Long Island Autonomous Vehicle Accident
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Tesla Autopilot failures, ADAS defects, and self-driving car accidents involve multiple defendants and complex products liability claims. We build the evidence record \u2014 EDR data, telematics logs, software version history \u2014 that holds manufacturers accountable. No fee unless we win.
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Autonomous vehicle accidents involving Tesla Autopilot, Waymo, Uber AV, and other Level 2–4 systems can support products liability claims against the vehicle manufacturer, software developer, and fleet operator — in addition to negligence claims against the human operator. New York’s serious injury threshold under Insurance Law §5102(d) applies. Products liability claims are subject to a 3-year statute of limitations under CPLR §214 (or §214-c for latent defects). Critical evidence includes EDR data, vehicle telematics logs, OTA software version history, and NHTSA complaint records. AV accidents often support punitive damages claims when the manufacturer knew of a defect and continued deployment.
Last updated: April 2026 · Every case is unique — these ranges reflect general New York outcomes and are not guarantees.
Autonomous Vehicle Accident Cases We Handle
What Type of AV or ADAS Failure Caused Your Accident?
Tesla Autopilot / FSD Failures
AEB / ADAS System Failures
Waymo / Robotaxi Accidents
LiDAR / Camera Sensor Defects
Fleet Operator Negligence
Software Version / OTA Update Defects
Proven Track Record
Autonomous Vehicle & ADAS Failure Results
When EDR data, telematics logs, and products liability expert testimony establish that an autonomous system defect caused the accident, these cases produce significant results against manufacturers and fleet operators.
$2.1M
Tesla Autopilot Phantom Braking — Rear-End Chain Collision
Tesla operating in Autopilot mode executed sudden, unprovoked braking at highway speed on the Long Island Expressway; following vehicles were unable to stop in time; plaintiff sustained cervical disc herniation requiring anterior cervical discectomy and fusion at C5-C6; defendants included Tesla Inc. (design defect and failure to warn), the Tesla owner (negligent entrustment), and at-fault following driver; EDR data extracted by plaintiff's expert confirmed Autopilot was engaged and no operator input was registered in the 10 seconds before the braking event; punitive damages sought on the basis that Tesla received over 12,000 phantom braking complaints in NHTSA data prior to this incident
$1.4M
AEB Failure — ADAS Did Not Detect Pedestrian
Vehicle equipped with automatic emergency braking system failed to detect a pedestrian crossing at an unlit intersection in Nassau County; the ADAS system’s forward collision warning and auto-brake did not activate; plaintiff, a 67-year-old crossing in a marked crosswalk, sustained bilateral lower extremity fractures and traumatic brain injury; products liability claim against the vehicle OEM for design defect in the LiDAR-camera sensor fusion algorithm; manufacturer’s own internal validation testing, obtained through discovery, showed the system had a 9% failure rate for pedestrian detection at night
$875K
Waymo AV — Intersection Decision Algorithm Error
Waymo autonomous vehicle operating in driverless mode yielded incorrectly at a four-way intersection in New York City, resulting in a T-bone collision with a driver proceeding on right-of-way; plaintiff’s vehicle sustained significant structural damage; soft tissue injuries with cervical radiculopathy confirmed by EMG; fleet operator and Waymo parent company joined as defendants; telematics logs obtained in discovery confirmed the AV’s software made an incorrect intersection priority determination; design defect claim based on failure of the decision-making algorithm to correctly process right-of-way rules under dynamic traffic conditions
$650K
Lane Departure — Tesla FSD Beta Failure to Maintain Lane
Tesla operating in Full Self-Driving Beta mode drifted from its lane on Sunrise Highway and sideswiped plaintiff’s vehicle; Tesla FSD Beta was classified as a Level 2 system requiring continuous driver monitoring; the vehicle owner had engaged the system while not maintaining the required hands-on attention; dual liability theory: Tesla for design defect in the lane-keeping algorithm and failure to warn that FSD Beta was not suitable for the roadway type; vehicle owner for negligent use; OBD and telematics data confirmed FSD Beta engagement and absence of steering wheel torque from the driver for 47 seconds prior to the lane departure event
$430K
Uber AV Test Vehicle — Intersection Right-of-Way Failure
Uber Advanced Technologies Group test vehicle failed to yield to a vehicle with right-of-way at a suburban intersection during a supervised test deployment; plaintiff sustained lumbar disc herniation at L4-L5; both the fleet operator and the safety driver who failed to intervene were joined as defendants; respondeat superior against Uber for safety driver negligence; negligent hiring claim based on safety driver’s insufficient training documentation produced in discovery; software version logs confirmed the system had not been updated with a hotfix issued three weeks prior that addressed right-of-way decision logic
$295K
ADAS Camera Sensor Failure — Sun Glare Collision
Forward collision avoidance camera array failed to function in direct sunlight conditions on the Southern State Parkway; the plaintiff was rear-ended by a vehicle whose AEB system was disabled by sun glare into the forward-facing camera; products liability claim against the vehicle OEM for failure to warn that the AEB system had a known sun-glare limitation that could disable the safety system; NHTSA Technical Service Bulletin obtained through discovery confirmed the manufacturer had identified the sun-glare vulnerability and issued a software update that the vehicle owner had not installed; failure to warn theory based on inadequacy of the update notification process
Past results do not guarantee a similar outcome. Each case is unique.
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Reach us 24/7 at (516) 750-0595 or fill out our online form. We respond within minutes.
Evidence Preserved
We immediately issue litigation hold notices to the vehicle manufacturer, fleet operator, and owner demanding preservation of EDR data, telematics logs, OTA software update history, and all incident reports before critical data is overwritten or the vehicle is repaired.
Experts Retained
We retain automotive engineers, AI systems analysts, and accident reconstructionists to analyze the autonomous system’s decision sequence, identify the defect, and build the products liability claim with the expert foundation required to defeat manufacturer defenses.
We Fight. You Heal.
We take on the manufacturer’s and insurer’s litigation teams while you focus on recovery. We handle every discovery battle, expert disclosure, and trial proceeding. We don’t get paid until you do.
Why Tenenbaum Law for AV Accident Cases
Built to Take on Manufacturers in Complex Products Liability Litigation
Autonomous vehicle manufacturers deploy sophisticated legal teams and resist producing internal testing data, safety reports, and engineering communications at every step. Jason Tenenbaum has spent 24 years litigating complex products liability cases — mastering the discovery practice, expert witness strategy, and defect theory framework that turns vehicle data into verdicts.
EDR & Telematics Data Extraction
We work with automotive engineers who specialize in extracting and interpreting EDR, OBD, and manufacturer-proprietary telematics data. This data tells the story of exactly what the autonomous system was doing in the seconds before the collision — and it is the foundation of every AV defect case.
Multiple Defendant Strategy
AV accidents often have more than one negligent party. We build parallel theories against the manufacturer (products liability), the fleet operator (negligence and respondeat superior), and the human operator (negligent supervision) to maximize recovery and prevent any single defendant from shifting blame to others.
NHTSA Records & Prior Complaint Evidence
We leverage NHTSA complaint databases, Technical Service Bulletins, defect investigations, and recall records to establish that the manufacturer knew of the defect before your accident. This prior knowledge evidence is essential to both the design defect claim and, when appropriate, the punitive damages claim.
“The Tesla slammed on its brakes for no reason on the LIE and the car behind hit us at full speed. Jason’s team got Tesla’s data out of the car, found that Autopilot was engaged and there was nothing in the road, and connected it to hundreds of other complaints. The manufacturer had to answer for it. We got far more than we expected.”
David K.
Tesla Autopilot Phantom Braking — Long Island Expressway
Legal Analysis
Autonomous and Self-Driving Vehicle Accidents on Long Island
The deployment of autonomous driving systems on Long Island’s roads — from the Long Island Expressway and Northern State Parkway to suburban intersections in Nassau and Suffolk Counties — has created a new category of motor vehicle accident where the technology itself is the defendant. When a Tesla operating in Autopilot or Full Self-Driving (FSD) mode executes an erroneous braking, steering, or acceleration decision that causes a collision, the traditional car accident liability analysis is incomplete. The vehicle manufacturer, software developer, and fleet operator may all share liability for the AI system’s failure.
Autonomous driving systems are classified by the SAE International J3016 standard on a scale from Level 0 (no automation) to Level 5 (full automation). The most commercially prevalent systems on Long Island roads today are Level 2 systems — primarily Tesla’s Autopilot and Full Self-Driving Beta. Level 2 means the system simultaneously controls steering and acceleration/braking, but the human driver must remain fully engaged, with hands on the wheel and eyes on the road, ready to take over at any moment. Level 2 systems are not self-driving in any legal or common-sense meaning; they are driver assistance systems that transfer physical control of the vehicle to the computer while the human remains legally responsible. When a Level 2 system fails — through phantom braking, lane departure, or failure to detect a stationary object — liability is shared between the manufacturer (for the system defect) and the human operator (for inadequate supervision).
Advanced Driver Assistance Systems (ADAS) are distinct from full autonomy but present similar liability issues. ADAS features — including automatic emergency braking (AEB), forward collision warning, lane departure warning, lane-keeping assist, adaptive cruise control, and blind spot monitoring — are now standard on most new vehicles. When an AEB system fails to detect a pedestrian or a stationary obstacle and the vehicle strikes the hazard without braking, the vehicle manufacturer may be liable for the ADAS design defect. NHTSA has mandated AEB on all new passenger cars by 2029 and actively investigates AEB failure complaints. Sensor failures — including LiDAR sensor degradation, camera obstructions, and radar sensor misalignment — are documented defect categories in ADAS litigation. For the broader context of car accident claims on Long Island, see our car accident lawyer page.
The New York Department of Motor Vehicles governs autonomous vehicle testing and deployment on New York roads under 15 NYCRR Part 78, which requires AV operators to maintain a $5 million insurance or bond, report all accidents involving their AV systems, and adhere to specific safety standards. These regulatory requirements create a compliance record that is valuable in AV accident litigation: an operator’s failure to file required accident reports, maintain required insurance, or adhere to safety standards is evidence of negligence and may support punitive damages.
Tesla Autopilot and FSD Liability: Phantom Braking, Lane Departure, and Stationary Object Failures
Tesla’s Autopilot and Full Self-Driving systems have been the subject of more NHTSA investigations, consumer complaints, and civil litigation than any other autonomous driving technology. Understanding the specific failure modes and the regulatory and litigation history is essential to building a Tesla Autopilot products liability case.
Phantom braking is the most commonly reported Tesla Autopilot defect. The AI perception system incorrectly identifies a non-existent obstacle — a shadow, a road marking, an overpass, or electromagnetic interference — and executes emergency braking at highway speed without warning. Vehicles following the Tesla may be unable to stop, resulting in rear-end chain collisions. NHTSA opened Investigation PE22007 in August 2022 into Tesla Autopilot phantom braking after receiving over 750 complaints involving approximately 416,000 Tesla vehicles. Consumer complaint data submitted to NHTSA under 49 CFR Part 579 is publicly available and constitutes admissible evidence in products liability litigation of the manufacturer’s prior knowledge of the defect.
Failure to detect stationary objects is a documented design limitation of Tesla’s camera-based perception system. Unlike LiDAR-based systems that use laser pulse measurement, Tesla Autopilot relies primarily on camera inputs processed by a neural network. Camera-based systems have difficulty distinguishing stationary objects in the roadway — including stopped emergency vehicles, stalled cars, and debris — from background elements. NHTSA Investigation PE21020 examined 11 crashes where Tesla vehicles on Autopilot struck parked emergency vehicles with lights flashing; a 2022 recall addressed the emergency-vehicle detection failure. These prior crash investigations and the recall record are critical evidence in cases involving Tesla Autopilot collisions with stationary objects.
FSD Beta liability presents a distinct theory from standard Autopilot claims. Tesla marketed FSD Beta as a "Full Self-Driving" capability despite its classification as a Level 2 system that requires continuous driver supervision. The marketing of the system as "Full Self-Driving" — implying greater autonomy than the system actually provides — is the foundation of a failure-to-warn claim: if customers reasonably believed FSD Beta was a fully autonomous system that did not require driver monitoring, and Tesla’s marketing created or reinforced that belief, the resulting over-reliance on the system by drivers creates liability for both Tesla (failure to warn) and the vehicle owner (negligent entrustment of the FSD feature to an occupant who misunderstood its limitations).
Discovery in Tesla cases: Extracting and interpreting Tesla’s proprietary vehicle data requires specialized expertise. Tesla vehicles maintain detailed telematics records including GPS track, speed, Autopilot engagement status, driver monitoring alerts, steering wheel torque sensor readings, and sensor input logs. Tesla stores significant vehicle data remotely on its own servers. Litigation hold demands must be directed to both the vehicle owner and Tesla Inc. to preserve server-side telematics. Tesla has contested discovery of its internal engineering and testing documents in litigation, but New York courts have ordered production of relevant safety test data and internal defect reports under standard CPLR Article 31 discovery rules.
AV Accident Liability Framework: Multiple Defendants and Theories
The liability analysis in an autonomous vehicle accident case differs fundamentally from a conventional two-car collision because the responsible parties may include a corporation that manufactured a defective AI system rather than a negligent human driver. New York products liability law and tort law provide multiple parallel theories:
Design defect is the primary products liability theory in most AV accident cases. New York applies the risk-utility test: a product is defectively designed if the risks of the design outweigh its utility, considering the magnitude and probability of harm, the feasibility of alternative designs, and the manufacturer’s ability to reduce the risk. In AV cases, the design defect is typically in the AI decision-making algorithm, the sensor fusion system, or the system’s operational design domain (ODD) — the set of conditions under which the manufacturer claims the system operates safely. When an accident occurs within conditions the manufacturer represented as within the ODD, the design defect is that the system failed to perform as designed.
Manufacturing defect applies when a specific vehicle’s sensor hardware fails due to a deviation from the manufacturer’s intended design — a defective LiDAR unit, a misaligned radar sensor, or a malfunctioning camera. The manufacturing defect theory requires showing that the specific unit that caused the accident deviated from the manufacturer’s specifications, distinguishing it from vehicles that functioned as designed.
Failure to warn applies when the manufacturer marketed or described the autonomous system in a way that understated its limitations, or when the manufacturer failed to adequately communicate known defects, limitations, and operating restrictions to consumers. Tesla’s marketing of FSD Beta, Subaru’s EyeSight system warnings about performance degradation in rain and fog, and the adequacy of owner’s manual disclosures about ADAS limitations are all evaluated under the failure-to-warn theory.
Negligent entrustment applies when a fleet operator or vehicle owner allows a person or an AI system to operate a vehicle in circumstances where the operator knew or should have known the system was unfit for those conditions. A commercial delivery fleet that deploys vehicles with known ADAS defects in urban environments, or a Tesla owner who activates FSD Beta in conditions (highway exit ramps, construction zones) that Tesla’s own documentation identifies as unsupported by the system, may face negligent entrustment liability.
Strict liability applies to manufacturers of defective products in New York under the rule articulated in Codling v. Paglia, 32 N.Y.2d 330 (1973): a manufacturer that places a defective product in the stream of commerce is strictly liable for injuries caused by the defect regardless of whether the manufacturer was negligent. This means that in a design defect case, the plaintiff need not prove that the manufacturer was careless — only that the product was defectively designed and the defect caused the injury.
Key Point: NY Serious Injury Threshold Applies; Products Liability SOL Is 3 Years
Insurance Law §5102(d)’s serious injury threshold applies to all motor vehicle accident claims in New York, including AV accident claims. The products liability claim against the manufacturer is subject to CPLR §214’s 3-year statute of limitations from the date of injury; for latent defects, CPLR §214-c may extend the period to 3 years from discovery. The negligence claim against the human operator is also subject to CPLR §214’s 3-year period. Punitive damages are available against a manufacturer who knew of a defect and continued deployment in conscious disregard of the risk — a theory supported by NHTSA complaint records and internal manufacturer safety reports. For the complete framework of car accident claims in New York, see our car accident lawyer page.
Autonomous Vehicle Accident Questions
Who can be sued after a Tesla Autopilot or self-driving car accident in New York?
Autonomous vehicle accidents on Long Island can involve multiple defendants across several legal theories. The vehicle manufacturer (Tesla, GM, Ford, or another OEM) may be liable under products liability for a design defect in the autonomous driving system, a manufacturing defect in the sensor hardware, or a failure to warn about the system’s limitations. The software developer — which may be the OEM or a third-party AI company — may be independently liable for the defective algorithm that made the erroneous driving decision. A fleet operator (such as Waymo, Uber AV, or a commercial delivery fleet) may be liable under respondeat superior for the actions of a safety driver or under direct negligence for inadequate vehicle maintenance, insufficient training, or deploying vehicles with known software defects in unsuitable environments. The human operator of the vehicle — if a Level 2 system like Tesla Autopilot or FSD Beta was engaged — may be liable for inattentive supervision of the system, as these systems legally require continuous driver monitoring and override capability. New York CPLR Article 14 allows a plaintiff to sue all potentially liable defendants in a single action and recover from each in proportion to their fault. In practice, autonomous vehicle cases often involve aggressive defense strategies from manufacturers’ litigation teams; retaining an attorney with experience extracting EDR and telematics data is essential to establishing which defendant’s conduct caused the accident.
What is the difference between a Level 2 and a Level 4 autonomous vehicle for liability purposes?
The SAE International autonomy classification system (SAE J3016) defines six levels of driving automation from Level 0 (no automation) to Level 5 (full automation with no human operator required). The level of automation has significant implications for how liability is allocated after an accident. Level 2 systems — such as Tesla Autopilot and Full Self-Driving (FSD) Beta — are "partial automation" systems that control both steering and acceleration/braking simultaneously, but legally require the human driver to remain engaged, monitor the roadway at all times, and be ready to assume control immediately. When a Level 2 system fails, the vehicle manufacturer and the inattentive human operator may both share liability. Tesla’s Autopilot and FSD Beta have been the subject of multiple NHTSA investigations, including a 2021-2023 investigation into phantom braking (sudden unwarranted deceleration) and a 2022 recall of over 360,000 FSD Beta vehicles for traffic control law violations. Level 4 systems — such as Waymo’s fully driverless robotaxi in defined geofenced service areas — operate without any human monitoring requirement within their operational design domain (ODD). When a Level 4 system fails, the manufacturer and fleet operator bear full liability because there is no human driver whose inattention contributed to the accident. New York’s Department of Motor Vehicles AV regulations, found at 15 NYCRR Part 78, require AV operators to maintain safety standards and accept liability for accidents caused by their systems. This regulatory framework supports strict products liability claims against AV manufacturers and fleet operators for accidents caused by autonomous system failures.
What evidence is critical in an autonomous vehicle accident case?
Autonomous vehicle accident cases require specialized evidence that does not exist in conventional car accident litigation. The event data recorder (EDR) — the "black box" in the vehicle — records pre-crash data including vehicle speed, braking inputs, steering inputs, and whether a driver-assistance system was engaged. In Tesla vehicles, the EDR and the vehicle’s telematics system record data far more granularly than conventional EDR devices, including whether Autopilot or FSD was active, driver hand-torque on the steering wheel, and the AI system’s decision outputs in the seconds before a collision. This data must be preserved immediately through a litigation hold letter and a demand to the manufacturer to preserve all telematics, OTA update logs, and incident data before it is overwritten. OBD (on-board diagnostics) data provides additional vehicle condition information. The vehicle’s software version at the time of the accident is critical: if the manufacturer had issued an over-the-air (OTA) software update that addressed a known defect prior to the accident, and the update had not been installed, the failure-to-warn and negligent maintenance claims are strengthened. Internal manufacturer testing data, obtained through discovery, is often the most powerful evidence in AV defect cases: validation test failure rates, known defect reports, consumer complaint logs submitted to NHTSA, and internal engineering communications about the system’s limitations. New York courts apply standard products liability discovery rules under CPLR Article 31 to AV cases, and plaintiffs’ attorneys have successfully compelled manufacturers to produce software testing records and internal safety reports.
Does the New York serious injury threshold (Insurance Law §5102(d)) apply to autonomous vehicle accident claims?
Yes. New York Insurance Law §5102(d) applies to all motor vehicle accidents on New York roads regardless of whether the vehicle was operated by a human driver or an autonomous system. A plaintiff injured by a self-driving car in New York must satisfy the serious injury threshold to recover non-economic damages — pain and suffering — from any at-fault party, including the vehicle manufacturer in a products liability claim. The threshold categories are the same: fracture, permanent consequential limitation, significant limitation, 90/180-day category, and others. The products liability claim against the manufacturer is in addition to, not instead of, the threshold analysis. However, autonomous vehicle accidents often involve more severe collisions — because the AI system may have failed to brake, failed to avoid a stationary object, or made a high-speed lane change error — producing injuries serious enough to clearly satisfy the threshold. The statute of limitations for a products liability claim based on a latent design defect is governed by CPLR §214-c (three years from discovery of the defect or injury), while the general negligence claim against the human operator or fleet company is subject to CPLR §214’s three-year statute from the date of accident. Punitive damages — which are not available in a straightforward car accident negligence case — may be available against the vehicle manufacturer if the plaintiff can prove that the manufacturer knew of the defect, knew it created a substantial risk of harm to the public, and continued to market and sell the vehicle despite that knowledge. NHTSA’s complaint database and internal manufacturer communications obtained in discovery can support this punitive damages theory.
What is "phantom braking" and how does it support a products liability claim against Tesla?
Phantom braking — also called "false braking" or "unintended deceleration" — is a defect in Tesla’s Autopilot and Full Self-Driving systems where the vehicle suddenly and without warning decelerates sharply while operating in autonomous mode, even though there is no actual obstacle or hazard in the roadway ahead. The AI perception system incorrectly identifies a non-existent obstacle — often a shadow, a road marking, an overpass, or sensor noise — as a real threat, and executes emergency braking. Vehicles following the Tesla at highway speed may be unable to stop in time, resulting in rear-end collisions. NHTSA opened a formal investigation into Tesla Autopilot phantom braking in August 2022 (Investigation PE22007) after receiving over 750 complaints of sudden unintended braking involving approximately 416,000 Tesla vehicles with FSD software versions 10.3 through 10.8. Consumer complaint data submitted to NHTSA under 49 CFR Part 579 constitutes admissible evidence of a known defect, and the manufacturer’s failure to recall or remediate the defect despite thousands of reported incidents supports a design defect claim under the risk-utility test applied in New York: if the risks posed by the phantom braking defect outweigh the utility of the Autopilot system as designed, the design is defective. The plaintiff’s products liability expert — typically a mechanical engineer or AI systems engineer with automotive sensor experience — analyzes the Tesla’s EDR and telematics data to confirm phantom braking caused the subject accident, compares the incident to the documented complaint history, and opines that a feasible alternative design — such as improved sensor fusion algorithms, higher braking confidence thresholds, or more rigorous real-world testing before deployment — would have prevented the accident.
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Jason Tenenbaum, Esq.
Jason Tenenbaum is a personal injury attorney serving Long Island, Nassau & Suffolk Counties, and New York City. Admitted to practice in NY, NJ, FL, TX, GA, MI, and Federal courts, Jason is one of the few attorneys who writes his own appeals and tries his own cases. Since 2002, he has authored over 2,353 articles on no-fault insurance law, personal injury, and employment law — a resource other attorneys rely on to stay current on New York appellate decisions.
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Autonomous vehicle accident cases are time-sensitive: vehicle data is overwritten and litigation holds must be issued immediately. Call now for a free consultation — we handle AV cases on contingency.