Self-Driving Cars with Fexingo: Autonomous Vehicles, Lidar, and Mobility Tech

Self-Driving Cars with Fexingo: Autonomous Vehicles, Lidar, and Mobility Tech

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Self-Driving Cars with Fexingo: Autonomous Vehicles, Lidar, and Mobility Tech episodes

  • Why Autonomous Vehicles Still Cant Handle Train Crossings in 2026

    Episode 75 of Self-Driving Cars with Fexingo dives into a persistent blind spot: autonomous vehicles and railroad crossings. Lucas and Luna explore why even the most advanced sensor stacks—lidar, radar, cameras—struggle with active train crossings, from misjudging gate arms to misreading flashing lights. They break down two recent incidents: a Waymo that hesitated at a crossing in Arizona, causing a 20-minute backup, and a Cruise vehicle that drove around a lowered gate in San Francisco. Both cases highlight the gap between controlled testing and real-world variability. The hosts also tie in market reactions: autonomous driving ETF DRIV is down 8% over the past five days, reflecting investor skepticism about near-term deployment. Along the way, they discuss how regulators and companies are responding—everything from geofencing to dedicated crossing protocols. This episode continues the show's 'can't handle' series with a focus on a specific, high-stakes infrastructure challenge that remains unsolved as of mid-2026.

    #AutonomousVehicles #SelfDrivingCars #TrainCrossings #RailroadSafety #Waymo #Cruise #Lidar #SensorFusion #AVBlindSpots #Infrastructure #Regulation #Technology #MobilityTech #DRIV #InvestorSkepticism #FexingoBusiness #BusinessPodcast #SelfDrivingCarsWithFexingo

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    10 min
  • Why Autonomous Vehicles Still Can't Handle Construction Workers

    Episode 74 of Self-Driving Cars with Fexingo examines one of the most dangerous edge cases for autonomous vehicles: construction workers directing traffic in work zones. Lucas and Luna discuss why even the latest sensor suites struggle with human hand signals, how a recent incident involving a Waymo vehicle in Phoenix exposed the gap, and what companies like Waymo and Aurora are doing to solve it. The episode also touches on the broader market sell-off in EV and AV stocks this week, including Tesla's 6.3% drop and Rivian's 10% plunge. If you're following the autonomous vehicle industry, this is the edge case nobody's talking about enough.

    #AutonomousVehicles #SelfDrivingCars #ConstructionZones #Waymo #AuroraInnovation #HandSignals #EdgeCases #AVSafety #Lidar #ComputerVision #Robotaxi #Tesla #Rivian #Technology #BusinessPodcast #FexingoBusiness #MobilityTech #AutonomousDriving

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    10 min
  • Why Self-Driving Cars Still Can't Handle Wildfires and Smoke

    Episode 73 of Self-Driving Cars with Fexingo tackles an overlooked challenge for autonomous vehicles: navigating through wildfire smoke. Lucas and Luna break down how particulate matter scatters lidar beams, why camera-based systems lose contrast in haze, and what it means for AVs in the Western US during fire season. With Tesla down 6.3% and the Global X Autonomous & Electric Vehicles ETF losing 7.2% over the past five days, the hosts connect the technical hurdles to real-world deployment timelines. They also explore how startups and research labs are testing sensor fusion in smoke chambers, and why regulators are starting to ask questions. A specific, grounded conversation for anyone following the gap between AV hype and edge cases.

    #AutonomousVehicles #SelfDrivingCars #WildfireSmoke #Lidar #SensorFusion #EdgeCases #Tesla #Robotaxis #AVSafety #Technology #ClimateAdaptation #Waymo #Cruise #FexingoBusiness #BusinessPodcast #MobilityTech #AutonomousDriving #SmokeNavigation

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    10 min
  • Why AVs Still Can't Handle Dust Storms

    In this episode, we look at the surprising challenge of dust storms for autonomous vehicles. While rain and snow are well-known obstacles, airborne particulate matter from dust can blind lidar and confuse cameras in ways that are harder to predict and model. Lucas shares recent test data from Waymo and WeRide showing how dust causes false positives and degraded sensor performance. Luna points out that this is especially problematic for the Middle East and parts of the American Southwest where dust storms are common. They discuss how companies are approaching the problem with multispectral sensors and machine learning, and why dust could delay AV deployments in arid regions for years. Market context: GM and Ford stocks have dipped, and the industry's focus on dry-climate testing is intensifying.

    #AutonomousVehicles #SelfDrivingCars #DustStorms #Lidar #Waymo #WeRide #AVChallenges #SensorFusion #MachineLearning #AutonomousDriving #Weather #Technology #Business #Podcast #FexingoBusiness #BusinessPodcast #SelfDrivingCarsPodcast #AVSafety

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    7 min
  • Why Autonomous Vehicles Still Can't Handle Hand Signals from Traffic Cops

    Episode 71 of Self-Driving Cars with Fexingo: Autonomous Vehicles, Lidar, and Mobility Tech explores a persistent edge case: how self-driving car sensors interpret — or fail to interpret — hand signals from police officers directing traffic. With Tesla down over 5% in the past five days and Rivian dropping 10%, the hosts discuss why solving this problem is both a technical challenge and a regulatory puzzle. Lucas and Luna break down why LIDAR and camera-based systems struggle with ad-hoc human gestures, how companies like Waymo and Cruise are approaching the issue, and whether vehicle-to-infrastructure communication or AI models could be the fix. No fluff, just the specific reasons a cop raising a palm can confuse an autonomous vehicle's decision-making pipeline.

    #AutonomousVehicles #SelfDrivingCars #HandSignals #TrafficCops #EdgeCases #LIDAR #Waymo #Cruise #Tesla #Rivian #AI #ComputerVision #VehicleToInfrastructure #Safety #Technology #FexingoBusiness #BusinessPodcast #2026

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    9 min
  • Why Self-Driving Cars Still Can't Handle Construction Zones in 2026

    In this episode, Lucas and Luna dig into a persistent blind spot for autonomous vehicles: construction zones. Despite billions in R&D, robotaxis and ADAS systems still struggle with the chaotic, temporary geometry of road work. Lucas cites recent data showing that Waymo's Phoenix fleet disengages at construction sites 3x more often than on standard highways. They discuss why lidar and camera systems fail against orange barrels, flaggers, and shifting lane markings. Tesla's FSD V13 performance on construction detours is compared unfavorably to Mobileye's REM-mapped approach. The hosts also touch on how Department of Transportation pilot programs are now mandating AV-friendly signage, and what that means for the timeline of Level 4 autonomy. A focused, concrete look at one of the hardest unsolved problems in self-driving tech.

    #SelfDrivingCars #AutonomousVehicles #ConstructionZones #Waymo #Tesla #Mobileye #Lidar #FSD #Robotaxi #ADAS #RoadWork #AVSafety #Phoenix #Level4 #Technology #FexingoBusiness #BusinessPodcast #MobilityTech

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    8 min
  • Why Autonomous Vehicles Still Can't Handle Fog

    Episode 69 of Self-Driving Cars with Fexingo dives into one of autonomy's most stubborn weather challenges: fog. Lucas and Luna break down why fog wreaks havoc on lidar, cameras, and radar—and how the industry is fighting back. They reference Waymo's recent testing in San Francisco's summer fog, discuss why traditional sensor fusion breaks down below 50 meters of visibility, and explore promising fixes like short-wave infrared lidar and thermal cameras. They also touch on Tesla's strategy of betting on pure vision and the stock market's recent sell-off in EV names. Listeners learn the concrete physics behind why fog is fundamentally different from rain or snow for self-driving cars.

    #SelfDrivingCars #AutonomousVehicles #Fog #Lidar #Waymo #Tesla #SensorFusion #AutonomousDriving #AVs #Weather #Technology #Business #Podcast #FexingoBusiness #BusinessPodcast #Tech #Innovation #Safety

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    8 min
  • Why Autonomous Vehicles Still Cant Handle Snow

    Lucas and Luna explore why snow remains one of the toughest challenges for self-driving cars. They break down the physics: falling snow confuses lidar, snow-covered roads erase lane markings, and salt spray creates false positives. They reference Waymo's limited winter operations in Minnesota, Tesla's struggles with Autopilot in snowy conditions, and the latest lidar improvements from Luminar. The conversation also touches on the recent fatal Tesla crash in Texas and why weather is a key barrier to full autonomy. Plus, a low-key mention of listener support via Buy Me a Coffee.

    #Snow #AutonomousVehicles #Lidar #Waymo #Tesla #Autopilot #Luminar #SelfDrivingCars #Weather #WinterDriving #FexingoBusiness #BusinessPodcast #Technology #Mobility #AVs #CrashSafety #LaneMarkings #SensorFusion

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    8 min
  • Why Autonomous Vehicles Still Can't Handle Rain

    In this episode, Lucas and Luna explore why heavy rain remains a stubborn challenge for self-driving cars. They break down how raindrops scatter lidar beams, how camera-based systems lose lane markings, and why even radar struggles with water attenuation. Drawing on recent research from Waymo and the University of Michigan, they explain why the industry's current sensor fusion approach still fails in moderate downpours. They also discuss how Tesla's vision-only strategy faces particular difficulties, and why the solution may require new kinds of radar or machine learning models trained on rain data. A clear, technical look at why weather remains a critical bottleneck for autonomous vehicle deployment.

    #AutonomousVehicles #SelfDrivingCars #Lidar #Rain #Weather #Technology #Waymo #Tesla #Radar #Camera #SensorFusion #MachineLearning #Mobility #Transportation #Safety #FexingoBusiness #BusinessPodcast #Tech

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    8 min
  • How China Built a Dominant Robotaxi Fleet

    Episode 66 of Self-Driving Cars with Fexingo examines China's surprising lead in autonomous ride-hailing. Lucas and Luna break down a recent TechCrunch mobility scorecard that shows Chinese robotaxi fleets—operated by Baidu, Pony.ai, and WeRide—now outnumber U.S. deployments by nearly 3 to 1. They discuss the regulatory and infrastructure factors behind the gap, from city-level AV permits in Beijing and Shanghai to the slower rollout in American cities like San Francisco and Phoenix. The hosts also touch on how Tesla (down 1.5% this week) and Rivian (down 1.4%) are approaching autonomy differently, and what the DRIV and IDRV ETFs reveal about investor sentiment. A candid moment about listener support via Buy Me a Coffee keeps the show ad-free. If you want to understand why your next airport ride might be driverless—and why it's more likely to happen in Shenzhen than San Francisco—this episode is for you.

    #ChinaRobotaxi #AutonomousVehicles #Baidu #PonyAI #WeRide #TechCrunchMobility #Tesla #Rivian #DRIV #IDRV #Lidar #SelfDrivingCars #AVFleet #Beijing #SanFrancisco #Technology #FexingoBusiness #BusinessPodcast

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    12 min

About Self-Driving Cars with Fexingo: Autonomous Vehicles, Lidar, and Mobility Tech

From the publisher's feed

Lucas and Luna dissect the business of autonomous mobility — not the hype, but the unit economics, sensor supply chains, and regulatory timelines that separate viable players from vaporware. Each episode opens with fresh data: lidar sensor prices from Yole Group, NHTSA accident reports, Waymo and Cruise fleet expansion figures, and the latest SPAC filings from mobility-tech startups. Lucas, a journalist covering automotive tech for a decade, presses the numbers: 'Is L4 deployment actually accelerating, or are we just seeing more test miles reported?' Luna, an engineer turned product strategist, matches him with on-the-ground sourcing — what a procurement manager at a Tier 1 supplier told her about LiDAR yield rates, or why a city planner in Austin chose to restrict autonomous delivery bots. Together, they build a grounded picture of who's winning the talent war (former Tesla Autopilot engineers now at Aurora), which chip fabs are securing long-term contracts for radar SoCs, and why insurance premiums for robo-taxis remain a hidden drag on unit economics. They don't forecast a future; they interrogate the present. Can the autonomous-vehicle industry survive a capital winter? When does a prototype become a product? This show is for the investor, engineer, or policy analyst who needs to know where the puck is — not where the press release says it is.