Published Date: 2022-02-08
| Postmortem Analysis | |
|---|---|
| Timeline | 1. The software failure incident with the driverless Tesla crashing into a private jet while being 'summoned' across a Washington airfield happened in April 2022 as per the article published on April 22, 2022 [Article 126583]. |
| System | 1. Full Self-Driving software system in Tesla vehicles [124031, 124041, 126583] |
| Responsible Organization | 1. The Full Self-Driving software developed by Tesla was responsible for causing the software failure incidents reported in the articles [124031, 124041]. 2. The Smart Summon feature of Tesla's self-driving models was also responsible for causing a software failure incident [126583]. |
| Impacted Organization | 1. Tesla owners [124031, 124041] 2. Pedestrians [124031] 3. Other vehicles on the road [124031] 4. Cirrus Vision private jet [126583] |
| Software Causes | 1. The Full Self-Driving software in Tesla vehicles failed to detect and cope with relevant features of its Operational Design Domain, such as road obstacles and pedestrians, leading to near-misses and accidents [124031]. 2. The Full Self-Driving software in Tesla vehicles veered the Model 3 into a bike lane barrier post, ran a red light, attempted to go down a railroad track and a tram lane, and showed deficiencies in detecting road obstacles, highlighting software flaws [124041]. 3. The Smart Summon feature in Tesla vehicles allowed a driverless Tesla to crash into a private jet while being summoned across a Washington airfield, indicating a software failure in the Smart Summon mode [126583]. |
| Non-software Causes | 1. The physical location of the ultrasonic sensors on the Tesla Model 3 may have contributed to the failure incident by potentially missing small, sporadic objects like bollards [124031]. 2. The limitations of cameras in detecting pedestrian intent due to their inability to measure the distance of distant objects and being blinded by glares from headlights or the sun may have played a role in the failure incident [124031]. 3. The driver's actions, such as letting the wheel rotate too far to the right before noticing the obstacle and attempting to turn quickly to the left, may have also contributed to the failure incident [124041]. |
| Impacts | 1. The software failure incident involving Tesla's Full Self-Driving software led to near-misses and accidents, including collisions with bike lane bollards and failure to stop for pedestrians, highlighting the software's inability to detect common road obstacles and pedestrians [124031, 124041]. 2. The incident raised concerns about the software's incomplete state and its failure to meet basic safety requirements, as noted by autonomous-driving experts who viewed the videos [124031]. 3. The software failure incidents resulted in Tesla having to recall nearly 54,000 vehicles equipped with the Full Self-Driving software due to issues such as running through stop signs and other safety concerns [124031]. 4. The incidents added to the series of recalls by Tesla, including recalls related to seat belt reminder chimes, windshield defrosting, and issues with vehicles not stopping at junctions, indicating a pattern of software-related issues [124031]. 5. The software failure incidents contributed to increased scrutiny from the National Highway Traffic Safety Administration (NHTSA) over Tesla's vehicles and software, with investigations into crashes caused by the Full Self-Driving software and Autopilot system [124031]. 6. The incidents highlighted the challenges and risks associated with Tesla's autonomous driving features, including the need for drivers to be ready to intervene at all times despite the software's level 2 autonomy capabilities [124031, 124041]. 7. The software failure incidents showcased the limitations of relying solely on cameras for autonomous driving, as cameras may not accurately detect certain objects or measure distances, leading to potential safety hazards [124031]. 8. The incidents underscored the ongoing efforts by Tesla to improve its self-driving software, with the company releasing new software updates to address reported faults and enhance the performance of the Full Self-Driving Beta program [124041]. |
| Preventions | 1. Improved mapping and perception capabilities: The software failure incident involving a Tesla Model 3 crashing into a bike lane bollard could have been prevented by enhancing the mapping and perception capabilities of the Full Self-Driving system. Permanent obstacles like bollards should be accurately mapped to ensure the vehicle recognizes and avoids them [124031, 124031]. 2. Training on unusual road obstacles: To prevent incidents like the failure to detect a pedestrian in a crosswalk, the software should be trained on recognizing and reacting to unusual road obstacles, such as pedestrian walk signs and pedestrians stepping off sidewalks [124031]. 3. Integration of lidar technology: Incorporating light detection and ranging (lidar) technology into the software could improve the detection of distant objects, prevent glare interference, and enhance overall object recognition capabilities, especially in scenarios involving pedestrians [124031]. 4. Continuous monitoring and intervention by drivers: Despite the autonomous capabilities of the Full Self-Driving system, drivers must remain vigilant, ready to intervene, and actively monitor the vehicle and its surroundings at all times to prevent accidents and ensure safety [126583]. |
| Fixes | 1. Improving the mapping and perception capabilities of the Full Self-Driving software to ensure that permanent obstacles like bollards are accurately detected and accounted for on the map. This could prevent incidents like the Tesla Model 3 crashing into a bike lane bollard due to incomplete mapping and perception [124031, 124031]. 2. Enhancing the computer vision training of the software to recognize and respond to unusual road obstacles, such as uniquely shaped and colored bollards, to avoid missing them until it's too late. This would address issues with the software's perception capabilities and improve its ability to detect and react to various objects on the road [124031]. 3. Implementing lidar technology in addition to cameras to improve the detection of distant objects and prevent issues like failing to measure the distance of objects or being blinded by glares. This would enhance the software's ability to detect pedestrian intent and improve overall safety on the road [124031]. 4. Conducting thorough testing and validation of software updates before wide rollouts to ensure that reported faults are addressed and improvements are made to prevent incidents like running red lights or attempting to drive down railroad tracks due to software glitches. This would help in refining the Full Self-Driving software and enhancing its performance [124041, 126583]. |
| References | 1. Experts in autonomous driving technologies, including Nicola Croce, Brad Templeton, Andrew Maynard, and Hod Finkelstein [124031] 2. Tesla CEO Elon Musk [124031, 124041, 126583] 3. YouTubers AI Addict and Dirty Tesla [124031, 124041] 4. Technical program manager at Deepen AI [124031] 5. Chief research and development officer for AEye [124031] 6. US National Highway Traffic Safety Administration (NHTSA) [124031, 124041, 126583] 7. Reddit post [126583] |
| Category | Option | Rationale |
|---|---|---|
| Recurring | one_organization, multiple_organization | (a) The software failure incident has happened again at Tesla. In a recent incident, a Tesla Model 3 in 'Full Self-Driving' mode collided with a bike lane barrier post, showcasing a potential setback for Tesla's self-driving technology [Article 124041]. This incident adds to previous reports of Tesla vehicles experiencing issues with their Full Self-Driving software, including running red lights and failing to detect road obstacles [Article 124031]. (b) The software failure incident has also occurred at other organizations or with their products and services. For example, a driverless Tesla was filmed crashing into a private jet while being 'summoned' across a Washington airfield, highlighting another instance of a Tesla vehicle experiencing a software-related mishap [Article 126583]. This incident, along with the previous incidents involving Tesla vehicles, indicates a broader trend of software failures in the autonomous driving sector. |
| Phase (Design/Operation) | design, operation | (a) The software failure incident related to the design phase is evident in the Tesla Full Self-Driving software incidents reported in the articles. The incidents include the software failing to detect common road obstacles and pedestrians, such as a bike lane bollard, light-rail tracks, and a pedestrian in a crosswalk [124031, 124041]. Experts highlighted that the software's failure to detect these obstacles and respond appropriately was a result of inherent weaknesses in the software design, such as incomplete mapping, perception issues, and lack of training on certain objects like bollards. These design flaws led to the system not meeting basic safety requirements it was designed to adhere to, showcasing a failure in the design phase of the software development. (b) The software failure incident related to the operation phase is demonstrated in the Tesla Full Self-Driving software incidents where the system allowed the vehicle to run through stop signs, ignore oncoming traffic, and make incorrect lane changes [124031, 124041]. These operational failures were due to the software's inability to properly interpret and respond to real-time road conditions and signals, leading to dangerous situations. Users were seen struggling to intervene and control the vehicle to prevent accidents, indicating failures in the operation phase of the software usage. Tesla's warnings to users to remain responsible for monitoring the car and its surroundings at all times also point to operational challenges in using the Full Self-Driving system. |
| Boundary (Internal/External) | within_system | (a) The software failure incident related to the Tesla Full Self-Driving software crashing into a bike lane bollard and failing to stop for a pedestrian in a crosswalk ([124031], [124041]) can be categorized as within_system. The incidents were attributed to flaws within the software itself, such as the system's failure to detect common road obstacles like bollards and pedestrians, as well as issues with perception and computer vision leading to missed objects and misinterpretations of road signs and pedestrian intent. Experts pointed out weaknesses in the software's ability to detect and cope with relevant features within its Operational Design Domain, indicating internal shortcomings in the software's design and functionality. Additionally, the incidents highlighted the incomplete nature of the Full Self-Driving software, which was still in a beta stage and not fully polished or tested for mass market readiness. |
| Nature (Human/Non-human) | non-human_actions | (a) The software failure incident occurring due to non-human actions: - In Article 124031, it is reported that a Tesla Model 3 with Full Self-Driving software collided with a bike lane bollard and attempted to drive down light-rail tracks, mistaking them for a road, showcasing flaws in the software's ability to detect common road obstacles and pedestrians [124031]. - Another incident in Article 124041 describes a Tesla Model 3 in Full Self-Driving mode colliding with a bike lane barrier post and running a red light, indicating issues with the self-driving software's ability to navigate and avoid obstacles [124041]. - Additionally, in Article 126583, a driverless Tesla collided with a private jet while being 'summoned' across an airfield, demonstrating a failure in the Smart Summon feature where the car continued in motion after the collision [126583]. (b) The software failure incident occurring due to human actions: - The articles do not specifically mention any software failure incidents caused by human actions. |
| Dimension (Hardware/Software) | hardware, software | (a) The software failure incident occurring due to hardware: - In the incident where a driverless Tesla crashed into a private jet while being 'summoned' across a Washington airfield, the incident was related to the car being in 'Smart Summon' mode, where owners can control their cars' movements via smartphones. The Tesla continued in motion after hitting the jet until unidentified individuals intervened, indicating a hardware-related failure in the car's physical movement [Article 126583]. (b) The software failure incident occurring due to software: - The incidents involving Tesla's Full Self-Driving software, where users posted videos showing near-misses and accidents, highlight failures in the software's ability to detect road obstacles, pedestrians, and other common features. Experts pointed out flaws in the software's perception and mapping capabilities, as well as its inability to recognize and respond to certain objects and scenarios, indicating software-related failures [Article 124031, Article 124041]. |
| Objective (Malicious/Non-malicious) | non-malicious | (a) The articles do not provide information about a malicious software failure incident where the failure was due to contributing factors introduced by humans with the intent to harm the system. (b) The software failure incidents reported in the articles are non-malicious. They involve failures in Tesla's Full Self-Driving software, such as collisions with obstacles like bike lane bollards, failure to stop for pedestrians, attempting to drive down light-rail tracks, and running red lights. These incidents are attributed to flaws in the software, incomplete mapping, issues with perception, and limitations in the detection capabilities of the system [124031, 124041, 126583]. |
| Intent (Poor/Accidental Decisions) | poor_decisions, accidental_decisions | (a) poor_decisions: The intent of the software failure incident can be attributed to poor decisions made in the development and implementation of the Full Self-Driving (FSD) software by Tesla. The incidents reported in the articles highlight how the FSD software made poor decisions leading to accidents and near-misses. For example, the software failed to detect common road obstacles, mistook light-rail tracks for roads, ignored fast oncoming trucks, and did not stop for pedestrians in crosswalks. These poor decisions by the software contributed to the incidents and raised concerns about the software's readiness for mass market deployment [124031, 124041]. (b) accidental_decisions: The software failure incidents can also be attributed to accidental decisions or unintended consequences of the FSD software. For instance, in one incident, a Tesla Model 3 in Full Self-Driving mode collided with a bike lane barrier post, despite the driver hitting the brakes and trying to steer away from the obstacle. The incident was captured during a drive in downtown San Jose, California, and provided evidence that the FSD software was directly responsible for the accident. This unintended consequence of the software's behavior led to the collision with the bollard [124041, 126583]. |
| Capability (Incompetence/Accidental) | development_incompetence | (a) The software failure incident occurring due to development incompetence: - The incident involving a Tesla Model 3 crashing into a bike lane bollard and other near-misses was attributed to flaws in the Full Self-Driving software, highlighting the software's failure to detect common road obstacles and pedestrians. Experts pointed out that the software did not meet basic safety requirements it was designed to adhere to, indicating an inherent weakness in the software [124031]. - The same incident was mentioned in another article, emphasizing that the Full Self-Driving software was directly responsible for the accident, showcasing deficiencies in the software that needed improvement before a wide rollout [124041]. (b) The software failure incident occurring accidentally: - The incident where a driverless Tesla collided with a private jet while being 'summoned' across a Washington airfield was described as the car going haywire and causing chaos. The Tesla was in 'Smart Summon' mode, allowing owners to manipulate their cars' movements via smartphones. The incident was not intentional and resulted in no injuries [126583]. |
| Duration | temporary | (a) In the reported software failure incidents related to Tesla's Full Self-Driving software, the duration of the software failure incident appears to be temporary. The incidents mentioned in the articles highlight specific scenarios where the Full Self-Driving software failed to detect road obstacles, pedestrians, or make correct driving decisions, leading to accidents or near-misses [124031, 124041, 126583]. These failures were attributed to factors such as incomplete software, lack of proper mapping, issues with perception, and limitations of camera-based detection systems. The incidents occurred under certain circumstances, indicating that the software's failure was not permanent but rather due to specific contributing factors in those situations. |
| Behaviour | crash, omission, timing, value, other | (a) crash: The software failure incident described in the articles involves crashes where the Tesla vehicles in Full Self-Driving mode collided with obstacles such as bike lane bollards and a private jet. The incidents resulted in physical collisions, indicating a failure of the system to avoid obstacles and maintain safe driving conditions [124031, 124041, 126583]. (b) omission: The software failure incident also involved instances where the Full Self-Driving software omitted to perform its intended functions. For example, the system failed to stop for a pedestrian in a crosswalk, did not recognize road obstacles like bollards, and ran a red light, showcasing instances where the system omitted crucial actions it should have taken [124031, 124041]. (c) timing: There are indications of timing-related failures in the software incidents. For instance, the system attempted to drive down light-rail tracks and mistook them for a road, indicating a timing issue where the system performed its functions at the wrong time or in the wrong context [124031]. (d) value: The software failure incidents also involved failures related to the system performing its intended functions incorrectly. For example, the Full Self-Driving software allowed vehicles to run through stop signs at low speeds without coming to a complete halt, indicating an incorrect performance of the system's functions [124031, 124041]. (e) byzantine: The articles do not provide specific information indicating a byzantine behavior of the software failure incidents. (f) other: The other behavior observed in the software failure incidents includes the system attempting to go down a railroad track and a tram lane, which are not intended paths for vehicles, showcasing a behavior that is not explicitly covered by the crash, omission, timing, or value categories [124041]. |
| Layer | Option | Rationale |
|---|---|---|
| Perception | sensor, processing_unit, embedded_software | (a) sensor: Failure due to contributing factors introduced by sensor error: - The incident involving a Tesla Model 3 crashing into a bike lane bollard in San Jose was attributed to a sensor-related issue. The location of the ultrasonic sensors used for Full Self-Driving on the vehicle, particularly in the front bumper, was mentioned as a factor contributing to the oversight of small, sporadic objects like bollards [124031]. - In another incident, a Tesla Model 3 in Full Self-Driving mode collided with a bike lane barrier post in downtown San Jose. The video highlighted deficiencies in the car's ability to detect road obstacles, specifically the green bike lane barrier posts, indicating a sensor-related problem [124041]. (b) actuator: Failure due to contributing factors introduced by actuator error: - There was no specific mention of failures related to actuators in the provided articles. (c) processing_unit: Failure due to contributing factors introduced by processing error: - The incidents with Tesla's Full Self-Driving software, such as running a red light, attempting to drive down a railroad track, and ignoring an oncoming truck, suggest processing errors within the software [124041]. (d) network_communication: Failure due to contributing factors introduced by network communication error: - There was no specific mention of failures related to network communication in the provided articles. (e) embedded_software: Failure due to contributing factors introduced by embedded software error: - The incidents involving Tesla's Full Self-Driving software, where the system failed to detect common road obstacles and pedestrians, point to errors in the embedded software used for autonomous driving [124031, 124041]. |
| Communication | unknown | The software failure incidents reported in the articles do not specifically mention failures related to the communication layer of the cyber physical system. The incidents primarily focus on the Full Self-Driving software of Tesla vehicles encountering issues with detecting road obstacles, pedestrians, and making incorrect driving decisions, rather than failures related to the physical or network layers of communication within the system. Therefore, the articles do not provide information on failures at the link_level or connectivity_level. |
| Application | TRUE | The software failure incidents reported in the provided articles are related to the application layer of the cyber physical system. The incidents involve failures due to contributing factors introduced by bugs, operating system errors, unhandled exceptions, and incorrect usage. In Article 124031, it is mentioned that the Tesla Full Self-Driving software, which is still in beta testing, was involved in multiple incidents where it failed to detect common road obstacles and pedestrians, leading to near-misses and collisions. The incidents included the software mistakenly driving into a bike lane bollard, attempting to drive down light-rail tracks, and failing to stop for a pedestrian in a crosswalk. Experts highlighted the flaws in the software's ability to detect and cope with relevant features of its Operational Design Domain, indicating issues at the application layer [124031]. Similarly, in Article 124041, a Tesla Model 3 in Full Self-Driving mode collided with a bike lane barrier post in downtown San Jose. The incident was directly attributed to the Full Self-Driving software, which veered the vehicle into the bollard despite the driver's attempts to avoid it. The article also mentions other deficiencies in the Full Self-Driving software, such as running a red light and attempting to navigate down a railroad track and tram lane, indicating issues at the application layer of the software [124041]. Therefore, based on the information from the articles, it can be concluded that the software failures in the incidents were related to the application layer of the cyber physical system, involving bugs, errors, and incorrect usage of the Full Self-Driving software. |
| Category | Option | Rationale |
|---|---|---|
| Consequence | harm, property, non-human, theoretical_consequence | (a) death: There were no reports of people losing their lives due to the software failure incidents described in the articles [124031, 124041, 126583]. (b) harm: The software failure incidents resulted in physical harm to individuals. For example, in one incident, a Tesla Model 3 in 'Full Self-Driving' mode collided with a bike lane barrier post, causing damage to the vehicle and potentially endangering the occupants [124041]. (c) basic: There were no reports of people's access to food or shelter being impacted due to the software failure incidents described in the articles [124031, 124041, 126583]. (d) property: The software failure incidents led to property damage. For instance, a driverless Tesla collided with a private jet, causing damage to the aircraft [126583]. (e) delay: The software failure incidents did not result in people having to postpone an activity due to the failures [124031, 124041, 126583]. (f) non-human: Non-human entities were impacted by the software failure incidents. For example, a driverless Tesla collided with a private jet [126583]. (g) no_consequence: The software failure incidents had observable consequences, such as physical harm and property damage, and were not without consequences [124031, 124041, 126583]. (h) theoretical_consequence: There were discussions about potential consequences of the software failures, such as accidents and safety risks, but these did occur in reality [124031, 124041]. (i) other: There were no other specific consequences of the software failure incidents mentioned in the articles [124031, 124041, 126583]. |
| Domain | information, transportation, health, other | (a) The failed system in the articles was intended to support the production and distribution of information. The software failure incident involved Tesla's Full Self-Driving software, which is designed to enable autonomous driving capabilities in Tesla vehicles. The incident highlighted various flaws and failures of the Full Self-Driving system, such as not being able to detect common road obstacles and pedestrians, leading to near-misses and accidents [124031, 124041]. (j) The software failure incident also had implications for the health industry. The incident involved a Tesla Model Y in Full Self-Driving mode causing a crash in Brea, California, which raised concerns about the safety and reliability of Tesla's autonomous driving technology. The incident resulted in the vehicle forcing itself into the incorrect lane and being hit by another vehicle, highlighting potential risks to road safety and public health [124041]. (m) The software failure incident can also be associated with the "other" category. In one of the incidents, a driverless Tesla was filmed crashing into a private jet while being 'summoned' across a Washington airfield. This incident showcased the challenges and risks associated with Tesla's self-driving technology, indicating potential safety concerns and the need for improved system reliability [126583]. |
Article ID: 124031
Article ID: 124041
Article ID: 126583