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Improving the road scanning behavior of older drivers through the use of situation-based learning strategies.

机译:通过使用基于情况的学习策略来改善老年驾驶员的道路扫描行为。

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摘要

Older drivers are over-represented in angled crashes when compared with younger experienced drivers. Past research primarily points to age-related cognitive and physical decline, which can impede older drivers' ability to monitor their driving environment efficiently and decrease their ability to maintain adequate situational awareness. Despite compensatory behaviors such as driving less, driving more slowly or avoiding driving in inclement conditions, there is evidence that in some cases these drivers may be under-compensating, as older drivers are still involved in more angled crashes than any other category. Of particular concern are intersections in which other vehicles can approach from the side.;Two experiments described here investigate whether tailored feedback based on a driver's own unsafe behaviors and active, situation-based training in a simulator can change drivers' attitudes about their own abilities, raise their awareness of the crash risks for older drivers and lead to long-term improvements of driving behavior such as increased side-to-side scanning while negotiating intersections.;Experiment 1 investigated whether customized feedback tailored to the individual's specific unsafe driving behaviors in a simulator can successfully alter an older driver's perceptions of his driving skills. Experiment 2 compared how effectively customized feedback about a driver's specific unsafe driving behaviors on the open road followed by active situation-based training in a simulator can improve road scanning and head turning behavior when compared with lecture-style training. The results from Experiment 1 demonstrated that letting drivers make errors in a simulator and then providing customized feedback was successful in changing older drivers' perception of their ability, making them more willing to change driving behavior.;The results from Experiment 2 indicated that capturing drivers' errors on the road, providing customized feedback, and then adding active training in a simulator increased side-to-side scanning in intersections by nearly 100% in both post-training simulator and field drives. A second group, which received passive classroom-style training, demonstrated no significant improvement. In summary, compared with passive training programs, error capture, feedback, and active situation-based practice in a simulated environment is a much more effective strategy for raising awareness and increasing the road scanning behavior of older drivers.
机译:与经验丰富的年轻驾驶员相比,年龄较大的驾驶员在撞车事故中的比例过高。过去的研究主要指出与年龄有关的认知和身体衰退,这可能会阻碍老年驾驶员有效监控其驾驶环境的能力,并降低其保持足够的态势感知能力。尽管发生了一些补偿性行为,例如减少驾驶,慢速驾驶或避免在恶劣条件下驾驶,但有证据表明,在某些情况下,这些驾驶者可能补偿不足,因为年长的驾驶者仍比其他任何类型的驾驶者都更容易发生倾斜事故。尤其值得关注的是其他车辆可以从侧面驶近的交叉路口。此处描述的两个实验研究了基于驾驶员自身不安全行为的量身定制的反馈以及模拟器中基于情况的主动训练是否可以改变驾驶员对其自身能力的态度,提高他们对年长驾驶员的撞车风险的认识,并导致驾驶行为的长期改善,例如在协商交叉路口时增加从侧面到侧面的扫描。实验1研究了是否针对个人特定的不安全驾驶行为量身定制了量身定制的反馈。模拟器可以成功地改变年长驾驶员对其驾驶技能的看法。实验2比较了相对于讲课式培训,有关驾驶员在空旷道路上特定的不安全驾驶行为的定制反馈在模拟器中进行基于状态的主动培训后,如何有效地改善了道路扫描和头部转弯行为。实验1的结果表明,让驾驶员在模拟器中犯错,然后提供定制的反馈成功地改变了老年驾驶员对他们能力的感知,使他们更愿意改变驾驶行为。实验2的结果表明,捕获驾驶员道路上的错误,提供定制的反馈,然后在模拟器中添加主动训练,在训练后的模拟器和现场驱动器中,交叉路口的侧向扫描将近100%。第二组接受了被动的课堂式培训,但没有显着改善。总而言之,与被动训练计划相比,在模拟环境中错误捕获,反馈和基于状况的主动练习是一种有效的策略,可以提高老年人的意识并提高道路扫描行为。

著录项

  • 作者

    Romoser, Matthew Ryan Elam.;

  • 作者单位

    University of Massachusetts Amherst.;

  • 授予单位 University of Massachusetts Amherst.;
  • 学科 Education Adult and Continuing.;Engineering Industrial.;Transportation.
  • 学位 Ph.D.
  • 年度 2008
  • 页码 295 p.
  • 总页数 295
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 成人教育、业余教育;综合运输;一般工业技术;
  • 关键词

  • 入库时间 2022-08-17 11:38:53

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