Corridor-Based Monitoring and Emergency Braking Decision for Automated Vehicle Safety
Corridor-Based Monitoring and Emergency Braking Decision for Automated Vehicle Safety
This paper presents an emergency-braking approach for automated vehicles that uses a predicted motion corridor to filter lidar measurements and decide on braking. The method constructs a curvature-aware boundary from the planned path and vehicle geometry, scores geometric occupancy and temporal urgency independently, and employs hard gates and soft-OR arbitration for decision-making. Consecutive-scan confirmation reduces sensitivity to noise. Evaluation includes controlled collision simulations, campus driving recordings, and Monte Carlo simulations of lead-vehicle braking and transverse-crossing encounters.
The authors propose a corridor-based monitoring method using predicted motion boundaries and geometric occupancy scoring to trigger emergency braking in automated vehicles, with evaluation via controlled collision simulations and campus driving recordings.
Source: arXiv Robotics — research abstracts · Read original article ↗
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ency independently. Hard gates permit braking when either source is conclusive; soft-OR arbitration combines partial evidence when neither gate is active. Consecutive-scan confirmation reduces sensitivity to transient measurement noise. Corridor coverage is evaluated in controlled collision simulations and recorded campus driving. Braking decisions are evaluated in Monte Carlo simulations of lead-vehicle braking and
Open source S4
arXiv:2611.06287v1 Announce Type: new Abstract: This paper addresses emergency-braking decisions for a redundant safety channel in automated vehicles. The channel is responsible for identifying hazards from sensor data and determining whether braking is necessary, given the constrained computational resources of embedded hardware. We present an emergency-braking approach that uses a predicted motion corridor to filte
Open source S2
Source：arXiv Robotics — research abstracts · arxiv.org