论文标题
混合眼睛：使用现实世界自动驾驶系统的预测级合作驾驶的设计和评估
Hybrid Eyes: Design and Evaluation of the Prediction-level Cooperative Driving with a Real-world Automated Driving System
论文作者
论文摘要
当前，在各种情况下，自动化驾驶系统（AD）无法像人类驾驶员那样执行，尤其是在预测周围流量的行为时。随着人类在此任务中仍在超越最新的广告，这是一个新的概念，使人类驾驶员能够帮助广告更好地预期其他道路使用者的行为。初步结果表明，在预测水平上的合作可以有效地增强广告的体验和舒适性。为了深入研究该概念，我们实施了一个交互式原型，称为预测级合作自动化驾驶系统（PROCOAD），调整了以前在公共道路上已验证的现有广告。在不同高速公路场景中的15名参与者中进行驾驶模拟器研究的结果表明，预加载可以增强自动驾驶性能并提供积极的用户体验。与参与者的后续采访还提供了有关系统改进的见解。
Currently, there are still various situations in which automated driving systems (ADS) cannot perform as well as a human driver, particularly in predicting the behaviour of surrounding traffic. As humans are still surpassing state-of-the-art ADS in this task, a new concept enabling human driver to help ADS to better anticipate the behaviour of other road users was developed. Preliminary results suggested that the collaboration at the prediction level can effectively enhance the experience and comfort of ADS. For an in-depth investigation of the concept, we implemented an interactive prototype, called Prediction-level Cooperative Automated Driving system (PreCoAD), adapting an existing ADS that has been previously validated on the public road. The results of a driving simulator study among 15 participants in different highway scenarios showed that PreCoAD could enhance automated driving performance and provide a positive user experience. Follow-up interviews with participants also provided insights into the improvement of the system.
