Airplane’s famed “black box” – the electronic recording device that captures flight data to facilitate investigations into aviation incidents – has an automotive counterpart that is emerging as a product liability “hot spot” as vehicles become less reliant on drivers and more dependent on automated technologies.
An event data recorder (EDR), also known as a sensing diagnostic module (SDM) or a crash data retrieval system (CDR), can be installed in cars and trucks to record vehicle speed, airbag deployment, passive restraint/seat belt use, and other safety information that may be relevant to vehicular crashes or accidents. With the advent of driverless or autonomous cars in the US market, the importance of EDRs has expanded dramatically. The data that these “black boxes” can provide will become increasingly critical in understanding how people and property are injured in car crashes. As a result, EDRs will play a significant role in product liability cases involving autonomous automobiles.
EDRs in autonomous vehicles – what is it and what can we expect?
Autonomous vehicles (AVs) have the potential to change the transportation landscape through increases in safety, fuel and traffic efficiency, as well as through attendant passenger productivity. They can also seriously alter the legal landscape for automobile manufacturers.
Today, drivers and environmental factors are more likely to be blamed for car crashes than vehicle manufacturers (or suppliers to those manufacturers). However, with the advent of autonomous and semi-autonomous vehicles – and the correspondingly reduced role of drivers – the natural questioning of causes and the search for explanations of accidents will inevitably move beyond the human to encompass the machine. Consequently, manufacturers have the continued incentive, as they always have when going to market, to demonstrate the safety of their product. Enhanced EDRs can be a way to literally prove their point.
Although car manufacturers had not previously been required to include EDRs in vehicle design, they increasingly included them as a way to improve the safety of their vehicles. Now, more than 90 per cent of cars utilise some form of EDR, and recent National Highway Traffic Safety Administration (NHTSA) regulations are accelerating – even forcing – that trend by requiring EDR in new cars and setting mandatory standards for the type of data EDRs must capture.
EDRs were originally installed in vehicles in the 1990s to analyse airbag activation – recording when and whether airbags deployed. Over time, as with airplanes, EDRs have been used as just one of many data points in accident reconstruction. Unlike the black box of an airplane, EDR does not save all data regarding a car’s movements. Instead, it typically records data in a continuous loop in temporary memory, writing over the data every five or more seconds until an airbag-deployment event occurs. At that point, data from a certain period (typically seconds) before the crash are recorded into permanent memory, which can be retrieved and analysed. The recorded data has traditionally contained basic information related to airbag deployment, such as car speed, seatbelt usage, status of the car brakes, RPMs and time between crash impact and airbag deployment. More recently, the NHTSA created standards for EDR data, requiring 15 data points and certain accuracy ranges for each.
The advent of differing levels of automation in vehicles, from automatic braking systems to fully automated cars, will cause EDR technology to grow broader in scope and figure more prominently in product liability cases. Automation will create more data points and information regarding not only the car itself, but also about its surroundings and driver (eg, the distance from and movements of other vehicles or pedestrians, the actions of the driver, whether the car was in automated mode, etc).
One way AV manufacturers will likely be able to avoid liability is by using EDRs to show that the car operated properly. To avoid potential liability, manufacturers will likely programme EDRs to record an increasing amount of this data – beyond the airbag deployment information collected today – in an effort to absolve car automation technology when accidents arise. In fact, Tesla has already used its data to counter claims from a driver that one of its vehicles crashed into a building after suddenly accelerating on its own. (For more on this see Tom Simonite, “Tesla Knows When a Crash is Your Fault, and Other Carmakers Soon Will, Too”, published in the MIT Techonology Review, 8 June 2016.)
As a consequence of EDR data becoming both more abundant in type and more prevalent in usage, manufacturers and their product liability lawyers will need to better understand the full implications and admissibility of this data – and corresponding expert analysis – in court.
What’s happened so far under Daubert and Frye?
Daubert and Frye are the two main standards for the admissibility of expert testimony in US product liability cases, and the use of EDR data in expert testimony involving automobiles has been evaluated to some extent under each of these admissibility regimes.
A Daubert analysis (Daubert v Merrell Dow Pharm) requires that an opinion or technique in question:
can be and has been tested;
has been subjected to peer-review and publication;
has a known or potential rate of error;
contains standards of controlling the technique’s operation; and
has attracted widespread acceptance within a relevant scientific community.
A Frye analysis requires that expert proof concerning a new or novel scientific principle must, among other things, be based on a principle that is “sufficiently established to have gained general acceptance in the particular field in which it belongs” (Matos v State). Under Frye, the proponent must additionally “present cases and other independent evidence demonstrating the scientific acceptability of the technique”. Federal courts use the Daubert standard for admissibility of expert evidence. In many, but not all, state jurisdictions, the Daubertstandard has also superseded the Frye standard.
When EDR technology initially entered the US market in the 1990s, courts reviewed the use of data from automobile EDRs in expert testimony under the Frye general acceptance standard and, in many instances, concluded that the technology is tested and reliable. In the last several years, however, courts have also admitted expert analysis of EDRs under Daubert, but none of the cases provide in-depth analysis of the data itself, leaving little guidance for manufacturers going forward.
As AV advancements continue and EDR begins to record more data points, the use of data from EDRs in the courtroom may be subject to additional judicial scrutiny, and attorneys should be prepared for challenges to EDR data and expert analysis of such data. Although different from Daubert, analysis of EDR data under the Frye standard can offer clues on how courts will act under Daubert and provide some guidance for automobile manufacturers as they look to incorporate new types of EDR into their AVs and use such data as critical defense evidence in product liability cases.
In Matos, a defendant in a criminal vehicular homicide case challenged the admissibility of the EDR data under the Frye general acceptance standard. The prosecution countered by presenting the court with studies supporting the use of EDR data.
First, they introduced “Accuracy of Pre-Crash Speed Captured by Event Data Recorders”, an SAE technical paper authored by J Lawrence, C Wilkinson, B Heinrichs, and G Siegmund, which concluded that the EDR data was extremely accurate and only overestimated vehicle speeds by 1 mph at low speeds and by 2.5 mph at high speeds.
The prosecution also presented a paper to the court titled “Recording Automotive Crash Event Data”, authored by General Motors engineers and staff from the NHTSA. This paper included a case study by the NHTSA on real-life crashes that calculated an accuracy of +/- 4 per cent for the vehicle speed component. Admitting the EDR data into evidence, the court cited studies supporting the use of EDR data and concluded that the “process of recording and downloading [EDR] data does not appear to constitute a novel technique or method,” in part because “crash sensors such as the [EDR] have been in production in automobiles for over a decade.”
Several other courts have also analysed EDRs under the Frye standard and similarly concluded that EDRs are admissible in connection with expert testimony. In Commonwealth v Zimmermann, a defendant claimed that the judge erred in denying her motion in limine to exclude evidence taken from the vehicle’s EDR because it was not reliable. The prosecution’s expert testified that he had performed more than 200 crash tests “looking to the reliability of the accuracy” of EDRs by comparing the EDR findings to external instruments. Based on the prosecution’s expert’s testimony, the court concluded that the evidence from the EDR was reliable and the appeals court agreed. In other cases, general acceptance by the automobile industry and NHTSA was also deemed sufficient to pass the Frye standard. (See also Bachman v General Motors; People v Christmann.)
In the Daubert regime, where courts have left us with little analysis, that lack of analysis has sometimes resulted from the parties’ apparent acceptance of the reliability of EDR. See, for example, State v Diaz(because the defendant challenged the expert, but not “the science underlying the [EDR] system”, the court was entitled to assume that the underlying reliability need not be examined) and Calbas v Davis (because the defendant had not objected to the reliability of the EDR in the trial court, the court did not address the issue). Even when the moving party has not waived its opportunity to contest the data, however, courts have accepted the reliability of EDR data without thorough analysis. In Ferguson v Nat’l Freight, defendants sought to exclude expert testimony regarding a commercial tractor-trailer’s speed at different points in time as interpreted from the EDR recovered from the tractor-trailer after it collided with the plaintiff’s Dodge Ram. In analysing the opinions under Rule 702 and Daubert, the court held that the expert’s testimony regarding speed was admissible because it would “help the jury interpret the EDR data and determine the speed,” was “based on sufficient data,” and other courts had “previously relied on this type of data to determine a vehicle’s speed.”
One of those courts cited in Ferguson had discussed the evidence of speed data from the EDR on a truck in a ruling on a motion for summary judgment, but, similarly, did not assess the reliability of the data (Pracht v Saga Freight Logistics). See also Pierce v Chicago Rail Link (finding an expert’s conclusions admissible when he relied on EDR data from a train, among other information) and Johnson v Trans-Carriers (allowing expert opinions regarding the speed of a vehicle and whether the vehicle crossed the centre line of the road, both based in part on “pre-impact steering data from the crash data recorder,” but failing to analyse the reliability of the data itself).
Considerations going forward
Notably, none of the cases cited here involve AVs, so there is no absolute certainty that courts will automatically apply the analyses of such cases to the unchartered territory of driverless car cases. However, the use of EDR has existed for almost 40 years and has been recognised as an acceptable tool used by accident reconstruction experts to determine a vehicle’s speed prior to an impact (Commonwealth v Safka). It is thus reasonable to assume that as AVs use and record more data, the admissibility of new types of data recorders will play a key role in how manufacturers defend product liability suits.
The Frye cases that analysed the peer-reviewed studies, error rates and reliability of EDRs provide insight as to how courts will wrestle with new types of EDRs going forward. As the Zimmerman case shows, having experts who have performed extensive testing on the new technology will be critical to its admissibility as the technology expands. Furthermore, creating partnerships with federal agencies to evaluate the new technology, and complying with (or going above and beyond) the current NHTSA regulations for accuracy, may also help sway courts to permit new types of EDR data into evidence in future driverless automobile product liability cases. Despite the increase in the quantity of data collected via EDR, as long as the quality of what is being captured remains statistically significant and relevant, EDR is likely to continue to pass Daubert and Fryescrutiny – even in the brave new world of AV litigations.