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 Buses

    Episode 104 of Self-Driving Cars with Fexingo tackles a deceptively tricky edge case: school buses. Lucas explains why autonomous vehicles struggle with the unique combination of irregular stops, flashing lights, and unpredictable kid behavior. Luna points out that even lidar can be fooled by the bus's reflective yellow paint. They reference recent stock moves in Rivian and Lucid to frame the broader market skepticism. Plus, a look at how Waymo and Cruise are quietly testing in suburban school zones. A focused 10-minute drill into one of the most stubborn unsolved problems in autonomy.

    #SelfDrivingCars #AutonomousVehicles #SchoolBuses #Lidar #Waymo #Cruise #Rivian #Lucid #EdgeCases #AutonomousTech #Mobility #Technology #Business #FexingoBusiness #BusinessPodcast #Podcast #SelfDriving #AV

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    7 min
  • Why Self-Driving Cars Still Can't Handle Speed Bumps

    In this episode, Lucas and Luna explore why autonomous vehicles still struggle with a mundane but critical feature of urban roads: speed bumps. They examine how lidar and camera systems interpret raised pavement, the problem of inconsistent municipal designs, and why even the most advanced sensor suits fail on a standard 12-foot-wide hump. With Tesla down nearly 3% and Rivian dropping 13% this week, the hosts discuss how these failures impact the business case for robotaxis and why speed bumps remain a harder engineering challenge than highway driving or even roundabouts.

    #SelfDrivingCars #AutonomousVehicles #Lidar #SpeedBumps #UrbanDriving #Robotaxi #Tesla #Rivian #Luna #Lucas #Fexingo #Technology #BusinessPodcast #SensorFusion #PerceptionSystems #GroundTruth #AVInfrastructure #MobilityTech

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    7 min
  • Why Lidar Still Fails on Wet Roads at Night

    Episode 102 of Self-Driving Cars with Fexingo dives into a persistent blind spot for autonomous vehicles: wet roads after dark. Lucas and Luna break down why water on asphalt turns lidar into a noise machine, how retroreflectivity tricks sensors, and why Tesla's camera-only approach has an unexpected edge here. They reference recent market moves for lidar stocks like DRIV and IDRV, plus Stellantis's steep slide. The conversation covers a 2025 University of Michigan study that found a 35% increase in perception errors on wet roads at night, and explains why the solution might involve polarizing filters or thermal sensors. No ads — just clear, specific tech talk.

    #Lidar #WetRoads #NightDriving #AutonomousVehicles #SelfDrivingCars #SensorFusion #Retroreflectivity #DRIV #IDRV #STLA #Tesla #UniversityOfMichigan #Technology #FexingoBusiness #BusinessPodcast #SelfDrivingCarsWithFexingo #PerceptionErrors #PolarizingFilters

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    9 min
  • Why Self-Driving Cars Still Cant Handle Parking Lots

    Episode 101 of Self-Driving Cars with Fexingo digs into a deceptively hard problem: autonomous vehicles in parking lots. While highway driving is increasingly solved, the unstructured chaos of a parking lot — with pedestrians, shopping carts, blind corners, and erratic drivers — remains a massive challenge. Lucas and Luna discuss why lidar and cameras struggle with the 'last 50 feet' of autonomy, how companies like Tesla and Waymo approach the problem differently, and why even in 2026, your car still can't park itself reliably in a crowded lot. They also touch on recent market moves for Tesla and Rivian, and the surprising physics of why parking lots are harder than highways.

    #SelfDrivingCars #AutonomousVehicles #Lidar #ParkingLots #Tesla #Rivian #Waymo #AutonomousParking #Technology #FexingoBusiness #BusinessPodcast #AI #Mobility #ComputerVision #Sensors #LastMile #Autonomy #AVChallenges

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    9 min
  • Why Self-Driving Cars Cant Handle Emergency Vehicles in 2026

    In this episode of Self-Driving Cars with Fexingo, Lucas and Luna explore why autonomous vehicles still struggle to detect and yield to emergency vehicles like ambulances and fire trucks. They discuss the sensor limitations (lidar vs. siren triangulation), a recent federal demand that AV companies stop blocking first responders, and how Tesla's stock dip reflects market skepticism. The hosts also explain why solving this problem is critical for public acceptance, using real-world examples from 2026.

    #SelfDrivingCars #AutonomousVehicles #EmergencyVehicles #Lidar #Tesla #FirstResponders #AVRegulation #TechFailures #SensorFusion #SirenDetection #AutonomousDriving #Safety #FexingoBusiness #BusinessPodcast #Technology #Podcast #SelfDriving #2026

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    8 min
  • Why Self-Driving Cars Still Cant Handle Dirt Roads

    Episode 99 of Self-Driving Cars with Fexingo: why dirt roads remain a nightmare for autonomous vehicles in 2026. Lucas and Luna dive into the specific sensor and mapping challenges posed by loose gravel, dust, and changing terrain profiles. They reference Tesla's recent struggles with unpaved routes and compare approaches from Waymo and Chinese automakers like NIO. The conversation also touches on how lidar and camera systems degrade in dusty conditions, and why high-definition maps fail when roads are ungraded. A must-listen for anyone following the real-world limits of autonomy.

    #SelfDrivingCars #AutonomousVehicles #Lidar #DirtRoads #Tesla #Waymo #NIO #GravelRoads #Mapping #SensorFusion #AVLimits #UnpavedRoads #Technology #BusinessPodcast #FexingoBusiness #FutureOfMobility #Autonomy #Podcast

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    8 min
  • Why Self-Driving Cars Still Cant Handle Left Turns

    In this episode of Self-Driving Cars with Fexingo, Lucas and Luna dive into one of the most deceptively hard challenges for autonomous vehicles: the unprotected left turn. While highways and right turns have largely been solved, left turns across traffic remain a major bottleneck for robo-taxi deployment in 2026. Lucas breaks down why the problem is fundamentally harder than it looks — it involves predicting human driver intent, dealing with occluded vision, and making split-second probabilistic decisions. He references Tesla's struggles with the maneuver at a specific Phoenix intersection, and contrasts Waymo's more cautious approach in San Francisco. Luna brings up new data from the University of Michigan showing that left-turn maneuvers account for over 60 percent of autonomous vehicle disengagements in urban settings. The conversation also touches on how lidar's limitations with glossy black cars compound the problem when turning across multiple lanes of traffic. Lucas explains why some companies are now programming their cars to 'yield aggressively' — a counterintuitive tactic that actually reduces hesitation-related accidents.

    #SelfDrivingCars #AutonomousVehicles #LeftTurns #Waymo #Tesla #Lidar #UnprotectedLeft #Robotaxi #AVChallenges #TrafficSafety #Phoenix #SanFrancisco #UniversityOfMichigan #MachineLearning #Prediction #FexingoBusiness #BusinessPodcast #Technology

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    10 min
  • Why Lidar Fails When a Car Is Covered in Mud

    Episode 97 of Self-Driving Cars with Fexingo tackles a messy problem: why autonomous vehicles can't see when mud, dirt, or road grime covers the sensors. Lucas and Luna break down the physics of lidar attenuation through opaque layers, using real-world testing data from a major AV operator that saw a 40% perception failure rate on muddy vehicles after off-road or construction zone exposure. They discuss why wiper systems and self-cleaning coatings haven't solved it yet, and how the industry is approaching sensor fusion as a workaround—keeping the vehicle in a degraded mode until a wash station is reached. The conversation ties into broader market signals: Rivian's recent stock dip and Toyota's surprising strength, suggesting investors are watching which companies solve dirty-sensor reliability. A concrete, undercovered edge case that exposes the gap between lab demos and real-world autonomous driving.

    #SelfDrivingCars #Lidar #AutonomousVehicles #SensorFusion #Mud #AVSafety #DriverlessTech #Rivian #Toyota #LidarLimitations #AutonomousEdgeCases #VehicleDirt #PerceptionFailure #FexingoBusiness #Technology #BusinessPodcast #MobilityTech #CleanSensors

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    8 min
  • Why Self-Driving Cars Still Can't Handle Flooded Roads

    Episode 96 of Self-Driving Cars with Fexingo dives into a persistent edge case: flooded roads. Lucas and Luna explain why standing water confuses lidar, cameras, and ultrasonic sensors, using real-world examples like Hurricane Harvey and recent 2026 storms. They discuss how water's reflectivity, refraction, and depth estimation challenges lead to puddles that look like mirrors, depthless voids, or impassable lakes. The episode also touches on Rivian's 20% stock jump tied to its off-road autonomous ambitions, and why hydroplaning risk remains unsolved by software. A concrete look at why your self-driving taxi still won't drive through a deep puddle in July 2026.

    #AutonomousVehicles #SelfDrivingCars #FloodedRoads #Lidar #ComputerVision #EdgeCases #Rivian #AVTechnology #Hydroplaning #SensorFusion #WeatherChallenges #AutonomousDriving #DeepLearning #TechPodcast #Technology #FexingoBusiness #BusinessPodcast #MobilityTech

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    10 min
  • Why Self-Driving Cars Cant Handle Emergency Vehicles

    In this episode, we explore why autonomous vehicles still struggle to detect and respond to emergency vehicles like fire trucks, ambulances, and police cruisers. Lucas breaks down the sensor limitations — lidar reflections on flashing lights, audio confusion with sirens, and the lack of a standardized V2V protocol for emergency alerts. Luna brings up Rivian's recent 19.8% stock surge amid its new emergency-vehicle detection patent filings, and we discuss Tesla's current approach using vision-only systems. We also cover the broader industry challenge: until there's a universal protocol like the European eCall system adapted for autonomy, emergency vehicles will remain a blind spot. Plus, a quick note on how listener support keeps this show ad-free.

    #SelfDrivingCars #AutonomousVehicles #EmergencyVehicles #FireTrucks #Ambulances #Lidar #Tesla #Rivian #Technology #Business #Podcast #FexingoBusiness #BusinessPodcast #AutonomousDriving #SensorFusion #V2VCommunication #EmergencyResponse #TechNews

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    7 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.