A prototype Xiaomi electric vehicle equipped with driver-assistance technology crashed during road tests in Xinjiang, China, resulting in three fatalities. This incident, reported by local media, sent Xiaomi shares down. While details remain scarce, the crash highlights the ongoing safety challenges surrounding autonomous driving technology.
BYD plans to incorporate its advanced driver-assistance system (ADAS), comparable to Tesla's Autopilot, into all its vehicle models. This technology, developed in-house and not reliant on third-party systems like Nvidia's, will be offered free of charge to customers. BYD emphasizes its self-sufficiency in developing this system, claiming it offers better integration and cost-effectiveness. The rollout will begin with the upcoming Seagull model, followed by other vehicles in the lineup throughout the year.
Hacker News commenters are skeptical of BYD's claim to offer "Tesla-like" self-driving tech for free. Several point out that "free" likely means bundled into the car price, not actually gratis. Others question the capabilities of the system, doubting it's truly comparable to Tesla's Autopilot or Full Self-Driving, citing the lack of detail provided by BYD. Some express concern over the potential safety implications of offering advanced driver-assistance systems without proper explanation and consumer education. A few commenters note BYD's vertical integration, suggesting they might be able to offer the technology at a lower cost than competitors. Overall, the sentiment is one of cautious disbelief, awaiting more concrete information from BYD.
Waymo, Alphabet's self-driving unit, plans to expand its autonomous vehicle testing to over ten new US cities. Focusing on trucking and delivery services, Waymo will leverage its existing experience in Phoenix and San Francisco to gather data and refine its technology in diverse environments. This expansion aims to bolster the development and eventual commercial deployment of their autonomous driving systems for both passenger and freight transport.
HN commenters are generally skeptical of Waymo's expansion plans. Several point out that Waymo's current operational areas are geographically limited and relatively simple to navigate compared to more complex urban environments. Some question the viability of truly driverless technology in the near future, citing the ongoing need for human intervention and the difficulty of handling unpredictable situations. Others express concern about the safety implications of widespread autonomous vehicle deployment, particularly in densely populated areas. There's also discussion of the regulatory hurdles and public acceptance challenges that Waymo and other autonomous vehicle companies face. Finally, some commenters suggest Waymo's announcement is primarily a PR move designed to attract investment and maintain public interest.
This paper introduces a novel method for 3D scene reconstruction from images captured in adverse weather conditions like fog, rain, and snow. The approach leverages Gaussian splatting, a recent technique for representing scenes as collections of small, oriented Gaussian ellipsoids. By adapting the Gaussian splatting framework to incorporate weather effects, specifically by modeling attenuation and scattering, the method is able to reconstruct accurate 3D scenes even from degraded input images. The authors demonstrate superior performance compared to existing methods on both synthetic and real-world datasets, showing robust reconstructions in challenging visibility conditions. This improved robustness is attributed to the inherent smoothness of the Gaussian splatting representation and its ability to effectively handle noisy and incomplete data.
Hacker News users discussed the robustness of the Gaussian Splatting method for 3D scene reconstruction presented in the linked paper, particularly its effectiveness in challenging weather like fog and snow. Some commenters questioned the practical applicability due to computational cost and the potential need for specialized hardware. Others highlighted the impressive visual results and the potential for applications in autonomous driving and robotics. The reliance on LiDAR data was also discussed, with some noting its limitations in certain adverse weather conditions, potentially hindering the proposed method's overall robustness. A few commenters pointed out the novelty of the approach and its potential to improve upon existing methods that struggle with poor visibility. There was also brief mention of the challenges of accurately modelling dynamic weather phenomena in these reconstructions.
Self-driving buses, operating in simpler, more controlled environments than robotaxis, are emerging as a potentially faster route to widespread autonomous vehicle adoption. These buses can navigate fixed routes with fewer unpredictable variables, making them easier to deploy and potentially build public trust in autonomous technology. While challenges like complex intersections and pedestrian interactions remain, successful pilot programs suggest that autonomous buses could not only improve public transit but also pave the way for wider acceptance and eventual expansion of self-driving technology to personal vehicles.
HN commenters are generally skeptical of the claims made in the article about the potential of autonomous buses. Several point out the limitations of current self-driving technology, particularly in complex environments and unpredictable weather. Some highlight the "last mile" problem and doubt that these buses offer a significant advantage over existing public transit. Others question the economic viability, suggesting the cost and maintenance of these specialized vehicles might outweigh the benefits. A few commenters bring up safety concerns and the potential for accidents, referencing previous incidents involving autonomous vehicles. There's also discussion of the regulatory hurdles and public acceptance challenges that need to be overcome. While some express a degree of optimism, the overall sentiment appears to be cautious pessimism about the near-term impact of autonomous buses.
Summary of Comments ( 38 )
https://news.ycombinator.com/item?id=43545921
Hacker News users discuss the potential implications of the Xiaomi self-driving car crash, with several highlighting the complexities of assigning blame in such incidents. Some question whether the driver assistance system malfunctioned or if driver error was a contributing factor. Others express skepticism about the initial reports, pointing out the lack of detailed information and the possibility of sensationalized media coverage. The conversation also touches upon the broader challenges facing autonomous vehicle development, particularly in navigating unpredictable real-world scenarios. Several commenters emphasize the need for thorough investigations and transparent reporting to understand the cause of the accident and prevent similar occurrences in the future. Finally, there's discussion about the potential impact of this incident on Xiaomi's entry into the competitive electric vehicle market.
The Hacker News post titled "Xiaomi Car with Driver Assistance Crashes, Three Reported Dead" linking to a Bloomberg article about a fatal crash involving a Xiaomi vehicle has generated a moderate discussion with several insightful comments.
Several commenters raise concerns about the clarity of the reporting and the potential for misinformation. One commenter points out the ambiguity in the phrase "driver-assistance," questioning whether the system was fully autonomous or simply offered features like lane keeping assist. This user emphasizes the importance of distinguishing between levels of autonomous driving to avoid mischaracterizing the incident. Another commenter echoes this sentiment, noting the crucial difference between Level 2 assisted driving (requiring driver supervision) and higher levels of autonomy. They suggest that the current reporting doesn't offer sufficient detail to determine the level of autonomy involved.
Another line of discussion revolves around the challenges of testing and deploying autonomous driving technology. One commenter highlights the complex interplay between hardware, software, and unpredictable real-world scenarios, suggesting that even extensive testing can't account for every possibility. This leads to another discussion point regarding the responsibility for accidents involving driver-assistance features. Some commenters argue that the driver always bears ultimate responsibility when such features are engaged, while others suggest that manufacturers should be held accountable for flaws in their systems.
One commenter offers a more cynical perspective, suggesting that such incidents are inevitable as companies race to deploy self-driving technology. They argue that the pressure to be first to market often outweighs concerns about safety and thorough testing.
Finally, several users express skepticism about the original Bloomberg article, citing its reliance on local media reports and the lack of official statements from Xiaomi. They suggest waiting for more information before drawing conclusions about the cause of the crash and the role of the driver-assistance system.