for possible clinical trials in drivers who have a variety of medical impairments. The results may be used to design safer automobiles that use new strategies and technologies for collision warning, perceptual augmentation, and attention management.

这项研究项目的主要目标是确定驾驶性能和安全错误的模式 由于年龄相关的损害，在有用的视野（UFOV），并开发车载 降低碰撞风险并提高安全性和机动性的对策。 具体目标是：1）确定用于驾驶员报警和碰撞警告的最佳信号参数 装置，2）测试装置在高- 逼真的驾驶模拟器和道路上的仪表车辆（四）; 3）表征道路上的驾驶 表现，搜索行为和补偿策略，在风险驾驶员与UFOV损伤 和比较对象操作IV; 4）评估风险驾驶员安全干预的效果， 在IV中的道路上的比较主体;以及5）估计所提议的安全干预措施的益处 在避免撞车事故方面。 该研究通过测试150名年龄在65至85岁之间的司机来实现这些目标，其中包括75名司机， UFOV减值和75个比较司机没有减值。将随机分组， 三分之二的人接受干预，三分之一的人作为对照。这些实验利用了高保真度的 驾驶模拟器，最先进的仪表车，和复杂的认知测试工具， 通过车载解决方案系统地解决驾驶员损伤问题，提高驾驶员的监控能力 信息，分配注意力，并做出准确和及时的决策。研究小组成员是 人因工程学、神经学、生物统计学、计算机图形学和认知科学方面的专家。 作为这些研究的结果，我们期望（1）提出有前途的碰撞预警建议 设备的风险驾驶员与UFOV的损失，（2）开发的基本信息，在现实世界中的驾驶策略， 有碰撞危险的人，（3）了解基本警告信号参数的有效性，以及它们如何 不同的认知受损和正常的司机，（4）开发工具，为可能的临床试验的司机， 有各种各样的医学缺陷。研究结果可用于设计更安全的汽车， 碰撞预警、感知增强和注意力管理的策略和技术。