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NTSB: driver errors, overreliance on automation, lack of safeguards, led to fatal Tesla crash

The National Transportation Safety Board has determined that a truck driver’s failure to yield the right of way and a Tesla driver’s inattention due to overreliance on vehicle automation are the probable cause of the fatal 7 May 2016, crash near Williston, Florida. (Earlier post.)

The NTSB also determined the operational design of the Tesla’s vehicle automation permitted the car driver’s overreliance on the automation, noting its design allowed prolonged disengagement from the driving task and enabled the driver to use it in ways inconsistent with manufacturer guidance and warnings. As a result of its investigation the NTSB issued seven new safety recommendations and reiterated two previously issued safety recommendations.

While automation in highway transportation has the potential to save tens of thousands of lives, until that potential is fully realized, people still need to safely drive their vehicles. Smart people around the world are hard at work to automate driving, but systems available to consumers today, like Tesla’s ‘Autopilot’ system, are designed to assist drivers with specific tasks in limited environments. These systems require the driver to pay attention all the time and to be able to take over immediately when something goes wrong. System safeguards, that should have prevented the Tesla’s driver from using the car’s automation system on certain roadways, were lacking and the combined effects of human error and the lack of sufficient system safeguards resulted in a fatal collision that should not have happened.

Findings in the NTSB’s report include:

  1. No investigative evidence indicates that either driver was fatigued, that cell phone use distracted the truck driver, that the car driver was impaired by alcohol or other drugs, that any mechanical system on either vehicle failed, or that the highway design was inappropriate; consequently, these were not factors in the crash.

  2. There was sufficient sight distance to afford time for either the truck driver or the car driver to have acted to prevent the crash.

  3. The Tesla’s automated vehicle control system was not designed to, and did not, identify the truck crossing the car’s path or recognize the impending crash; consequently, the Autopilot system did not reduce the car’s velocity, the forward collision warning system did not provide an alert, and the automatic emergency braking did not activate.

  4. Although the results of postcrash drug testing established that the truck driver had used marijuana before the crash, his level of impairment, if any, at the time of the crash could not be determined from the available evidence.

  5. If automated vehicle control systems do not automatically restrict their own operation to those conditions for which they were designed and are appropriate, the risk of driver misuse remains.

  6. Because driving is an inherently visual task and a driver may touch the steering wheel without visually assessing the roadway, traffic conditions, or vehicle control system performance, monitoring steering wheel torque provides a poor surrogate means of determining the automated vehicle driver’s degree of engagement with the driving task.

  7. The Tesla driver’s pattern of use of the Autopilot system indicates an overreliance on the automation and a lack of understanding of system limitations.

  8. The Tesla driver was not attentive to the driving task, but investigators could not determine from the available evidence the reason for his inattention.

  9. The way that the Tesla Autopilot system monitored and responded to the driver’s interaction with the steering wheel was not an effective method of ensuring driver engagement.

  10. Without the manufacturer’s involvement, vehicle performance data associated with highly automated systems on vehicles involved in crashes cannot be independently analyzed or verified.

  11. A standardized set of retrievable data is needed to enable independent assessment of automated vehicle safety and to foster automation system improvements.

  12. To determine the safety effects from the use of automated vehicle control systems and to analyze the benefit-cost outcomes of these systems, reliable information is needed on the types of systems deployed and the numbers of miles driven using them.

  13. Connected vehicle technology will be most effective when all vehicles traveling on our roadways are equipped with the technology, and that is particularly important with respect to large, heavy trucks that pose the highest risk of injury to occupants of other vehicles.

The NTSB issued a total of seven safety recommendations based upon its findings, with one recommendation issued to the US Department of Transportation, three to the National Highway Traffic Safety Administration, two to the manufacturers of vehicles equipped with Level 2 vehicle automation systems, and one each to the Alliance of Automobile Manufacturers and Global Automakers.

The safety recommendations address the need for: event data to be captured and available in standard formats on new vehicles equipped with automated vehicle control systems; manufacturers to incorporate system safeguards to limit the use of automated control systems to conditions for which they are designed and for there to be a method to verify those safeguards; development of applications to more effectively sense a driver’s level of engagement and alert when engagement is lacking; and it called for manufacturers to report incidents, crashes, and exposure numbers involving vehicles equipped with automated vehicle control systems.

The board reiterated two safety recommendations issued to the National Highway Traffic Safety Administration in 2013, dealing with minimum performance standards for connected vehicle technology for all highway vehicles and the need to require installation of the technology, once developed, on all newly manufactured highway vehicles.

The abstract of the NTSB’s final report, that includes the findings, probable cause and safety recommendations is available online. The final report will be publicly released in the next several days.


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