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San Francisco 49ers coach Kyle Shanahan revealed that his Tesla was on Autopilot during a recent crash in Palo Alto, while taking responsibility and cautioning that drivers must stay engaged.
Tesla teases a before-and-after comparison of life with FSD Supervised, hinting at the transformative impact of its supervised full self-driving feature.
Elon Musk shares Paul Graham's anecdote about Jessica buying a Tesla and being impressed by its self-driving capabilities, highlighting the automaker's ability to inspire customers.
Tesla Europe announces FSD Supervised has been trained and tested on 2.2 million km across 19 EU countries, handling rare edge cases.
INTraJ is a unified framework for trajectory prediction that decomposes social influence into two stages: planning with future social information and local reaction from residuals, achieving state-of-the-art results on Argoverse 2, ETH/UCY, and SDD benchmarks.
Jensen Huang announced that NVIDIA has officially open-sourced its autonomous driving reasoning model Alpamayo 2 Super. The model can understand complex scenes and think before acting, and is suitable for Robotaxi, trucks, delivery vehicles, etc. It is open for commercial use under the OpenMDW-1.1 license.
This paper audits NAVSIM v2.2's defensive driving scoring, showing that a shared reference-conditioned forgiveness rule combined with numerical instability can cause actor-blind probes to outrank human replay, undermining the benchmark's validity.
The paper presents NSF-HRPT, a framework that combines a Neural Semantic Field with a Hierarchical Risk Perception Tree for quantitative risk assessment in safety-critical autonomous driving scenarios, achieving state-of-the-art performance on synthetic benchmarks and near-state-of-the-art results on real-world datasets.
Wayve announces GAIA-4, a multimodal world model powering closed-loop simulation for safety-critical evaluation of end-to-end autonomous driving models, enabling counterfactual replay of cyclist and pedestrian interactions.
This thesis introduces polynomial representations for long-term traffic scene prediction in autonomous driving, showing improved computational efficiency, generalization, and prediction plausibility over sequence-based baselines, validated on Argoverse 2 and Waymo Open datasets.
Introduces AD-MCQ and DEFT-RLVR, a method for verifiable reasoning in autonomous driving VLMs that defers future trajectory exposure to post-decision verification, improving reasoning faithfulness while reducing hallucinations.
Introduces DENSEWORLD, a 1,000-hour dataset of crowded Global South urban scenes, and FactorJEPA, a JEPA variant that factorizes future prediction into layout, agents, and interactions, improving accuracy and robustness under occlusion and heterogeneity.
The Detroit News article highlights how seniors are using Tesla's Full Self-Driving system as a driver assist to maintain mobility independence.
Tesla reports that its FSD Supervised system is over 5.2 times safer than manual driving based on 65 million kilometers driven in 5 EU countries over the last 4 months.
Elon Musk reacts to Tesla's statement about Full Self-Driving (FSD) Supervised, highlighting how the technology has become normalized.
Tesla promotes its FSD Supervised feature, noting that advanced technologies quickly become normalized.
Tesla's FSD Supervised system achieves a new autonomous Cannonball Run record, completing the cross-country drive in record time, marking a significant milestone for autonomous driving technology.
SevDiff is a severity-conditioned diffusion model for generating vehicle conflict trajectories with controlled time-to-collision values, achieving high hit-rate on a real-world dataset for ADAS evaluation.
User @TaoRay analyzes Tesla's stock, believing that although there is a short-term oversold bounce opportunity, intensified competition in autonomous driving and China's improved AI capabilities will erode Tesla's premium, suggesting avoiding investment.
The PAVE panel discussed the practical deployment of autonomous driving in off-highway scenarios (defense, industrial, logistics parks), emphasizing how it improves safety and operational efficiency rather than replacing humans.