Jauregui v. Daimler Truck North America LLC

• Court: District Court, D. Arizona
• Decided: March 25, 2025
• Docket: 2:23-cv-00729
• Status: Unknown

Opinion

1 WO 2 3 4 5 6 IN THE UNITED STATES DISTRICT COURT 7 FOR THE DISTRICT OF ARIZONA

9 Sandra Jauregui, No. CV-23-00729-PHX-JJT

10 Plaintiff, ORDER

11 v.

12 Daimler Truck North America LLC, et al.,

13 Defendants. 14 15 At issue are Defendant PACCAR Incorporated’s (Paccar) and Defendant Bendix 16 Commercial Vehicle Systems LLC’s (Bendix) separate motions to exclude the testimony 17 of Tony Gioutsos (Doc. 132; Doc. 144). Each defendant filed a notice of joinder with 18 respect to the other defendant’s motion (Doc. 146; Doc. 159). Plaintiff Sandra Jauregui 19 filed a combined response to the two motions (Doc. 163), and Defendants filed separate 20 replies (Doc. 170; Doc. 173). The Court finds these matters appropriate for resolution 21 without oral argument. See LRCiv 7.2(f). For the reasons set forth below, the Court grants 22 Defendants’ motions in part and denies them in part. 23 I. Brief Factual Background 24 This case arises out of a tragic highway collision in which Plaintiff’s late husband, 25 Mr. Jauregui, drove a big-rig truck into another big-rig truck that had stalled and come to 26 a complete standstill on the Interstate 17. Mr. Jauregui, who perished in the accident, was 27 driving a 2022 Peterbilt Conventional 579 tractor-trailer manufactured by Paccar. 28 Mr. Jauregui’s truck was equipped with a product manufactured by Bendix known as the 1 Wingman Fusion, which is an Advanced Driver Assistance System (ADAS) designed to 2 assist drivers with the avoidance of roadway hazards, including stationary objects present 3 in traffic lanes. Plaintiff asserts that a defect in Bendix’s collision avoidance system, and/or 4 a defect in the Peterbilt truck’s integration of Bendix’s technology, proximately caused the 5 collision that killed Mr. Jauregui. 6 There is no dispute between the parties regarding the nature of Bendix’s Wingman 7 Fusion ADAS system. According to Bendix’s description thereof, which Plaintiff 8 incorporates by reference, (see Doc. 163 at 9), “Bendix’s system included forward collision 9 warning, automatic braking, and adaptive cruise control components which can help 10 mitigate or prevent collisions.” (Doc. 144 at 3.) The Wingman Fusion system generates 11 data from camera and radar sensors, from which it then determines whether objects in the 12 vicinity of the host vehicle constitute a risk, such as the risk posed by a stationery vehicle. 13 (Doc. 144 at 3.) The camera and radar sensors operate at different acuity levels in different 14 physical conditions, and as a result the sensors generate a “confidence setting” that 15 accompanies the sensors’ identification of the host vehicle’s surroundings. (Doc. 144 16 at 3–4.) “Bendix’s proprietary algorithm, which is incorporated into its collision mitigation 17 system will only trigger alerts or automatic braking—depending on various data inputs—if 18 the sensors definitively detect a stationary object or vehicle.” (Doc. 144 at 4.) The 19 algorithm is designed to balance the competing goals of responding to potential risks and 20 avoiding false alerts. (Doc. 144 at 4.) Thus, the proper functioning of Bendix’s system 21 depends upon (1) the efficacy with which its sensors are able to collect data and (2) the 22 algorithm’s processing of that data. (Doc. 144 at 4.) 23 In support of her claims against Paccar and Bendix, Plaintiff has retained 24 Mr. Gioutsos to serve as an expert witness regarding the alleged malfunctioning of the 25 Wingman Fusion system during the subject accident. In motions that largely mirror one 26 another, Bendix and Paccar argue that the testimony proffered by Mr. Gioutsos is 27 inadmissible both because Mr. Gioutsos is unqualified to opine on the matter at hand and 28 because his testimony is the product of unreliable methodology. Defendants also contend 1 that the testimony proffered by Mr. Gioutsos includes impermissible legal conclusions. The 2 Court addresses these arguments in turn. 3 II. Legal Standard 4 Under Federal Rule of Evidence 702, an expert may testify on the basis of 5 “scientific, technical, or other specialized knowledge” if it “will assist the trier of fact to 6 understand the evidence,” provided the testimony rests on “sufficient facts or data” and 7 “reliable principles and methods,” and “the witness has reliably applied the principles and 8 methods to the facts of the case.” Fed. R. Evid. 702(a)–(d). The trial judge acts as the 9 “gatekeeper” of expert witness testimony by engaging in a two-part analysis. Daubert v. 10 Merrell Dow Pharms., Inc., 509 U.S. 579, 589, 592 (1993). First, the trial judge must 11 determine that the proposed expert witness testimony is based on scientific, technical, or 12 other specialized knowledge. Id.; Kumho Tire Co. v. Carmichael, 526 U.S. 137, 147 13 (1999). Second, the trial court must ensure that the proposed testimony is relevant—that it 14 “will assist the trier of fact to understand or determine a fact in issue.” Id. “Evidence is 15 relevant if it has any tendency to make a fact more or less probable than it would be without 16 the evidence and the fact is of consequence in determining the action.” Fed. R. Evid. 401. 17 “The inquiry envisioned by Rule 702” is “a flexible one.” Daubert, 509 U.S. at 594. 18 “The focus . . . must be solely on principles and methodology, not on the conclusions that 19 they generate.” Id. The advisory committee notes on the 2000 amendments to Rule 702 20 explain that Rule 702 (as amended in response to Daubert) “is not intended to provide an 21 excuse for an automatic challenge to the testimony of every expert.” See Kumho Tire, 526 22 U.S. at 152. “Vigorous cross-examination, presentation of contrary evidence, and careful 23 instruction on the burden of proof are the traditional and appropriate means of attacking 24 shaky but admissible evidence.” Daubert, 509 U.S. at 595 (citation omitted). 25 III. Discussion 26 A. Mr. Gioutsos’ Qualification as an Expert Witness 27 Throughout their motions, in an apparent effort to downplay his technical 28 background, Defendants repeatedly refer to Mr. Gioutsos as a salesman. That vocational 1 moniker does nothing to diminish Mr. Gioutsos’s decades-long history as an engineer 2 responsible for the design of numerous camera- and radar-based algorithms. (See 3 Doc. 132-9.) Although Mr. Gioutsos’s most recent work experience focused on sales and 4 marketing, there is no genuine dispute that he has extensive experience in the design and 5 implementation of algorithms, including time-sensitive algorithms that integrate sensor- 6 generated data for the purpose of executing a rapid mechanical process. Defendants argue 7 that Mr. Gioutsos is nevertheless unqualified to opine on the functioning of Bendix’s 8 ADAS system because he acquired automotive algorithm expertise primarily though his 9 design of products that control the firing of airbags, not the avoidance of collisions. (See 10 Doc. 132 at 8; Doc. 144 at 6.) Similarly, although Mr. Gioutsos has experience writing 11 algorithms that incorporate data from both cameras and radar, (see Doc. 132-9), Defendants 12 contend that he is unqualified to serve as an expert in this case because he has never 13 “integrated a radar and camera system in a production vehicle” and has not “worked on 14 brake system integration.” (See Doc. 132 at 8; Doc. 144 at 6.) Finally, Defendants argue 15 that Mr. Gioutsos lacks meaningful expertise in “human factors,” which is the body of 16 knowledge that concerns driver psychology, such as a driver’s willingness to accept an 17 excessive number of hazard alerts. (See Doc. 144 at 8.) Although the Court agrees that 18 Mr. Gioutsos is unqualified to provide expert testimony concerning the human-factor 19 considerations that informed the calibration of Bendix’s algorithm, the Court rejects 20 Defendants’ position that he is unqualified to opine on the algorithm itself. 21 Defendants do not explain in what manner the sensors and algorithms that control 22 collision avoidance differ from the sensors and algorithms that control airbag deployment. 23 Plaintiff plausibly asserts that the two systems are similar and that, as part of the airbag 24 algorithm design process, Mr. Gioutsos “analyzed a radar based forward collision warning 25 system for purposes of analyzing the capability of that system to supply speed information 26 of objects ahead to help improve the timing performance of frontal airbag crash sensing.” 27 (Doc. 163 at 9–10.) Although a collision-avoidance mechanical system surely differs from 28 an airbag-deployment mechanical system, Mr. Gioutsos does not profess to be an expert in 1 vehicular braking, materials science, or any other body of knowledge related to the physical 2 stopping of a big-rig truck. Mr. Gioutsos’s expertise encompasses only the algorithmic 3 processing of data generated by cameras and radar, not the execution of whatever task the 4 algorithm outputs. The Court fails to perceive why Mr. Gioutsos’s inexperience with brake 5 systems in production vehicles would ipso facto render him unqualified to opine on the 6 functioning of the sensors and algorithm that combine to issue a command to a brake 7 system. 8 Moreover, to the extent that experience with collision-avoidance algorithms is a 9 prerequisite to opining upon such algorithms, Mr. Gioutsos possesses the requisite 10 experience. Mr. Gioutsos has previously worked with ADAS systems that implement 11 collision avoidance algorithms. In the early 90’s, as director of research and development 12 for Automotive Systems Lab, Mr. Gioutsos oversaw the design of computational 13 technology capable of “measuring the performance of ANY algorithm (e.g. All ADAS 14 detection algorithms like AEB).” (Doc. 132-9 at 3.) Then, as a director of sales at Siemens 15 in the 2010’s, Mr. Gioutsos developed expertise in the functioning of a tool designed to 16 simulate the performance of various collision-avoidance technologies, including the ADAS 17 system at issue here. (Doc. 132-9 at 2.) Defendants correctly state that “working adjacent 18 to programmers and developers of a technology does not make one qualified to opine on 19 the particularities of its programming and design.” (Doc. 132 at 9.) However, Mr. Gioutsos 20 does not claim that his exposure to ADAS systems by way of his work on simulation 21 technology by itself renders him an expert on the ADAS system at issue here. Instead, 22 Mr. Gioutsos’s indirect experience with collision-avoidance algorithms serves to bolster 23 his pre-existing conversance with algorithms such that that expertise may extend to ADAS 24 technology. 25 “The party offering expert testimony has the burden of establishing its 26 admissibility.” Bldg. Indus. Ass’n of Wash. v. Wash. State Bldg. Code Council, 683 F.3d 27 1144, 1154 (9th Cir. 2012). The Court is satisfied that Plaintiff has carried her burden with 28 respect to Mr. Gioutsos’s general qualifications. In order to defeat that conclusion, 1 Defendants needed to provide some explanation as to how the sensors and algorithms of a 2 collision-avoidance system differ so materially from the sensors and algorithms with which 3 Mr. Gioutsos is familiar that his expertise in the latter is inapposite to the former, even in 4 light of his various sources of exposure to collision-avoidance technology. Defendants 5 have offered no such explanation. For that reason, the cases cited by Defendants are 6 unavailing. The principal case relied upon by Defendants is Diviero v. Uniroyal Goodrich 7 Tire Co., 919 F. Supp. 1353, 1356–57 (D. Ariz. 1996). (See Doc. 132 at 9–10; Doc. 144 8 at 9–10.) In Diviero, this District held that a tire engineer who only possessed experience 9 with bias belted tires, but who lacked experience with steel belted radial tires and also 10 lacked knowledge in chemistry, was unqualified to provide expert testimony on steel belted 11 radial tires. 919 F. Supp. at 1356–57. Crucially, the defendant in Diviero provided two of 12 its own experts in steel belted radial tires who persuaded the court “that steel belted radial 13 tires are unique and complex and the experience and knowledge must have some valid 14 connection with these tires,” “that it is important to have worked in a plant with engineers 15 and chemists involved in control testing of steel belted radial tires,” and “that it is standard 16 in the tire industry that one must have expertise which relates to the particular tire for the 17 tire failure analysis.” Id. Diviero does not control the instant analysis because Defendants 18 have declined to apprise the Court of the source of Mr. Gioutsos’s purported insufficiency 19 as an expert. The Court concludes that Mr. Gioutsos is qualified to render expert testimony 20 on the functioning of Bendix’s Wingman Fusion ADAS system. 21 However, Mr. Gioutsos is not qualified to provide expert testimony regarding the 22 human-factors considerations that informed Bendix’s calibration of its ADAS system. In 23 his rebuttal report, Mr. Gioutsos states that “[d]rivers are accepting all of those 24 alerts/alarms, which are quite frequently false alerts/alarms” and that “false alarms in 25 vehicles are very common in American vehicles over the past decades.” (Doc. 144-13 26 at 14.) Defendants assert that Mr. Gioutsos’s expertise in algorithms does not permit him 27 to opine on human factors. (See Doc. 144 at 8.) Mr. Gioutsos expressly concedes that those 28 statements fall outside the scope of his expertise and are therefore inadmissible as expert 1 testimony. (See Doc. 144-10 at 90–92.) Plaintiff does not contest this point. The Court 2 therefore holds that Mr. Gioutsos may not testify on the subject of human factors. 3 B. The Reliability of Mr. Gioutsos’s Expert Opinion 4 Defendants argue that Mr. Gioutsos’s expert opinion is unreliable because it 5 depends upon impermissible assumptions and is not predicated upon adequate data. 6 Although the Court disagrees with some of Defendants’ reasoning, the Court nevertheless 7 agrees with their ultimate contention. Mr. Gioutsos’s testimony is inadmissible for the 8 purpose of explaining the cause of the accident in this case. 9 In his expert report, after expounding upon his background and the materials he 10 reviewed, Mr. Gioutsos describes the physical circumstances of the collision and concludes 11 that the camera and radar sensors integrated into Bendix’s Wingman Fusion ADAS system 12 likely had no issue detecting the stalled truck in the road. 13 Mr. Jauregui was driving northbound on I-17 near mile post 216.1 at about 14 68 MPH. It was about 4:02 a.m., the weather was clear and the lighting conditions were good. The road was straight with some very slight curve to 15 the left. The 2022 Peterbilt driven by Mr. Jauregui was in the center left lane 16 traveling at approximately 68 mph. In the same lane was a stopped Tractor/trailer. The truck was a 2018 Freightliner. The trailer was a 2018 17 Hyundai refrigerated box trailer. 18 . . . . As discussed, the night of the crash was basically perfect for a camera and 19 an image processing algorithm (IPA) to find objects and lane lines. The Hyundai trailer had a relatively easy rear (and flashing hazard lights) for an 20 IPA to recognize. This recognition would produce a bounding box (of the 21 trailer) to be “fused” with radar data. The fusion algorithm would also use the lane lines to determine if the trailer was within the lane. This would make 22 the recognition job of the camera IPA fairly straightforward in the 2022 23 timeframe. . . . . 24 [O]ne can see that there are really no stationary false “objects” near the road. 25 These would include overhead signs, bridges, tunnels, road signs, guardrails, traffic lights, poles, railroad tracks, etc. Without another vehicle (or 26 Pedestrian, biker, etc.). A radar on the 2022 Peterbilt would have produced 27 only limited returns from the ground, road and shrubbery other than from the Hyundai trailer. 28 1 The trailer had large areas of flat metal structures for the radar microwave signal to reflect off of. For example, the rear doors and all of the metal 2 bracketry for them. Also, the underride protection was made of metal and 3 had large sections of flat surfaces facing the travel direction.

4 As discussed earlier for this crash, there was a large vehicle overlap. The 5 impact was slightly off-center because of last second steering at the end of the crash, but this slight bias would not have affected a radar return much 6 even in that last second. Lots of other parts of the trailer would have produced 7 multiple radar returns to process in the signal processing portion of the radar. However, since the vehicle was not moving it would be relatively simple to 8 group these together and determine that a stationary large vehicle was in front 9 of the 2022 Peterbilt. 10 (Doc. 132-12 at 9, 16–17, 20–21 (footnotes and internal citations omitted).) From there, 11 Mr. Gioutsos assumes that the sensors were functioning properly. (Doc. 132-12 at 20 12 (stating that “the Bendix Wingman Advanced Fusion system’s camera and radar should 13 have supplied adequate data for that system to process and react” (emphasis added)); 14 Doc. 132-12 at 25 (“The failure was not because of the inadequacy of the camera, radar or 15 computer processing capabilities.”).) Based upon the facts surrounding the collision and 16 the assumption that the sensors were not broken or otherwise malfunctioning, Mr. Gioutsos 17 then infers that the source of the ADAS system’s failure to issue a driver alert or engage in 18 automatic braking must have been the algorithm’s prioritization of avoiding false alarms 19 over avoiding collisions, as there is simply no other plausible explanation. (See 20 Doc. 132-12 at 25 (“The Failure was because of poor decisions on algorithms and 21 applications of those technologies in the Bendix system.”); Doc. 132-12 at 26 (“Bendix 22 and PACCAR’s prioritizing avoidance of some false alarms over avoidance of high-speed 23 heavy truck collisions is clearly a bad decision.”).) 24 Defendants cite numerous cases for the proposition that a plaintiff may not infer the 25 existence of a defect simply by virtue of an accident’s occurrence. The case relied upon by 26 Defendants that the Court finds most apposite is Watson v. Sunbeam Corp., 816 F. Supp. 27 384 (D. Md. 1993). In Watson, a fire arose in a bunk bed in which a child had been using 28 an electric blanket. Id. at 386. After the fire had been put out, a fire marshal opined that it 1 could not be determined whether the fire had been started by a defect in the electric blanket, 2 by the electric blanket’s misuse, or by a child’s playing with matches. Id. In assessing an 3 expert’s assertion that the fire had been caused by a product defect, the court noted that an 4 expert cannot infer the existence of a defect from the mere occurrence of an accident. Id. 5 at 387–88.1 The Court views Watson and the other cases cited by Defendants as standing 6 for the proposition that a plaintiff may not infer the existence of a defect from the 7 occurrence of an accident where such inference is not logically supported. Thus, in Watson, 8 the plaintiff could not conclude that the electric blanket was marred by a defect simply by 9 virtue of the fire’s occurrence, as doing so would have improperly overlooked the plausible 10 explanation that the fire was caused by either misuse of the blanket or by pediatric 11 pyromania. In other words, an expert may not pick a causal explanation out of a hat full of 12 such explanations. 13 Here, although the portion of Mr. Gioutsos’s report described above sets forth a 14 hypothesis that the Court might have accepted as logically sound and not in contravention 15 of Watson or other similar cases, Mr. Gioutsos’s report later undermines the very 16 assumption upon which its conclusion rests. Eight pages after writing that “[t]he failure 17 was not because of the inadequacy of the camera, radar or computer processing 18 capabilities” and that “[t]he hardware in the Bendix Wingman Advanced Fusion system is 19 easily capable of providing the Bendix promised 3.5 second forward collision warning,” 20 Mr. Gioutsos writes that he was “flabbergasted” to learn that the Wingman Fusion system 21 utilizes EyeQ2 camera technology, which Mr. Gioutsos asserts is out of date. (Doc. 132-12 22 at 33.) He expressly recognizes that it is “possible the Mobileye [camera] IPA had trouble 23 recognizing the box trailer with flashing hazard lights” but contends that “if EyeQ2 was 24 the issue, it did not need be [sic]” because “Bendix should have been using the EyeQ3 chip 25 at a minimum.” (Doc. 132-12 at 32–33.) As Plaintiff expressly concedes, the algorithm in 26 Bendix’s ADAS system relies upon a confidence setting generated by the system’s sensors, 27 which in turn depends upon the acuity of the sensors themselves. Without proof, or at the

28 1 The Court in Watson ultimately admitted the expert testimony for reasons that are not relevant here. See 816 F. Supp. at 388. 1 very least a reasonable assumption, establishing that the sensors did indeed perceive the 2 stalled vehicle in front of Mr. Jauregui’s truck, it is impossible to determine whether the 3 non-occurrence of a driver alert or automatic braking was caused by a defect in Bendix’s 4 algorithm or the interaction of its hardware with exterior roadway conditions. 5 Throughout their motions, Defendants repeatedly fault Mr. Gioutsos for not having 6 inspected the code of Bendix’s underlying algorithm. Indeed, Defendants assert, and 7 Plaintiff does not gainsay, that Plaintiff never sought any aspect of Bendix’s ADAS system 8 in discovery and indeed did not even serve a written discovery request of any kind on either 9 Bendix or Paccar. (See, e.g., Doc. 132 at 8, 14.) The Court will not say as a matter of law 10 that an expert must in all circumstances base his opinion of an ADAS algorithm’s 11 functionality on the underlying code, as it may be possible for an expert to draw reliable 12 conclusions without having done so if he controls for exogenous variables. But in this case, 13 Mr. Gioutsos has not accounted for considerations extraneous to the algorithm, as he also 14 did not analyze the Wingman Fusion’s radar or camera systems. 15 Thus, much of his report is mere guesswork. Given the express uncertainty 16 regarding whether the Wingman Fusion’s camera system perceived the stalled vehicle in 17 this case, the only way that one could be sure the algorithm was at fault is if one is confident 18 that the radar sensors alone generated sufficient data for the algorithm to act upon. But 19 according to materials incorporated into Mr. Gioutsos’s report, “Stationary Vehicle 20 Braking (SVB) is possible because the system uses BOTH radar and camera data to 21 confirm the vehicle ahead.” (Doc. 132-12 at 22 (emphasis in original).) Based on 22 Mr. Gioutsos’s report, the Court cannot countenance an assumption that the radar sensors 23 by themselves generated sufficient data upon which the algorithm could have outputted a 24 collision-avoidance command. At best, Mr. Gioutsos’s testimony establishes that one of 25 several things might have caused Bendix’s ADAS system to not issue a driver alert or 26 engage in automatic braking. Although such information might be helpful to the finder of 27 fact, it runs contrary to the purpose of Mr. Gioutsos’s testimony, which Plaintiff submits 28 to substantiate her assertion that the collision was caused by a “faulty algorithm” and 1 “could not [have] be[en] the result of faulty cameras or radar.” (See Doc. 163 at 12 2 (emphasis in original).) Plaintiff may not utilize Mr. Gioutsos’s expert testimony for that 3 purpose. 4 Other portions of Mr. Gioutsos’s report are also unreliable. For instance, the section 5 of his report addressing his recommended implementation of algorithmic “fuzzy logic” is 6 of little utility with respect to determining the accident’s cause, as Mr. Gioutsos cannot say 7 that Bendix’s algorithm does not already incorporate fuzzy logic, given that he neither 8 inspected the Wingman Fusion’s algorithm nor so controlled for all other variables that he 9 could logically deduce the characteristics of the algorithm. (See Doc. 132-12 at 26–30.) 10 Similarly, Mr. Gioutsos’s implication that Bendix implemented an algorithmic shut-off 11 function is speculation, as is clear from the verbiage of the report. (See, e.g., Doc. 132-12 12 at 30 (“To ‘shut the system OFF’ for high-speed differentials seemed like what 13 happened.”).) Mr. Gioutsos’s report indicates that an older version of Bendix’s ADAS 14 technology, the radar-only Wingman Advanced, implemented a shut-off function, but 15 Mr. Gioutsos can only guess as to whether the Wingman Fusion does as well. (See Doc. 16 132-12 at 30 n.10 (“This paper was written about the Wingman [A]dvanced. But there is 17 no reason to believe that a similar strategy is not used in the Wingman Fusion . . . .”).) In 18 sum, Mr. Gioutsos’s conclusion that the algorithm’s calibration defectively prioritized the 19 avoidance of false alarms over the avoidance of collisions is unreliable and therefore 20 inadmissible. 21 That is not to say that all of Mr. Gioutsos’s testimony is inadmissible. To the extent 22 relevant and encompassed by his report, he may still provide useful background 23 information on ADAS algorithms generally, and he may opine on the possible reasons that 24 the collision in this case was not mitigated by a driver alert or automatic braking. But he 25 may not assert that any particular feature of Bendix’s ADAS system was the proximate 26 cause of the crash, as Plaintiff has not established by a preponderance of the evidence that 27 Mr. Gioutsos has arrived at a reliable opinion thereon. Additionally, to the extent that 28 Mr. Gioutsos intends to testify that Defendants’ ADAS system was defective by virtue of 1 its use or non-use of certain hardware, he may not do so. After criticizing Defendants’ use 2 of a camera chip from 2010 and their failure to use “dedicated short-range communications 3 systems,” (Doc. 132-12 at 32–40), Mr. Gioutsos asserts that “[t]he cost is not really relevant 4 in performance, because there is little to no increase in cost to make it [sic] the Wingman 5 Advanced Fusion system capable of assisting drivers using that system in avoiding 6 stationary vehicles in their lane when they are approaching the stationary vehicle at the 65 7 to 70 mph speed range” (Doc. 132-12 at 58–59.) That statement is quite literally baseless. 8 Mr. Gioutsos does not even minimally consider the cost of developing and implementing 9 alternative ADAS designs in his report. Again, if Plaintiff possesses independent evidence 10 regarding the feasibility of alternative ADAS designs, then Mr. Gioutsos may provide 11 foundational testimony addressing the technical efficacy of such alternatives to the extent 12 that that testimony is relevant, within the scope of his report, and adequately disclosed. 13 C. Whether Mr. Gioutsos’s Testimony Impermissibly Embraces Legal 14 Conclusions 15 Defendants assert that Mr. Gioutsos’s report improperly touches upon legal issues 16 that expert witnesses may not opine on, such as legal duties, Arizona statutes, Arizona jury 17 instructions, and the sufficiency of evidence. (Doc. 132 at 17; Doc. 144 at 13.) Plaintiff 18 does not contest this point, but simply writes that “[d]uring Mr. Gioutsos’s testimony in 19 this matter, Plaintiff will ensure that, while he will be asked questions about the ultimate 20 issues in this case, none of the questions will be designed to elicit a legal conclusion.” 21 (Doc. 163 at 17.) There is therefore no dispute regarding this issue for the Court to resolve 22 at this juncture. 23 IV. Conclusion 24 Although Mr. Gioutsos is a qualified expert, his opinions are inadmissible for their 25 intended purpose of establishing that the Wingman Fusion ADAS system’s algorithm 26 proximately caused the collision in this case. Mr. Gioutsos’s testimony may be admissible 27 for other purposes, such as those described supra, but Plaintiff may not submit his 28 1 || testimony for the purpose of establishing that any particular feature of the Wingman Fusion 2 || was the proximate cause of the relevant trucking accident. 3 IT IS THEREFORE ORDERED granting in part and denying in part Defendants’ motions to exclude the testimony of Tony Gioutsos (Doc. 132; Doc. 144). 5 Dated this 25th day of March, 2025. CN

7 wefehlee— Unifga StatesDistrict Judge 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28

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