Safety Criteria Analysis for Negotiating Blind Corners in Personal Mobility Vehicles Based on Driver’s Attention Simulation on 3D Map

In this study, we attempt to establish the numerical safety criteria for negotiating blind corners in personal mobility vehicles (PMVs). Safety should be the most important consideration in designing autonomous PMVs. However, determining the suitable trade-off between safety and speed is a weighty concern because speed is significantly compromised when performing overly safe navigation. We analyze the driving behavior of a robotic PMV operated by a human driver. The robotic PMV can measure the driver’s gaze, and allows us to recognize both the pose of the PMV and the driver’s visual attention on a 3D map. As a result, the occluded areas for the driver can be estimated. Then, potential colliding hazard obstacles (PCHOs) are simulated based on the occlusion. PCHOs refer to occluded obstacles that the driver encounters suddenly with which he cannot avoid collision. The participants of our experiments were one skillful and three non-skilled ones. Experimental results demonstrate that similar PCHOs are observed even when the driving styles of the participants are different. Additionally, the existence of a boundary that distinguishes expected and unexpected obstacles is indicated by investigating the parameters of the PCHOs. Finally, we conclude that the boundary could be utilized as a numerical criterion for ensuring safety while negotiating blind corners.

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