测量驾驶员感知：眼动追踪与自动化道路场景感知相结合。

OBJECTIVE

To investigate how well gaze behavior can indicate driver awareness of individual road users when related to the vehicle's road scene perception.

BACKGROUND

An appropriate method is required to identify how driver gaze reveals awareness of other road users.

METHOD

We developed a recognition-based method for labeling of driver situation awareness (SA) in a vehicle with road-scene perception and eye tracking. Thirteen drivers performed 91 left turns on complex urban intersections and identified images of encountered road users among distractor images.

RESULTS

Drivers fixated within 2° for 72.8% of relevant and 27.8% of irrelevant road users and were able to recognize 36.1% of the relevant and 19.4% of irrelevant road users one min after leaving the intersection. Gaze behavior could predict road user relevance but not the outcome of the recognition task. Unexpectedly, 18% of road users observed beyond 10° were recognized.

CONCLUSIONS

Despite suboptimal psychometric properties leading to low recognition rates, our recognition task could identify awareness of individual road users during left turn maneuvers. Perception occurred at gaze angles well beyond 2°, which means that fixation locations are insufficient for awareness monitoring.

APPLICATION

Findings can be used in driver attention and awareness modelling, and design of gaze-based driver support systems.

目的

研究当驾驶员注视行为与车辆道路场景感知相关时，其能在何种程度上反映对个别道路使用者的意识。

背景

需要采用适当的方法来识别驾驶员的注视行为如何揭示其对其他道路使用者的意识。

方法

我们开发了一种基于识别的方法，用于在具有道路场景感知和眼动追踪功能的车辆中对驾驶员情境意识（SA）进行标记。13 名驾驶员在复杂的城市路口完成了 91 次左转，并在干扰图像中识别出遇到的道路使用者的图像。

结果

驾驶员对相关道路使用者的注视时间为 72.8%，注视角度为 2°以内；对不相关道路使用者的注视时间为 27.8%，注视角度为 2°以内；在离开交叉口 1 分钟后，驾驶员能够识别出 36.1%的相关道路使用者和 19.4%的不相关道路使用者。注视行为可以预测道路使用者的相关性，但不能预测识别任务的结果。出乎意料的是，有 18%的观察角度超过 10°的道路使用者被识别出来。