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 Self-Driving Cars Still Can't Handle School Zones

    School zones are a surprisingly tough challenge for autonomous vehicles. The combination of flashing beacons, variable speed limits, unpredictable children, and crossing guards creates a perception and decision-making nightmare. We break down exactly why the technology still stumbles on these critical safety zones, from camera limitations in low light to the challenge of recognizing human gestures. Plus, Lucas and Luna discuss how companies like Waymo and Cruise are approaching the problem, and why a simple sign change could make a big difference.

    #SelfDrivingCars #AutonomousVehicles #SchoolZones #AVs #Waymo #Cruise #GM #Lidar #Safety #Technology #FexingoBusiness #BusinessPodcast #Tech #Mobility #PerceptionSystems #VariableSpeedLimits #EdgeCases #Fexingo

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    6 min
  • Why Self-Driving Cars Still Can't Handle Snow and Ice

    Even in 2026, autonomous vehicles struggle to navigate snow-covered roads. This episode explains why ice and snow are uniquely difficult—blocking sensors, hiding lane markings, and challenging traction control systems. We look at what companies like Waymo and Tesla are doing to winterize their fleets, and discuss why this problem may take years to fully solve. Includes a look at the current market for autonomous vehicle stocks and the latest industry developments.

    #SelfDrivingCars #AutonomousVehicles #Snow #Ice #WinterWeather #Lidar #Cameras #Sensors #Waymo #Tesla #Technology #Business #Podcast #FexingoBusiness #WinterDriving #MachineLearning #EdgeCase #Autonomy

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    7 min
  • Why Self-Driving Cars Still Can't Handle Police Traffic Stops

    Self-driving cars have mastered highways and parking lots, but pulling over for a police officer remains a perplexing problem. This episode examines the police traffic stop scenario—why autonomous vehicles struggle to interpret flashing lights, hand signals, and the unspoken rules of the road when a cop is involved. We look at recent video from Waymo, compare Tesla's Autopilot limitations, and connect the challenge to broader industry timelines. Plus, how the Boring Company's new funding highlights the gap between tunnel visions and real-world complexity. A tight focus on one critical edge case that AVs must crack before truly driverless fleets can operate everywhere.

    #SelfDrivingCars #AutonomousVehicles #PoliceTrafficStops #EdgeCase #Waymo #Tesla #Autopilot #BoringCompany #Lidar #MobilityTech #Technology #FexingoBusiness #BusinessPodcast #Safety #Regulation #AVIndustry #Investing #EVStocks

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

    Episode 130 of Self-Driving Cars with Fexingo tackles a stubborn problem: heavy rain. Lucas and Luna explore why lidar, cameras, and radar all fail in downpours, how water droplets scatter laser pulses and block visual cues, and what companies like Waymo, Mobileye, and Tesla are doing to cope. They reference Mobileye CEO Amnon Shashua's recent transition and the company's push into robotaxis, alongside market data on Tesla's 16% drop this week. The hosts also explain a promising workaround—using HD maps and probabilistic models to 'see through' rain. Plus, a brief note on why the show stays ad-free and how listener support helps. No fluff, just the science and business of self-driving tech.

    #SelfDrivingCars #AutonomousVehicles #HeavyRain #Lidar #Mobileye #Waymo #Tesla #Robotaxis #SafetyCritical #AdverseWeather #PerceptionSystems #HDMaps #FexingoBusiness #BusinessPodcast #Technology #Innovation #AutonomousDriving #WeatherChallenges

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    8 min
  • Self-Driving Cars Still Cant Handle Dead Deer on the Road

    Episode 129 of Self-Driving Cars with Fexingo explores why autonomous vehicles struggle with dead animal carcasses on the road. Lucas and Luna examine how lidar and cameras fail to classify deer that are no longer moving, the surprising size of the problem, and what it means for rural roads and highway safety. They also touch on Tesla's recent door handle safety concerns and how the AV industry is training models on decaying shapes. A concrete look at an overlooked edge case.

    #SelfDrivingCars #AutonomousVehicles #Lidar #MobilityTech #Tesla #Waymo #Cruise #RoadSafety #WildlifeCollisions #EdgeCases #AVTechnology #Fexingo #Technology #FexingoBusiness #BusinessPodcast #Podcast #DeerCarcasses #DeepLearning

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    10 min
  • Why Self-Driving Cars Still Get Confused by Roundabouts

    Roundabouts are spreading across the US — more than 10,000 now. But self-driving cars still struggle with them. Lucas and Luna break down the specific challenge: the constant negotiation of yield, the lack of clear signaling, and why a Waymo in Phoenix handles a roundabout differently than a Cruise in Austin. They also look at how Tesla and Mobileye are tackling the problem with new neural network approaches. Plus, a quick look at how the market is reacting — Rivian and Lucid up, Tesla down — and what that says about investor confidence in autonomy.

    #SelfDrivingCars #Roundabouts #AutonomousVehicles #Waymo #Cruise #Tesla #Mobileye #Lidar #NeuralNetworks #TrafficEngineering #Phoenix #Austin #Rivian #Lucid #Technology #Mobility #FexingoBusiness #BusinessPodcast

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    8 min
  • Why Self-Driving Cars Still Can't Handle Parking Lots

    Lucas and Luna explore why autonomous vehicles struggle with parking lots—a deceptively complex environment of narrow aisles, erratic pedestrians, and ambiguous signage. They discuss how Waymo and Cruise handle structured parking vs. sprawling retail lots, and why Tesla's vision-only approach faces unique challenges. With specific examples from the latest testing data and a look at how computer vision models get confused by dim lighting and tight corners, this episode reveals why parking remains a stubborn edge case for self-driving technology. The conversation also touches on recent market moves by Tesla and Rivian, and why sensor fusion may be the key to solving the problem. No scripted intros or outros—just a sharp, focused look at the one parking lot problem that keeps autonomous vehicles from pulling into a space like a human driver.

    #AutonomousVehicles #SelfDrivingCars #ParkingLots #Waymo #Cruise #Tesla #Rivian #LIDAR #ComputerVision #SensorFusion #EdgeCases #Technology #Podcast #FexingoBusiness #BusinessPodcast #MobilityTech #AVTesting #UrbanDriving

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    11 min
  • Why Self-Driving Cars Still Can't Handle Four-Way Stops

    Episode 126 of Self-Driving Cars with Fexingo tackles one of the most deceptively hard problems in autonomous driving: the four-way stop. Lucas and Luna break down why this seemingly simple intersection — governed by a first-come-first-serve rule that humans handle with eye contact and gesture — becomes a nightmare of prediction, intent, and social negotiation for AV software. They walk through a specific 2025 study from the University of Michigan showing that autonomous vehicles at four-way stops fail to reach a consensus on turn order over 40 percent of the time in mixed traffic. They also touch on how companies like Waymo and Cruise are tackling the problem with V2X communication, and reference recent stock moves in Tesla (down nearly 4 percent this week) and Lucid (up 23 percent) as context for investor patience. If you've ever sat at a four-way stop wondering who goes next, this episode explains why your self-driving car is wondering too.

    #SelfDrivingCars #AutonomousVehicles #FourWayStops #AVChallenges #Waymo #Cruise #Tesla #Lucid #V2X #IntersectionLogic #TrafficNegotiation #UniversityOfMichigan #AutonomousDriving #Technology #BusinessPodcast #FexingoBusiness #MobilityTech #Lidar

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    8 min
  • Why Self-Driving Cars Still Can't Handle Emergency Vehicle Sirens in 2026

    Episode 125 of Self-Driving Cars with Fexingo tackles a persistent edge case: why autonomous vehicles still struggle to locate emergency vehicles by sound alone. Lucas and Luna break down the acoustic challenges — from Doppler shifts to multi-path interference — and compare lidar, camera, and microphone-based approaches. They reference Tesla's latest sensor suite, the recent $300 million Sila battery factory investment, and what actually happened when an AV got confused by a siren in San Francisco last month. If you've ever wondered why your robotaxi doesn't pull over like a human driver, this episode has the answer.

    #SelfDrivingCars #AutonomousVehicles #EmergencyVehicles #Lidar #SoundLocalization #AcousticSensing #Tesla #Sila #Sensors #EdgeCases #Robotaxi #SanFrancisco #AVTechnology #Technology #FexingoBusiness #BusinessPodcast #AutonomousDriving #SirenDetection

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    13 min
  • Self-Driving Cars Still Can't Handle Dirt Roads

    Lucas and Luna dive into one of the most stubborn edge cases for autonomous vehicles: unpaved dirt and gravel roads. While highway driving is nearly solved, rural and off-road routes present unique challenges — from loose surface material that scrambles LiDAR returns to dust clouds that blind cameras. The hosts examine why Tesla's vision-only approach struggles where lidar-heavy systems also fail, and discuss how the industry is adapting its sensor fusion strategies for the last mile of rural autonomy. They reference recent trades in Rivian and Lucid as indicators of market sentiment around off-road and rugged autonomy, and touch on the broader implications for autonomous trucking and agricultural vehicles.

    #SelfDrivingCars #AutonomousVehicles #DirtRoads #GravelRoads #LiDAR #Tesla #Rivian #Lucid #SensorFusion #EdgeCases #RuralAutonomy #AutonomousTrucking #Technology #Business #FexingoBusiness #BusinessPodcast #MobilityTech #AVChallenges

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    9 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.