AI & ML
Safety Blind Spot in Remote Driving: Considerations for Risk Assessment of Connection Loss Fallback Strategies
arXiv eess.SY0 views
arXiv:2502.10243v3 Announce Type: replace Abstract: As part of the overall goal of driverless road vehicles, remote driving is a major emerging field of research of its own. Current remote driving concepts for public road traffic often establish a fallback strategy of immediate braking to a standstill in the event of a connection loss. This may seem like the most logical option when human control of the vehicle is lost. However, our simulation results from hundreds of scenarios based on naturalistic traffic scenes indicate high collision rates for any immediate substantial deceleration to a standstill in urban settings. We show that such a fallback strategy can result in a SOTIF-relevant hazard, raising the question whether this design decision is acceptable. Therefore, from a safety perspective, we call this problem a safety blind spot, as safety analyses in this regard seem to be very rare. In this article, we first present a simulation on a naturalistic dataset that shows a high probability of collision in the described case. Second, we discuss the severity of the resulting potential rear-end collisions and provide an even more severe example by including a large commercial vehicle in the potential collision.
Source:https://arxiv.org/abs/2502.10243PreviousGeometric Pairwise Classification of Affine Constraints over Ellipsoidal RegionsNextOptical Network Digital Twin -- Practical Use Cases and Architecture
Related posts
W-2 vs 1099 Calculator: A Worked Offer Comparison for 2026
0dev.to

I tested ChatGPT's PDF Content Credentials: what survives a re-save, a print and an edit
0dev.to
I Built ResearchLens AI to Make Data Exploration and ML Benchmarking Easier
0dev.to
Fold Epic Paper Airplanes
0Hacker News
The Midterms Were a Pretty Good Sign for the Right-to-Repair Movement
0Wired
New Hulu Doc ‘Get Huge’ Shows the Deadly Toll of Looksmaxxing
0Wired