S&P 500 nears record high despite tech sell-off; Tesla drops 18% after profit miss The S&P 500 remains close to its all-time high, down only 2.7% despite recent declines. Last week, energy and commodities stocks led gains, while tech and growth stocks, including Tesla, faced heavy selling pressure. Tesla's shares fell 18% after its...
ICYMI: Ford ratifies Canadian labor deal and expands Windsor investment to $499 million. Used-vehicle prices ease as supply climbs to 47 days. U.S. and Mexico resume USMCA talks as Trump escalates trade pressure on Canada. Senate panel advances bill to ban Chinese vehicle tech. CBT News opens nominations for its 2026 40 Under 40 Award. Here’s a closer look at these top stories and more headlines to stay on top of this week’s automotive industry news. Ford ratifies Canadian labor deal, expands Windsor investment to $499 million Ford and Unifor have ratified a new three-year labor agreement for approximately 5,000 Canadian employees, which includes a 9% wage increase over the three years. Eligible full-time workers will receive about $7,130 (C$10,000) as a ratification bonus, while eligible temporary employees will receive about $1,430 (C$2,000). Read More Used-vehicle prices ease as supply climbs to 47 days Used-vehicle supply is loosening on both the retail and wholesale sides, and prices are pulling back from earlier gains. Cox Automotive’s June retail data shows inventory rising as sales slow, while Manheim’s mid-July wholesale index shows values easing for the first time in months. Dealers held 2.14 million used vehicles in June, up 1% from May, according to Cox Automotive’s analysis of vAuto Live Market View data. Read More GM’s core earnings jump 30%, pushing 2026 guidance higher again General Motors (GM) raised its full-year 2026 guidance for the second time this year, even as a major EV-related charge pulled net income down in the second quarter. The results point to a stronger core business than the headline profit number suggests, and dealers should pay attention to both sides of the story. While GM reported Q2 revenue of $48 billion, up 1.9% from a year ago, net income attributable to stockholders fell to $1.3 billion, down
As autonomous ride-hailing expands across the U.S. with Tela’s Robotaxi service and Alphabet’s Waymo, traditional gig platforms are working to protect their turf. Rather than focusing solely on vehicle development, legacy ride-hailing networks are turning toward legislative channels to keep driverless fleets tied to their existing apps. According to a report from the Financial Times, Uber has been actively lobbying state and federal policymakers to enforce mandatory hybrid networks, where human drivers and autonomous vehicles operate on the same platform. The Push for 85% Human Drivers in New Jersey In New Jersey, state lawmakers are evaluating a three-year pilot program designed to establish an official regulatory framework for testing and deploying driverless vehicles. However, Uber lobbyists are proposing a major add-on to the legislation: requiring any platform offering robotaxi services to have human drivers handle at least 85% of all rides during the pilot program. If adopted, this rule would force companies like Tesla and Waymo that already have dedicated autonomous rideshare apps to route their rides through Uber and similar third-party platforms that maintain large human driver pools. For Tesla, this proposal comes on top of existing hurdles in the legislation that would essentially ban its Robotaxi vehicles from New Jersey unless it adds more sensors to them. In its current form, the draft requires commercial driverless vehicles to be equipped with at least two distinct sensor modalities (like LiDAR and radar) alongside cameras, effectively ruling out Tesla’s camera-only. Beyond sensor demands, the bill requires operators to: - Complete 50,000 miles of supervised in-state testing with a human safety driver. - Submit complete safety certifications, proof of insurance, and law enforcement interaction plans. - Report all vehicle collisions directly to the New Jersey Department of Transportation within five days. Tacking on a requirement to operate exclusively on a hybrid
Waymo’s autonomous electric taxis crash 68% less than the average human driver, according to the Insurance Institute for Highway Safety, with lower-severity crashes on average as well. But there are some important caveats that limit the data. In recent years, we’ve seen a proliferation of companies offering autonomous taxi services with “level 4” automation – the ability to operate with no driver in the car, at least in a limited (geofenced) area. The leader among these services has been Waymo, a subsidiary of Google’s Alphabet, Inc. It now offers autonomous ride-hailing services in 11 US cities, covering a total area larger than a US state (okay, that state is Rhode Island… well, it’s a start). It has provided tens of millions of trips so far, which gives us an opportunity to examine the data and see how well these robots can actually drive. And it turns out… they’re pretty good. With some caveats. IIHS finds Waymo 68% safer than an *average* human The Insurance Institute for Highway Safety, famous for its “Top Safety Pick” crash safety recommendations, examined federal crash reporting data for various robotaxi services from 2021-2024. It focused on Waymo, because while others are in the data set, Cruise stopped operations in 2023 and Zoox only began offering public rides in 2025. Tesla, also, is not reflected in the 2021-2024 data set, as it only began offering its Austin “robotaxi” in 2025 (with drivers in the car at the time), and has only racked up 380,000 total unsupervised miles as of this week. After cleaning up the data of redundancies and determining severity of crashes, the IIHS said that Waymo resulted in 68% fewer crashes severe enough that the average person would report them to the police, over a sample of 50 million miles driven autonomously by Waymos
Gasgoo Munich- Tesla released its second-quarter 2026 earnings on July 23. Bolstered by global deliveries of over 480,000 vehicles, the automaker posted its best-ever performance for the period, up 25% from a year earlier. Total revenue climbed 26% to $28.2 billion, pushing trailing 12-month revenue past the $100 billion mark for the first time. Shanghai Gigafactory delivered more than 89,000 vehicles in June and nearly 468,000 in the first half — a 28.4% annual surge — providing a strong foundation for the results. Image source: Tesla Profit margins felt the squeeze, with operating profit slipping to $398 million year-over-year. The decline stems largely from Tesla pouring resources into next-generation AI infrastructure and forward-looking manufacturing capabilities. Research and development spending hit $2.37 billion, while capital expenditure soared to $5.79 billion — jumping 49% and 142%, respectively. Free cash flow briefly turned negative as the company doubled the size of its Texas computing cluster, expanded the Cortex 2 data center, and moved in parallel on dedicated production lines for humanoid robots and the Cybercab autonomous vehicle. "We are massively expanding manufacturing capacity for advanced infrastructure — this will be the largest build-out in history," Elon Musk told analysts on the earnings call. These investments are viewed as the critical pivot point in Tesla's shift from automaker to AI technology company. Image source: Tesla New business lines are gaining traction. Paid users of Tesla's driver-assistance software reached 1.48 million, with adoption rates in North America hitting a record high — more than half of new vehicles are delivered with the service subscribed. In the U.S. and South Korea, older models equipped with AI3 hardware began receiving the v14 lite update, bringing driving behavior and safety closer to the latest standard. The Robotaxi service, operating without safety drivers, has expanded to seven U.S. cities,
Some self-driving car systems have trouble detecting darker skin, study says Last year, Microsoft, IBM, and Amazon were called out for using facial recognition technology that was biased against people with dark skin. Well, it looks like self-driving cars could have the same problem. An analysis from Georgia Tech researchers found that systems used by self-driving cars to detect pedestrians had trouble picking out people with darker skin tones. Looking at footage from the Berkeley Driving Dataset, with video from New York, Berkeley, San Francisco, and San Jose, researchers were able to study how systems would react to different types of pedestrians. They took eight image recognition systems commonly used in autonomous vehicles and evaluated how each picked up skin tone, as measured on the Fitzpatrick skin type scale. They found "uniformly poorer performance of these systems when detecting pedestrians with Fitzpatrick skin types between 4 and 6," which are darker skin types. There are several factors that could lead to inaccurate results, like time of day or clothing color. But they found that solely based on skin color, accuracy dropped an average of 5 percent for pedestrians with darker skin. If a system doesn't identify a person as a pedestrian, they're more at risk of being hit because the computer doesn't know to predict their behavior. Many autonomous cars use a mix of LiDAR, radar, other sensors, and cameras. A few autonomous vehicle companies rely heavily on cameras, like Tesla's semi-autonomous Autopilot system. Silicon Valley-based company Ambarella is developing a self-driving system that relies almost entirely on cameras. Not all companies use cameras, though. Blackmore is focused on Doppler LiDAR, so clothing choices and skin tone don't matter. Instead, it measures the velocity of objects, concentrating on things that are moving, instead of stationary objects like trees and mailboxes.
Gasgoo Munich- At the 2026 China Auto Forum Technology Leaders Summit, Lu You addressed the industry's most persistent headaches. Lu You is general manager of products and markets at neueHCT. Despite being a joint venture founded just two years ago, the company addresses a sector caught in a blind race for computing power. Internal combustion engine (ICE) vehicles struggle to adopt affordable city-driving assist systems. Domestic autonomous driving tech often stumbles abroad due to unfamiliar road conditions and driving habits. Leveraging Horizon Robotics chips, neueHCT proposes a path forward. It involves tiered products paired with physical AI end-to-end algorithms. These algorithms balance cost, compatibility, and global adaptability. An arms race in computing power is clearly underway. Premium models pack chips ranging from 2,000 to 3,000 TOPS, yet vehicle costs keep climbing. Lu You stated that neueHCT rejects unchecked hardware stacking. Instead, the company plans hardware in tiers based on model positioning. The lineup includes an entry-level solution around 10 TOPS. It also features a mid-to-high-tier system backed by the J6M chip offering 100-plus TOPS. A next-generation cockpit-driving integrated chip will roll out in stages. This approach balances functional needs with manufacturing costs. The team is focusing heavily on the J6M platform. It uses a one-stage end-to-end physical AI algorithm. This delivers safety and smoothness comparable to 200-to-300 TOPS systems, offsetting the hardware gap through software optimization. Image source: 2026 China Auto Forum ICE vehicles have long been constrained by thermal and hardware architecture limitations. They often require expensive retrofits to support advanced city-driving features. neueHCT's solution, however, uses a single-fan hardware structure. It fits ICE vehicles without extra cost. It delivers consistent performance across both gasoline and electric models. The algorithm moves beyond rigid rules to understand road logic. This allows for flexible judgment at obscured crosswalks and irregular intersections.
Gasgoo Munich- The 2026 China Automotive Forum Technology Leader Summit convened successfully. Peng Xueming, senior chief engineer at Desay SV, dissected the industry's growing pains as new L3 autonomous driving regulations take effect. His diagnosis: split-architecture systems carry steep compliance costs down the line, while low-cost hardware struggles to sustain long-term OTA updates. Too many players, he argued, prioritize short-term feature launches while overlooking the hidden costs of a vehicle's ten-year lifecycle. Drawing on industry trends, he outlined a strategy centered on a unified central computing platform. Image Source: 2026 China Automotive Forum The competitive landscape has shifted fundamentally now that China's mandatory national standards for L3 autonomous driving have taken effect. The new regulations do more than expand testing requirements; they clearly define safety responsibilities across the entire autonomous driving chain, demanding a traceable system spanning R&D, verification, production, and after-sales. Peng predicts that the old model of rushing to market with cheap hardware is unsustainable. The battleground has moved to a platform's long-term ability to iterate. The next five years, he suggests, will be the critical window for companies to cement their standing in high-level autonomous driving. Currently, a vast number of models rely on a split "big and small brain" architecture. While this approach offers lower upfront costs, it accumulates significant technical debt in compliance and iteration over time. If a vehicle needs to upgrade from L3 to L4 later, companies must reinvest resources across the board—development, verification, and OTA. In contrast, a unified, dual high-compute central brain can share a single software and verification stack, enabling a smooth transition from L3 to L4 and avoiding redundant spending. Simultaneously, the industry is moving beyond the limits of traditional rule-based algorithms to fully embrace an AI-native path, relying on massive computing power to help large models navigate complex
Award Category: China Automotive New Supply Chain Top 100 Field: ADAS/AD Technology: All-Condition Camera Perception Solution Innovation: AUMOVIO's all-condition satellite camera solution integrates rapid defrosting (achieving full clarity from –20°C in six minutes), gas-liquid lens cleaning, and AI-driven low-light image enhancement. This ensures reliable autonomous driving availability in any environment while delivering optimal cost performance. Technical Description: Heating: AUMOVIO's cost-effective heating solution completes de-icing within six minutes and delivers significant cost savings compared to traditional heating methods. Cleaning: Using fixed-nozzle gas-liquid cleaning, the system cleans the camera lens in 200 milliseconds. Compared to retractable nozzle systems, this significantly boosts the operational uptime of autonomous driving systems. Night Vision Solution: A data-driven, scene-adaptive software image enhancement approach improves camera imaging performance at night. Even in harsh winter conditions down to –20°C, AUMOVIO's all-condition camera system operates reliably. Drawing on deep insights into real-world usage, the vehicle can preheat the camera system before the driver arrives, ensuring full perception capability immediately upon entry. While driving, the system maintains lens cleanliness and image clarity. It guarantees stable autonomous driving operation in low temperatures, ice, snow, and complex environments, delivering a consistent experience of safety and convenience. The Gasgoo Awards were initiated by Gasgoo Automotive to continuously spotlight the innovative power of China's new automotive supply chain. Focusing on core technology fields, the awards identify outstanding enterprises and frontier achievements to drive industrial innovation. Building on years of industry research, Gasgoo has simultaneously launched the "China Automotive Industry Innovation Case Library". This initiative systematically documents innovation practices in China's automotive supply chain, unearthing corporate technical capabilities and industrial value. Looking ahead, the case library aims to "bring Chinese solutions to the world," helping Chinese automotive technologies and excellent enterprises enter international markets and promoting global industry exchange and cooperation.
- New Zealand - / - Machinery - / - NZSE:SCT Uber Stock Shock Puts 3 Autonomous Vehicle Shares On Retail Investors’ Radar Waymo’s potential split from Uber has thrown a fresh spotlight on autonomous vehicles and advanced mobility, with one news event suddenly reshaping how investors think about robotaxis, ride hailing, and the companies that support them. A 4% move in Uber’s share price on the headlines shows how quickly sentiment can adjust when partnerships crack and competition heats up. This article looks at 3 stocks exposed to the same news story, each linked to autonomous driving or supporting technologies, and walks through why some investors may see opportunity while others might prefer to stay on the sidelines. Appen (ASX:APX) Overview: Appen is an AI lifecycle company that supplies the data sourcing, human annotation, and model evaluation work that helps train and test systems such as autonomous driving, speech recognition, and other AI applications for clients across technology, automotive, finance, retail, government, and healthcare. Operations: Appen generates about A$104.1 million from Appen China and A$127.9 million from Appen Global, with additional smaller corporate revenue, supported by customers in the United States, China, Australia, and other countries. Market Cap: A$220.2 million Appen offers direct exposure to the data behind autonomous driving, as carmakers and mobility platforms need large volumes of high quality training and evaluation data to keep improving navigation and safety. Partnerships like Waymo and Uber are coming under pressure and more players are pursuing their own technology. The company’s work on multilingual audio benchmarks with Hugging Face and its relationships with 11 auto companies in China position Appen inside many of the AI programs investors are watching, but it is still loss making and heavily tied to volatile AI project spending and a concentrated set of large tech
Abstract Precise trajectory tracking holds significant importance for autonomous vehicle navigation. Conventional lateral control strategies are oriented towards eliminating yaw angle deviation. However, this study reveals that such strategies are inadequate under high-speed and high-curvature conditions, where non-zero steady-state yaw angle deviation exists. An enhanced lateral tracking strategy is put forward.Initially, a trajectory tracking error model is constructed, and a steady—state error analysis is conducted. The results demonstrate that heading angle deviation is a more superior lateral tracking index than yaw angle deviation. Subsequently, a feedforward-feedback controller utilizing heading angle deviation is designed. This controller is compared with a yaw-angle-based controller and an Active Disturbance Rejection Controller (ADRC) strategy based on global lateral displacement.Co-simulations in CarSim/Simulink for circular turning and single lane-change yield two notable contributions: 1) During lane-change maneuvers, the heading-angle-based controller reduces the peak lateral displacement error by approximately 83.3% in comparison to the yaw-angle-based controller, thereby enhancing tracking accuracy. 2) A performance mapping between controller types and path geometries is established. The ADRC strategy exhibits better performance on non-return paths, while the heading-angle-based controller guarantees reliable tracking on return paths.This research offers a theoretical foundation and a practical framework for the selection of adaptive, high-precision trajectory tracking strategies in specific driving scenarios. Acknowledgements This work was supported by the China Shandong Provincial Natural Fund Grant Program Project under grant ZR2024QE068. Funding China Shandong Provincial Natural Fund Grant Program Project under grant ZR2024QE068. Author information Authors and Affiliations Corresponding author Ethics declarations Competing interests The authors declare no competing interests. Additional information Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Rights and permissions Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium
In an Industry First, Ford Will Use Apple Tech to Power Self-Driving Cars: ‘One of the Most Important Announcements’ For the first time, Apple Maps will affect the next generation of self-driving electric vehicles. Key Takeaways - Ford is working with Apple on a new line of electric vehicles. - The automaker is taking the unprecedented step of letting Apple’s software control how electric vehicles operate when they are driving themselves. - The new software will be built into the vehicle, so drivers won’t need an iPhone to use it. Ford is betting on Apple software to shape its autonomous future. The $56 billion automaker said this week that it would use Apple software to power driver-assistance systems in its new line of electric vehicles to be released next year. According to The New York Times, the move puts Apple center stage in Ford cars, giving the iPhone maker an unprecedented, essential role in car operations. Apple CarPlay, which operates in more than 800 car models from major brands like Toyota, Ford and Chevrolet, enables drivers to link their iPhones with their vehicle screens, unlocking functions like Apple Maps. Ford is taking things one step further by letting Apple’s software help control how electric vehicles operate when they are driving themselves, per the Times. For the first time, Apple and Ford engineers are collaborating directly to improve self-driving features in cars set to reach dealerships next year. In the past, Apple worked independently from automakers. Engineers will build the new software into the vehicle, so drivers won’t need an iPhone to use it. “Apple Maps will be embedded in the vehicle, so you don’t have to pay anything extra,” Ford’s CEO Jim Farley said in an interview with the Times. “This is one of the most important announcements for Ford.”
US Navy validates counter unmanned submarine tech in Lanternfish 2026 exercise Ultra Maritime and Anduril demonstrated undersea autonomous threat detection, tracking and classification in the exercise. Read Next: US neighbour could gain domestic engine overhaul capability for future fightersUltra Maritime demonstrated a counter-unmanned underwater vehicle (C-UUV) capability during the US Navy’s Lanternfish 2026 exercise. The demonstration served as a proof of concept for the company`s Sea Sphere deployable sonar system. The sonar was able to detect and classify autonomous undersea threats in a realistic port protection mission setting. Operationally unmanned underwater vehicles (UUVs) have grown in relevance across multiple navies worldwide. They can conduct surveillance, mine-laying, and infrastructure reconnaissance with minimal crew risk. Countering them requires passive and active acoustic sensing, signal processing, and rapid classification. What happened at Lanternfish 2026 Lanternfish is a multilateral naval exercise focussesing on critical undersea infrastructure protection and emerging autonomous vehicle threats. During the exercise, Sea Spear consistently detected, tracked and classified medium- and large-diameter UUVs. The demonstration validated the systems’ ability to provide persistent acoustic sensing while transmitting track data to undersea command centers worldwide. When integrated with Anduril’s Seabed Sentry, Sea Spear forms part of a distributed autonomous undersea network built for rapid deployment and scalable production. The system can be discreetly deployed from both crewed and uncrewed platforms, delivering persistent underwater sensing across remote regions, maritime choke points, and strategically significant waterways. Sea Spear is configurable as either a permanent installation or an attritable asset. More from Military See AllThe technical problem C-UUV systems must solve Detecting a UUV is fundamentally different from detecting a crewed submarine. UUVs run quieter, operate at varied depths, and can be programmed for evasive behavior. Acoustic signatures are weaker and harder to classify against background ocean noise. A C-UUV system must differentiate between a threat
Automotive software, electronics market to reach $519 bn by 2035, outpace vehicle market growth: McKinsey New Delhi [India], July 25 (ANI): The global automotive software and electronics market is projected to grow to USD 519 billion by 2035, expanding at a compound annual growth rate (CAGR) of 4.5 per cent - more than four times faster than the overall vehicle market - as software-defined vehicles, artificial intelligence (AI) and advanced driver assistance systems (ADAS) reshape the industry, according to a McKinsey report. The report titled 'The Automotive Software and Electronics Market Through 2035' said that while the global vehicle market is expected to grow by only around 1 per cent annually, the software and electronics segment will see much stronger expansion as automakers increasingly differentiate vehicles through software, connectivity and AI-enabled features. 'In contrast to the overall vehicle market, which is growing by around 1.0 percent CAGR annually, the global automotive software and electronics market could grow by 4.5 percent CAGR and reach $519 billion by 2035,' the report said. McKinsey said the industry is transitioning towards software-defined vehicles (SDVs) supported by zonal and central computing architectures, enabling over-the-air software updates, enhanced connectivity and generative AI integration. According to the report, 'software, electronics, and gen AI have emerged as critical enablers of innovation, transforming vehicle development and customer experience and business models for OEMs and suppliers.' The report noted that although expectations for fully autonomous vehicles have moderated because of delays in Level 3 and Level 4 deployment, investment has shifted toward near-term opportunities such as ADAS and connected services. McKinsey estimates that by 2035, vehicles equipped with Level 2 and higher driver assistance and autonomous driving capabilities could account for nearly 70 per cent of global vehicle sales, with Level 2 vehicles alone making up 52 per cent of
Quantum technology firm Terra Quantum and software-defined vehicle (SDV) provider Apex.AI have validated the integration of NIST-standardized post-quantum cryptography (PQC) into cloud-connected, autonomous robotic environments. Executed using Apex.OS—a safety-certified software foundation for mobility and robotics—the joint integration establishes quantum-resistant edge-to-cloud communications without altering underlying application logic, developer APIs, or real-time message-passing architectures. Autonomous vehicles, industrial robots, aerospace assets, and connected defense platforms operate on multi-decade service lifecycles. These edge devices rely on continuous cloud connectivity for fleet telemetry, diagnostic logging, over-the-air (OTA) software updates, and remote operation. Because current public-key encryption algorithms (such as RSA and ECC) face long-term vulnerabilities from cryptographically relevant quantum computers, embedding quantum-resistant security is becoming an essential requirement for assets designed to remain active past 2030. The joint solution addresses critical enterprise migration constraints by embedding Terra Quantum’s PQC libraries directly within the Apex.OS middleware layer. Development teams can drop in quantum-safe encryption while maintaining native software control loops, communication pipelines, and existing application workflows. This approach allows organizations operating mission-critical connected assets to de-risk long-term deployments and achieve crypto-agility without incurring the massive capital costs of refactoring core software architectures. Beyond commercial mobility and industrial automation, the architecture is engineered to support complex, interconnected Systems-of-Systems. Designed in alignment with NATO’s Multi-Domain Operations (MDO) framework, the platform establishes a scalable blueprint for securing interoperable communication networks across land, air, maritime, cyber, and defense domains. The successful demonstration proves that NIST-standardized PQC is deployment-ready for embedded systems today, offering a practical pathway toward long-term digital resilience. Review the official press release on PR Newswire here. July 25, 2026 Leave A Comment
Damion Smy 2026 Geely EX2 price and specs 9 Hours Ago Journalist The upcoming affordable electric ute being developed by Ford will use Apple Maps for its built-in navigation system. Due to go into production in 2027, the new ute, widely tipped to revive the Ranchero name, will be one of the first vehicles to have Apple Maps built in. Indeed, all cars based on the ute's Universal Electric Vehicle (UEV) platform will feature Apple Maps. Ford says UEV models will employ Apple Maps for turn-by-turn directions, real-time traffic and incident information, location searching, and EV-friendly routing that includes battery preconditioning. The company is also using road-level information from Apple Maps for the next generation of its BlueCruise hands-free autonomous driving system for highways in North America, which is being developed by the company's LatitudeAI division. The system is set to debut as an option in the new electric ute in 2028. It will be interesting to see if other manufacturers jump on board and adopt Apple Maps for their navigation systems. A significant number of manufacturers base their infotainment systems on the Android Automotive operating system, and many of these come with Google Maps built in and have access to third-party apps through the Google Play Store. The new Ranchero, or whatever it will be christened, could be revealed later this year. Set to be priced from US$30,000 (A$43,000), it will be one of the cheapest vehicles in Ford's American lineup. At present the Blue Oval's US range kicks off with the Maverick dual-cab hybrid, which begins at US$28,145 (A$40,200). A prototype of the ute was spotted in California in June, and it looks to have fairly traditional pickup truck design, apart from the steeply raked windscreen. The new ute will be the first vehicle based on the UEV
Study: Waymo robotaxis had fewer crashes than human drivers across four cities AUSTIN, Texas — Driverless Waymo vehicles crashed less often than human-driven cars across four major U.S. cities, according to a new study, though Austin was an outlier where Waymo’s crash rate was slightly higher than the others. The Insurance Institute for Highway Safety compared crash rates between human-driven vehicles and Waymo’s autonomous vehicles in Phoenix, San Francisco, Los Angeles and Austin. The results found Waymo vehicles crashed 68 percent less than human drivers overall. By city, the study found Waymo had 76 percent fewer crashes than human drivers in Phoenix, 71 percent fewer in Los Angeles and 35 percent fewer in San Francisco. In Austin, Waymo’s crash rate was 4 percent higher than human-driven cars. Waymo said Austin’s results were influenced by the timing of its rollout there. The company said its autonomous vehicles began operating in Austin after the other cities, resulting in fewer sample miles. Waymo also said it wants regulators to standardize how these safety metrics are measured. In a statement, Waymo said, “We welcome this new research from IIHS, which confirms our previous peer-reviewed analyses and reinforces the significant safety benefits of the Waymo Driver. We also support the authors’ recommendation for more robust reporting requirements for AV operators—requirements that Waymo already voluntarily meets.” RELATED: Study finds driverless cars crash less often than human drivers but flags data shortfalls Waymo vehicles have been a regular sight on Austin streets since 2024, logging millions of miles and sometimes drawing attention online for malfunctions caught on camera. Some riders say their experiences have been positive. “Yes I have been in Waymo before. I do like the Waymos because they feel very personalized and luxurious,” said Marie Drosche. She also described an instance where the vehicle stopped
Waymo’s driverless vehicles were involved in 68% fewer police-reportable crashes per vehicle mile traveled than human drivers in the same cities, according to a study released July 23 by the Insurance Institute for Highway Safety, which also concluded that the federal system for monitoring automated vehicles is inadequate to track a large-scale expansion of the technology. The study, “Rise of the Machines: Crash Experiences of Highly Automated Vehicles and Human Drivers,” examined Waymo operations in San Francisco, Phoenix, Los Angeles and Austin, Texas. The findings arrive as driverless fleets push into more markets and as insurers and repairers begin sizing Leave a Reply You must be logged in to post a comment.
- Inspectors randomly selected sample vehicles and power batteries on-site and sent them for testing to verify compliance with national standards. - The inspections came just a week after the MIIT held a meeting with key automakers, urging them to firmly resist irrational competition. China's Ministry of Industry and Information Technology (MIIT) has conducted on-site inspections at plants of GAC Aion and Xpeng (NYSE: XPEV), signaling that the regulator is moving quickly to implement the vehicle quality and safety checks it outlined a week ago. On July 24, the MIIT's first department of equipment industry visited the two automakers to conduct supervisory inspections on their product safety assurance capabilities and production consistency, according to a statement on Friday. The inspections focused on how the companies maintain production access conditions, including intelligent connected vehicle safety assurance capabilities, design, development and production capabilities, and production consistency assurance capabilities, the MIIT said. Inspectors randomly sampled vehicles and power batteries on site and sent them to relevant institutions for testing, including compliance with national standards, the statement showed. The MIIT said it will continue to organize supervisory inspections of automobile and motorcycle manufacturers and their products, deal seriously with companies found to have problems, firmly hold the bottom line of vehicle product safety, and effectively protect consumers' legitimate rights and interests. GAC Aion is the new energy vehicle (NEV) subsidiary of GAC Group. The Xpeng facility inspected was its Zhaoqing plant, the company's first self-built plant. The inspections are the MIIT's latest move to tighten oversight of the auto industry. On July 17, the ministry held a meeting with key vehicle manufacturers, requiring them to firmly resist irrational competition and strengthen product testing, validation and safety assessment. The meeting placed particular emphasis on strengthening the safety assessment of combined driving assistance and autonomous driving
Automotive Industry Honda, Nissan Consider Standardizing Control Units for Software-Defined Vehicles Honda and Nissan hope to reduce R&D costs, speed time to market, and to take advantage of economies of scale. TOKYO—In an effort to reduce development costs, Honda Motor Co. and Nissan Motor Co. are talking about standardizing the electronic control units (ECUs) that will be used in future software-defined vehicles (SDVs). The automakers could begin installing the units in vehicles as early as 2029. Although a proposed merger between the two companies was scrapped, Honda and Nissan are seeking to strengthen their relationship jointly developing vehicle components. SDVs are next-generation vehicles with software that can be updated over the internet, allowing manufacturers to improve performance and add features, such as autonomous-driving capabilities. Honda and Nissan plan to jointly develop a central ECU that oversees the entire vehicle. They are also considering supplying the unit to Mitsubishi Motors Corp., in which Nissan holds a 26 percent stake, and exploring whether they can standardize the underlying software. Conventional vehicles typically contain dozens of ECUs, each controlling a separate function, such as the engine or brakes. SDVs, by contrast, require a central ECU capable of handling frequent updates. Such systems are difficult to design and costly to develop. By working together, Honda and Nissan hope to reduce R&D costs, speed time to market, and to take advantage of economies of scale.Looking for quick answers on assembly and manufacturing topics? Try Ask ASM, our new smart AI search tool. Ask ASM Looking for a reprint of this article? From high-res PDFs to custom plaques, order your copy today!