Self-Driving Safety Report 2020 Content

03 Letter from CEO Logan Green 28 Validation Methods 05 Introduction 31 Human Machine Interface 07 Lyft’s Safety Principles 33 Cybersecurity 10 Consumer Education 36 Crashworthiness 13 System Safety 37 Post-Crash ADS Behavior 17 Operational Safety 38 Data Recording 21 Operational Design Domain (ODD) 39 Federal, State, and Local Laws 22 Object and Event Detection and Response 40 Conclusion • The eyes of our cars • The brain of our cars 41 Legal Disclaimer • The knowledge of our cars 42 Glossary of Terms 27 Fallback - Minimal Risk Condition LYFT 2020 SELF-DRIVING SAFETY REPORT Letter from theCEO safety methodology andmulti-staged testing protocol that allows usto first demonstrate our To gainthat level of trust, we recognize that it must beearned. That’s why we’ve developed a the critical mass. deliver ontheir promise for safe, accessible, andenvironmentally sustainable transportation for and regulations. Onlytogether can we gainthepublic’s trust andenableself-driving cars to state, andfederal policymakers andregulators to establish clear and transparent guidelines collaborate withthebroader autonomous vehicle community, industrystakeholders andlocal, Ultimately, our goalfor this VSSA isto deliver anobjective framework for reference aswe approach andmethodology to autonomous vehicle development andsafety. document provides atransparent overview of Lyft’s overarching safety principlesanddetails our Which bringsusto the Voluntary Safety Self-Assessment (VSSA) that you are reading today. This and center. At Lyft, safety isfundamental to everything we do. accessible intheday-to-day lives of Americans. This willremain an aspiration if safety isnot front that to center transportation around peoplewillrequire self-driving cars to beavailable and Our visionfor thefuture of transportation iscentered around people, andnot cars. We recognize by dramatically reducing thetragic effects of humanerror. stand firmthat self-driving cars have significant potential tomake our roadssafer than ever before including congestion, environmental impacts, access inequality, andmost importantly, safety. We transportation system of tomorrow, addressing thechallengeswe face ontoday’s roadways, the era of autonomous vehicles. Lyft believes that self-driving cars willbecritical to theimproved Fast-forward to 2020, andwe are speedingtoward thenext phaseof transportation innovation – has beenchampioningever since. This was just thebeginning of amovement to endcar ownership andreclaim our citiesthat Lyft transportation, becoming thefirst company to establish peer-to-peer, on-demand ridesharing. Lyft was founded in2012part to usetechnology to radically shift theconcept of personal Pioneering thefuture of transportation, together.

3 LYFT 2020 SELF-DRIVING SAFETY REPORT a thingof thepast. self-driving cars steering theway toward safer streets andhealthier cities,whilealsomaking traffic Together, we can make tangible progress toward realizing thefuture of transportation with and strong execution, ensuringthesafety of our riders andour communities every step of theway. lightly, andwe intend to leadthisnext phaseof transportation innovation withintegrity, humanity, the most significant societal shifts since theadvent of the car. We donot take that responsibility With theacceleration of our autonomous vehicle fleet, Lyft hastheopportunity to deliver one of years to come. committed to our platform asaplace to provide drivers withearningsopportunitiesnow andfor all rides. Therefore, humandrivers willcontinue to beacritical part of theLyft platform andwe are conditions. Even asself-driving cars become more prevalent, they won’t becapable of doing decades to bedeployed at scale, across awiderange of geographies andenvironmental important to note that self-driving technology willtake timeto evolve andit willtake years or to our originalmission:to improve people’s lives withtheworld’s best transportation. It is As we continue to championthefuture of transportation, Lyft remains wholeheartedly committed bicyclists, and scooter riders. This isthepathto publictrust andadoption. to leverage thistechnology to address thesafety of vulnerable road users, includingpedestrians, safety includesalltypesof transportation modesandroad users, we think it isespeciallyimportant to regulators, aswell asstakeholders, passengers andother road users. And since Lyft’s focus on technology to besafe to ourselves, withincontrolled Lyft-owned testing environments, andthen Chief Executive Officer Logan Green Sincerely, Letter from theCEO (continued)

4 LYFT 2020 SELF-DRIVING SAFETY REPORT Introduction Across transportation modes,Lyft iscommitted to improving safety for all, especiallyvulnerable road demonstrate thesafety of AVs. and understandable safety framework neededto forge away forward to quantify and public can seeandunderstand. Currently, we are partneringwithothers to create thetransparent challenge initself. We believe that simplicity inmetrics iskey to solve this challenge inaway that the and understandable methods andmetrics to demonstrate safety, whichisacomplex technical For thepublicto put its collective trust inautonomous technology, there isaneedfor transparent passengers, other road users, andof course, thepublicat large. and leadership —isdedicated to earningandmaintaining thetrust of regulators, stakeholders, involved withLyft’s self-driving division—from theoperators andengineers to thedata scientists the publicmust first come to trust that the technology issafe andsecure. That’s why everyone Make nomistake —Lyft understands that for AVs to emerge asamainstream transportation source, reduction, AVs can helpshapecitiesof thefuture to serve people, andnot cars. the effects of humanerror. When combined withthebenefits inmobility, accessibility, andemissions by advances inpersonal andpublicsafety, comprised primarilyof thepotential for AVs to reduce to significantly transform theentire transportation system for good. This changewillbehighlighted With thedevelopment of autonomous vehicle (AV) technology comes thelong-awaited opportunity the last decade to increase vehicle safety andreduce thenumber of fatalities. an acceptably “safe” system. Consequently, onlymodest, incremental progress hasbeenmadein unavoidable byproduct of our transportation system, andhave come to accept theseoutcomes as Yet society haslargely internalized suchalarge number of motor vehicle fatalities asthe basic humanerror contributing to 94%of thefatal crashes. our nation’s roads, according to theNational Highway Traffic Safety Administration (NHTSA), with access inequality, andmost importantly, safety. Inthe2018calendar year, 36,560peoplediedon Today’s transportation system hasmany challenges,includingcongestion, environmental impacts,

5 LYFT 2020 SELF-DRIVING SAFETY REPORT importance of thispotentially safety-beneficial technology. dialogue withregulators, legislators, partners, other stakeholders, andthepublicabout the intended to communicate our principledapproach to AV safety, andto continue aforward-looking supervision of safety operators inthevehicle. This Voluntary Safety Self Assessment (VSSA) is continuously advance thestate of our technology to eventually operate without theimmediate the presence of human safety operators to reduce andmitigate risk.However, we fullyexpect to developing thistechnology. At thisstage of development, Lyft’s systematic safety approach includes These ideashave shapedour AV program andbrought usto our current state of testing and scooting indenseurbanareas. a growing number of vulnerable road users that are increasingly reliant onwalking, biking,and priority focus ison VRU safety andhow thevehicles can operate safely inanenvironment amongst users (VRUs) suchaspedestrians,bicyclists, andscooter riders. As we develop anddeploy AVs, a Introduction (continued)

6 Lyft’s Safety Principles

Safety is fundamental to everything we do. Because we want to focus on the outcome of increased safety, Lyft has established the following core safety principles that guide our autonomous vehicle program to help reduce all types of roadway risks:

Improve autonomous technology

Guard the safety of all road users LYFT 2020 SELF-DRIVING SAFETY REPORT SAFETY SELF-DRIVING 2020 LYFT

Quantify safety through metrics

Collaborate with others

Maintain trust

7 Lyft’s Safety Principles (continued)

We will continuously seek to improve our AV technology to reduce the aggregate effect of human error on road safety by learning from experience and deliberately mitigating developmental risks.

Our current transportation system in the US today is far from perfect, and in fact no system is ever perfect. We have to strive for thoughtful and timely continuous improvement, and we believe that we can improve the transportation system by reducing the effects of human error that result in crashes. As we develop AV technology, Lyft believes it is critical to learn from experience as we systematically identify, understand, and resolve issues with this technology. We will strive to continuously mitigate risks and improve the technology through our systematic safety approach.

We will guard the safety of all road users, while attending to the uniqueness of vulnerable road users (pedestrians, bicyclists, scooter riders, etc.).

Walking, biking, and scooting are an increasingly important transportation mode in our cities and suburbs. Lyft envisions cities designed for people (not cars), including a continuous presence of pedestrian and micro- mobility road users. Lyft believes that vulnerable road users (VRUs) deserve special attention as we develop self-driving technology. We are convinced that the vigilance of sensors that don’t have human characteristics, such as getting distracted or sleepy, is potentially powerful in preventing collisions with people. We will focus on these LYFT 2020 SELF-DRIVING SAFETY REPORT SAFETY SELF-DRIVING 2020 LYFT road users and hope to leverage our knowledge and experience on how people use micro-mobility devices in cities to aid our development of self-driving technology.

We will quantify safety through metrics, and when possible compare AV performance to aggregate human driver performance.

Lyft believes that establishing clear and understandable measures of safety for AVs is a critical step to earn the trust of our customers and stakeholders, including cities and states where we develop or intend to operate. To do that, we believe it is incumbent on industry developers to work with each other and with other stakeholders to develop simple, but meaningful, quantified metrics and methods to assure the safe operation of these vehicles. We also believe it is important to use these metrics, where possible, to compare to the performance of human drivers to understand societal outcomes for transportation safety.

8 Lyft’s Safety Principles (continued)

We will collaborate with others to share safety best practices to improve safety for all road users.

Safety is a fundamental consideration in developing AV technology, and Lyft believes that we should work together with other developers and stakeholders to deliver on the safety potential of this technology. In truth, developing this technology is a significant technical and societal challenge, and AV developers and stakeholders must collaborate to establish and share best practices to further the safety of the transportation public. To that end, Lyft is committed to partnering with federal and state governments and other public and private stakeholders to implement the safe testing and deployment of autonomous vehicles.

We will maintain our customers’ and stakeholders’ trust in Lyft, and consider safety as critical to our decision-making process.

The safety of the millions of people using Lyft’s mobility platform has been fundamental to Lyft since its founding. We have worked hard to earn the trust of our customers and stakeholders by continuously improving the safety of the Lyft platform by developing innovative products, policies, and processes. Lyft’s approach to building an autonomous vehicle passenger service is no different, and customer safety and trust will always be the prime factors in our decision-making process. LYFT 2020 SELF-DRIVING SAFETY REPORT SAFETY SELF-DRIVING 2020 LYFT

9 LYFT 2020 SELF-DRIVING SAFETY REPORT Consumer Education Nevada pilot are likely to take another self-driving rideinthefuture. understanding of self-driving technology. Ninety-five percent (95%) of riders inour Las Vegas, focused onsafety at alltimes.Survey data shows thisprogram allows consumers to gainabetter through their Lyft app. All pilot program ridesincludeasafety operator inthedriver’s seat whois to request aself-driving ridejust asthey would astandard Lyft ride, andoffer feedback directly today, through thesameLyft appthey already know andtrust. Lyft riders inselect markets are able Our self-driving pilot program allows Lyft riders to engagedirectly withself-driving technology Lyft’s self-driving pilot program every step of theself-driving journey. multiple ways to provide feedback, we’re focused ongivingour riders peace-of-mind during rider onwhat to expect duringaself-driving ride, providing in-car education, or offering riders Rider safety andeducation isfundamental to our approach. Whether it’s communicating witha rideshare safety to our autonomous future. standard for rideshare safety that it created, andwe’re applyingthisnear decade of experience in and give thempeace of mindabout their safety. We’re proud of our safety-first legacy andthe first ride was given in2013, we focused onbuilding tools to helppeopleget where they are going, Since Lyft’s founding, we have centered our platform around thesafety of our users. Even before the better understand what to expect. experience it. They can alsohear from real riders whohave taken self-driving ridesto helpthem about thebenefits of self-driving technology, as well asthebasics of how andwhere they can • Before theride: technology that powers theride, andengagewiththetechnology safely. Lyft’s user experience isdesignedto helpriders request self-driving ridesseamlessly, understand the Our rider journey information isupdated frequently asthetechnology evolves. about key aspects of their self-driving ride, suchas pick-up details andin-ride safety. This • astandard Lyft rideinstead of aself-driving ride. therider. All self-driving rides onour network are opt-in: A rider can always chooseto use • In-app education: Before aself-driving ride isbooked, theLyft appeducates therider Self-driving opt-in: At Lyft, we believe thedecisionto tryaself-driving ride shouldsit with Through theLyft appandonthelyft.com/self-driving site, our riders can learn

10 Consumer Education (continued)

• Taking a ride: • Verifying the vehicle: Riders are provided with the same identifying information we provide for a standard Lyft ride, and prompted to verify that they are entering the correct vehicle. • In-car education: Once riders enter a self-driving car, Lyft’s onboard display helps them understand the technology and how to engage with core safety features. • Live support: In addition to the in-car safety operator, a live support agent is always on call to assist with questions or issues that may come up, and can be reached either through the Lyft in-car app or through our critical response line. Should a safety-critical event occur, a critical response agent will provide riders immediate support and coordinate with third-party emergency personnel. • After the ride: With teams spread across all time zones, we offer 24/7 support to our self-driving riders, even after their ride has ended. LYFT 2020 SELF-DRIVING SAFETY REPORT SAFETY SELF-DRIVING 2020 LYFT

Focus on accessibility

From day one, we have considered the accessibility of self-driving for all Lyft users. For example, we have partnered with the National Federation of the Blind to pilot self-driving rides with our blind and low vision users.

11 LYFT 2020 SELF-DRIVING SAFETY REPORT Consumer Education (continued) in establishing industryorganizations that support safety andconsumer education: to create asystem that issafe, effective, andtransparent. In fact, Lyft hasbeenaleading force As reflected inthisapproach, we believe that it’s critical to collaborate withindustrystakeholders Lyft partners withleadingself-driving technology companies to deploy their AVs onour network. Partnering with theindustry future of mobility. low vision consumers are includedinthe Federation of the Blind to ensure blindand Lyft haspartnered with theNational safe movement of our fleet. regulators incitiesof operation to guidethe Lyft works with first responders andlocal benefits of self-driving cars. the publicto realize thesafety andsocietal which works with lawmakers, regulators, and of theSelf-Driving Coalition for Safer Streets, Lyft isafounding andcurrent Board member lead creation of industry standards. Consortium (AVSC) inSeptember 2019to Lyft joinedthe Automated Vehicle Safety steering committee member. Education (PAVE) inFebruary 2019asa Lyft joinedPartners for Automated Vehicle

12 LYFT 2020 SELF-DRIVING SAFETY REPORT System Safety and unknown risks. AVs currently exists. With that inmind,Lyft aimsto reasonably anddeliberately mitigate both known and road users assafe aspossible. Unfortunately, nosingledefinition or quantification of “safety” for The development of autonomous systems requires asystematic approach to keep both passengers approach includes: safe to operate, that drives safety goalsalignedappropriately to thedevelopment phase. This and other road users. This starts withdefining asafety case, astructured argument that our AV is We employ arobust systems engineeringapproach, includingafocus onthesafety of passengers • Continuous risk monitoring, assessment, analysis, andmitigationprocess • Iterative and nimblemulti-segment testing andvalidation process • Stable safety-based vehicle architecture • Tightly defined andmaintained operational designdomain (ODD)

13 LYFT 2020 SELF-DRIVING SAFETY REPORT System Safety (continued) vehicle above all other considerations. that thesafety operator shouldtake control. This approach prioritizes thesafe operation of the Additionally, theself-driving system self-monitors andcan provide notification when it deduces braking, steering, throttle, andother controls, aswell asanemergency stop functionality. These disengagement methods includethesafety operator inputtingsignalsinto thevehicle’s or VRUs are at risk. automation system any timethey judge that thesafety of our operations, other humandrivers, They are alsotrained to beconservative, andhave fullauthorityto disengagethedriving safety operators are fullycapable, ready, andtechnologically astute enough to control thevehicle. numerous disengagement methods to maintain safe operations duringself-driving test rides. Our These operators are carefully selected andhighlytrained. Inaddition,our AVs are equippedwith to maintain aconstant state of vigilance. a humansafety operator andco-pilot to ensure complete coverage of allnecessary tasks, aswell as operators to reduce andmitigate risk. When testing onpublicroads we always operate our AVs with At thisstage of development, our systematic safety approach includesthepresence of humansafety bicyclists, scooter riders, transit vehicles, emergency vehicles, andother road users. vehicles withdedicated automated drivingsystems willsafely share theroad withpedestrians, These dynamicODDsare critical asthey represent thehybrid mobilitysystem of thefuture, where on publicroads inchallenging,real-world urbanandsuburbanoperational designdomains(ODD). on-road testing. We contend that asystems approach to autonomous development requires testing We employ asystematic, multi-staged testing program that includessimulation,closedcourse, and A safe, conservative approach to testing the vehicle. system, includingtheself-driving control system andthesafety operators, are always ableto control the basevehicle, for example. Further, we maintain asafety envelope of vehicle performance sothe unknown, uncontrolled, or not-yet-identified risks –suchas system faults intheself-driving system or In practice through iterative testing, our risk-based testing approach continually monitors for (HARA), fault tree analysis (FTA), andfailure modeandeffect analysis (FMEA), we: Using novel processes alongsideestablished tools andprocesses, suchashazard andrisk analysis the industryasawhole. ideas from industryandstakeholders are important asthey represent someof thebest thinkingof and best practices, suchas AVSC, SAE, ISO26262,21448,aswell asothers. These standardized safety case. Lyft incorporates applicable principlesandprocesses from existing industrystandards simulation, anditeratively feed that experience back to inform our safety approach through our are tested andvalidated. We monitor thesafety performance of our system through testing and These safety goalsdrive system, subsystem, andcomponent-level engineeringrequirements, which • Mitigate severity andprobability of occurrence of thesehazards • Assess what level of severity thesehazards present • Analyze thelikelihood that thosehazards might occur • Theorize andidentify possiblehazards

14 LYFT 2020 SELF-DRIVING SAFETY REPORT System Safety (continued) confidential feedback to the reporting employee. in data gathering,safety analysis, andadecisiononhow to address that concern withdirect can raise aflagonany potential safety concern. Thistriggers aseparate review process resulting We employ ananonymous safety concern reporting system whereby any Level 5team member potential mitigations,includingadecisiononwhether thefleet shouldbegrounded. and encouraged to raise aflagwhichtriggers ananalysis to review theneed for and efficacy of concern regarding theway that the Automated DrivingSystem (ADS) isperforming, they are able and resolved aspart of thisongoingprocess. If at any time, any Level 5team membera identifies throughout closedcourse andon-road testing onadailybasis. All issuesare tabulated, analyzed, to identify, qualify, quantify, andaddress any performance anomaliesthat are encountered We continually andcritically analyze data logsfrom testing andfeedback from safety operators closed course testing, andon-road testing segments. re-coded, verified, regression-tested, and validated through a testing process involving simulation, improvement process where issuesare quicklyandsystematically root-caused, resolved, this data extensively. This library of data drives our continuous iteration andrapid software otherwise —to understand their nature androot cause. To do so, we collect, bin,triage, andanalyze While we robustly test our system, we systematically record alldisengagements —intended or 15 LYFT 2020 SELF-DRIVING SAFETY REPORT System Safety (continued) prepare thetechnology for widespread deployment andadoption. challenges, aswell asto develop andshare best practices that willadvance AV safety andhelp to safe AVs. To date, Lyft hasjoinedother AV developers to collaboratively tackle thesesignificant the basisof quantifiable measures of safety andunderpinanindustry-wide systematic approach Such high-level key performance metrics alongwithmore detailed subsystem metrics willform We believe that high-level performance metrics shouldmeet thefollowing criteria: metrics andthetest methodology to measure themisacritical next step. quantified anddemonstrated to consumers, regulators, andthepublicat large. Defining key meaningful performance metrics. This willallow thesafety of self-driving technology to be Lyft believes that organizations developing autonomous vehicles must collaborate to develop Meaningful, consistent autonomous industry metrics performance inagiven ODD performance human-driven with Compareautonomous vehicle and repeatable manner Be measurable inastandardized understandable to thepublic Be meaningfulandreadily

long-term evaluation phases as well asinitialdeployment and Be useful indevelopment phases, and simulation Apply to both physical testing

16 LYFT 2020 SELF-DRIVING SAFETY REPORT Operational Safety mitigation tasks. thorough hiring,onboarding, andcontinuous training of our safety operators to perform thoserisk Lyft’s safety approach includesthepresence of humansafety operators. We prideourselves onour influence our strategy andimplementation of operational safety. At thisstage of development, numerous industries,includingaerospace, military, transit, andother modesof transportation to for AVs. Our approach isto learn from best practices that have proven to beeffective across Maintaining highoperational standards isof utmost importance aswe develop our new technology Safety operator training at Lyft’s East Palo Alto test facility

17 LYFT 2020 SELF-DRIVING SAFETY REPORT Operational Safety (continued) knowledge. Examples include: practical examinations that cover abroad range of policies,procedures, best practices andsystems take. Duringthetraining, they are expected to passaseriesof checkpoints consisting of written and This extensive training ispart of afive-week program that all Lyft safety operators are required to that prepares themto disengageat any moment to managesafety-critical situations. appropriate disengagement methods. Safety operators are trained to bevigilant withamentality normal patterns. This training isexecuted onaclosedcourse to train our operators onquick and series of system failures that are meant to teach operators how to manipulate the AV outside of All operators are further required to undergo fault injectiontraining where training staffa inject high-quality, post-mission feedback. visualization tool, recognize andtake detailed notes on AV behavior, escalate issues,andgive troubleshoot software andhardware issues,read theinformation displayed intheautonomy monitor andcontrol thevehicle asthesafety operator andastheco-pilot; launchsoftware, safety-critical roles: safety operator andco-pilot. To execute theseroles, they are taught how to As part of therigorous onboarding process, alloperators are extensively trained to perform both Onboarding andinitialtraining prioritize andpractice safety above allelse. grading rubricduringtheinterview process anddecisionsare madebasedontheir abilityto extensive, ongoingcriminalbackground checks. Inaddition,allcandidates are heldto astrict candidates must have aproven drivingrecord withnorecent or significant infractions andpass Program andgoesbeyond withour own rigorous operator vetting andselectionprocess. All requirements set forth by theCalifornia Department of Motor Vehicles’ Autonomous Vehicle Tester We employ avery thoughtful anddiligent operator selectionprocess. Our program fullymeets all Selection of Lyft test operators Best Practices for Interactions with thePublic Incident Protocol &Response Process Dynamics Training DriverManual Training& Third-PartyVehicle Self-Driving Systems Knowledge Advanced Driver Assistance Systems (ADAS) Function Awareness

18 LYFT 2020 SELF-DRIVING SAFETY REPORT Operational Safety (continued) self-nominate to beshifted to non-driving missionswithout repercussion. the AVs andencourage themto self-assess andreport their level of fatigue. When tired, they can behavior suchaserratic speedor harsh braking. Inaddition,we manageboth operators’ timein sensors monitor safety operators andco-pilots for signsof distraction andother improper driving combat thisissueandmaintain thesafety of our operators, customers, andthepublic,in-cabin Fatigue anddistracted drivingcontribute significantly to collisions caused by humanerror. To Prevention of fatigue &distracted driving better prepare theteam intheevent of acollision. examinations. Inaddition,they must undergo semi-annualincident response training drillsto expected to passaseriesof quarterly audits consisting of written andin-vehicle practical the software’s features, andany policy or procedure that mayaffect testing. Alloperators are required to keep abreast of andincorporate changesappliedto theOperational DesignDomain, sessions are complete; rather it continues through eachLyft operator’s tenure. All operators are We instillan“always betraining” attitudeinevery operator. Training doesnot stop after initial Continuous training andlearning

19 LYFT 2020 SELF-DRIVING SAFETY REPORT Operational Safety (continued) inspections of hardware, sensors, andequipment to maintain fleet integrity. Alongside operators, Lyft’s fleet technicians perform weekly preventative maintenance andperiodic can beoperated againonpublicroads. of our fleet technicians. Afterward, operators perform asoftware checklist for review before an AV hardware or software malfunctions,are immediately mitigated andescalated withtheassistance The AV’s interior andexterior are carefully inspected. Potential mission-critical issues,suchas Prior to testing inthefield,both the vehicle andits software must passpre-operational checklists. Operational checklists

20 LYFT 2020 SELF-DRIVING SAFETY REPORT (ODD) Operational DesignDomain rideshare business. human-based rideshare platform. We dothisby leveraging our extensive experience in the only ontheODDsrequired to develop andoperate abusiness-relevant, hybrid self-driving and In addition,adistinguishing factor of our approach to self-driving isthat our technology focuses safety operators onthisnew ODDbefore executing on publicroads. completion of thorough review andassessment, includingasafety andsoftware sign-off. We train our We execute specificadditions to thisODDasour technology development warrants, but onlyafter emergency vehicles, andother road users. dedicated vehicles willsafely share theroad withpedestrians,bicyclists, scooter riders, transit vehicles, automation system inenvironments that represent themobilitysystem of thefuture, where ADS (ODD). We chosethis dynamicenvironment because we believe it iscritical to test our driving We operate inachallengingreal-world urban/suburban publicroad operational designdomain using our system safety engineeringprocess. system meets our performance thresholds, under appropriate environments andconditions, defined At thistime, we deploy self-driving vehicles onlywithsafety operators inwell-defined ODDswhere the given automated drivingsystem or feature thereof isdesignedto function. Operational Design Domain: Framework andLexicon describesthespecific conditions undera which The operational designdomain(ODD) ascharacterized by AVSC Best Practice for Describing an

21 LYFT 2020 SELF-DRIVING SAFETY REPORT and Response Object andEvent Detection high-definition (HD) maps to augment thesensor suite. starting withthedesignandlayout of our sensor suite. Currently, we addour custom-built We enablehighly-capable OEDRby incorporating multiplelayers of data collection andanalysis, to evolve significantly over thedevelopment period of the vehicle. effectiveness of the AV to perform this task are critical for operation, andthis capability is expected cones, road debris,etc.) that are ontheroadway for any reason. The ability, consistency, and traffic control features andmiscellaneous static anddynamicobjects (e.g. roadsidefurniture, traffic users, includingalltypesof cars, trucks, buses,andvulnerable road users, aswell asroadway and appropriate level of response. AVs must beableto recognize andappropriately react to other road circumstance that isrelevant to theimmediate drivingtask, aswell astheimplementation of the Object andevent detection andresponse (OEDR) refers to the detection by thedriver or ADS of any

22 LYFT 2020 SELF-DRIVING SAFETY REPORT OEDR The Eyes of Our Cars perception pipeline. other supportingsensors to provide aconsistent view of theworld, guidingour vehicle’s information for detected objects. Together, theseinstruments are carefully calibrated alongwith that helpaccurately detect andclassifyobjects. And radars provide reliable distance andspeed world around thevehicle andhighlight potential objects andevents. Cameras generate images at any given time. Light detection andranging (LiDAR) sensors capture a3Drepresentation of the Our AVs are equippedwithafullsensor suite that allows for thedetection of objects andevents Our sensor suite previous drives, structured into aseriesof “layers”: navigation. We usepubliclyavailable information for sources, aswell assensor data collected on We precompute several categories of historical road information intheform of HDmapsto guide A second pair of eyes: HDmaps (continued) Geometric Layer Real-Time Layer Semantic Layer Base Layer Prior Layer

23 LYFT 2020 SELF-DRIVING SAFETY REPORT OEDR test runto enableadetailed comparison between models. rigorously tested before every singlerelease, and anextensive set of metrics isproduced from each tracked. All suchcharacterized data collections, or models,built onour perception pipelineare with avariety of other static anddynamicobjects, are constantly beingdetected, classified,and fused to produce afinalinterpretation of agiven object. Other vehicles, VRUs, traffic lights, along eyes usingarobust multi-modal,fault-tolerant system. The data collected from multiple sensors is The goalof Lyft’s perception pipelineisto achieve performance beyond thecapability of human and reacting to VRUs, suchaspedestrians,bicyclists, scooter riders andother micro-mobility users. The complexity of thereal world posesmany challengesto perception, especiallyaround detecting Our perception pipeline between lanes. traffic control elements, and connectivity A as acompressed point cloud. location of thevehicle (localization), composed static objects that aidindetermining theprecise A junctions, andhigh-level traffic control elements. A

semantic layer whichincludeslanegeometry, geometric layer whichincludesarange of base layer whichincludesroad names,road (continued)

areas that have fullyvalidated HDmaps. technology, we operate our AVs onlyin reflect current ODDs. Withour current Each of theselayers isregularly updated to temporary features like work zones. about current road or traffic conditions, or A observed whiledriving. statistical information about dynamicobstacles A

real-time layer prior layer whichincludesaggregates of prior which includesinformation

24 LYFT 2020 SELF-DRIVING SAFETY REPORT The Brain of Our Cars for steering, brake, andthrottle commands. selected. These instructions are thentransformed by thesystem controller into a set of instructions trajectories are generated, andthenthe most optimal pathforward to satisfy theseconstraints is After creating aset of constraints to follow alongaparticular path,alarge number of possible comfortable andnatural ride. “cut-in” scenario), the AV slows down in away that mimicshuman drivers, resulting inamore another vehicle abruptly enters thelaneinfront of the AV at aless-than-desirable distance (i.e. a speed andbehavior of our AVs based onlarge scale observation of humandrivingdata: When type to enablethevehicle to maintain asafe andlegaldistance at alltimes. We also adjust the For example, whenmaneuvering around objects, spatialbuffers are appliedbasedon theobject high abilityto generalize for ambiguoussituations. system hasboth highprecision —required for maintaining safety andadheringto thelaw—and of machine-learnedsystems, expert systems andhumandrivingdata to ensure theplanning we consider comfort for both passengers andexternal parties. We dothisby usingacombination foremost we ensure the AV’s maneuvers are safe; second we ensure that they are legal; andthird When determining themost appropriate behavior to implement, thefollowing logicisused:first and create andtrack multiplehypotheses for thispedestrian’s location. travel, thesystem would anticipate where they willbeprecisely at somepoint inthefuture, or would context. For example, based onapedestrian’s distance to anearby crosswalk andtheir direction of perception system to determine themost likely pathsthat anobject could take basedonthecurrent the typeof road user, beit another vehicle or a VRU. It thenusesinformation from theHDmapsand For eachobject inthevehicle’s surroundings, thesystem calculates multiplehypotheses basedon numerous timesper second. The planner uses thisinformation to: Our planningsystem ingests inputs from theperception system, localization system, andHDmaps The prediction andplanningsystem Choose anoptimal trajectory for thevehicle to take Determine themost appropriate behavior that shouldbeapplied Predict how thevehicle’s surroundings willevolve over time

25 LYFT 2020 SELF-DRIVING SAFETY REPORT OEDR The Knowledge of Our Cars that improve our test validation coverage. past drivingexperiences to helpguideusonthecreation of new synthetic, yet realistic scenarios, feature willhave asafe, legal,andcomfortable response inthetarget ODD. Additionally, we use scenarios andrerun theself-driving software withthesamesensor inputs to ascertain that anew and verify new software and hardware features. For example, we are ableto minerelevant the scenarios andmilesthat our autonomous vehicle fleet have accrued over the years to validate Human drivers rely onprior drivingexperiences to interpret theworld, andsodo AVs. At Lyft, we use (continued)

26 LYFT 2020 SELF-DRIVING SAFETY REPORT Minimal Risk Condition Fallback - degradation inthesystem. fallback strategy where we can choosebetween different actions dependingonthelevel of without theneedfor humanintervention. This willalsoallow usto implement amore sophisticated power, andactuationthat are capable of handlingfailures andbringing thevehicle to asafe state a fault-tolerant system architecture. This architecture could includeredundant sensors, compute, For our future-generation autonomous vehicle platform, we are actively working onthedesignof vehicle’s collision mitigationsystem remains operational throughout allour testing activities. well asemergency stop functionality. To further support our operators we ensure that thebase disengagement methods, includingthevehicle’s braking, steering, throttle, andother controls, as judge it may be necessary. As mentioned previously, operators have fullaccess to multiple disengage theself-driving system to quicklyregain fullhuman control of thevehicle any timethey Again, it isimportant to note that our operators are trained to beconservative andhave authorityto are ableto maintain vehicle control, if needed. the motion of our AVs iscontrolled withinasafety envelope, or buffer, whereby our safety operators and simultaneously inform our operators to resume fullmanualcontrol of thevehicle. Inaddition, 100 timesevery second. Intheevent of adetected failure, thesystem can automatically disengage maintain thesafe operation of our AVs. Our self-driving system alsomonitors safety-critical aspects As discussedabove, we currently rely onour thoroughly trained operators as afail-safe to ultimately

27 LYFT 2020 SELF-DRIVING SAFETY REPORT Validation Methods to validation rests onfour pillars: critical to safely deploying autonomous technology. Lyft’s approach As describedintheSystem Safety sectionabove, AV validation is re-validation a one-time activity, requiring continuous feedback loopsand Feedback Loops: Validation isanongoingiterative process, not practices (such as ISO26262) isanenabler for AV validation Industry Collaboration: Following andexceeding industrybest prioritization allows safety assessment inrealistic conditions RiskPragmatic Assessment: Quantitative risk-based and operational activities Safety First: Safety isfoundational for alldevelopment, testing,

28 Validation Methods (continued)

We leverage the “V-Model” approach to verification and validation defined in ISO26262 and execute our software development within this context through iterative development cycles.

Closed Loop Validation

SW & FW Validation Development

AV Scenarios/ Vehicle Track, Road System Skills (L0) (as necessary & per release) Test Dev #1 (add func. #1) est

e and t Platform/Stack HIL, Simulation Integration Test iterationNext at tegr Definition (L1) (~Daily to weekly) (Platform In sub-assy/stack) Dev #2 (add func. #2) Adjust & Sub-system HIL, Sim, Cloud Integration Test track new Contracts (L2) (~Daily) (Sub-system) Integrate and test features

Module/Service HIL, Sim, Module Dev #n Requirements Cloud Test Implement (add func. #n) (L3) changes (~Daily) In tegr at e and t Component/Unit Bench No Release est Requirements Cloud Unit Test (L4) Review

Yes Accept

Design, Code Build

Ultimately, before widespread deployment of AVs, every function must be designed and tested through a clearly defined test program that bothverifies that the function works as intended and validates that it meets stakeholder needs. To accomplish that, it is critical to properly specify the intended function to accomplish robust verification. Our process specifies a set of basic competencies, starting with those defined byNHTSA and CA-PATH and augmented with scenario catalogs. Detailed scenarios are specified within those catalogs and are fully traceable to these basic competencies.

To that end, we take a layered approach to verification and validation of the ADS that includes:

• Verifying statistical autonomy performance through simulation • Ensuring basic safety competencies are demonstrated for every software update • Refining simulation performance with structured testing and public road testing 29 LYFT 2020 SELF-DRIVING SAFETY REPORT Validation Methods (continued) • Publicroads withtrained safety operators includingour private test facility inEast Palo Alto, CA andother closedcourse locations • Structured testing of AV features andend-to-end behavioral competencies at test tracks, test data • Parametric simulationwithenvironment calibration andvalidation using real-world • Hardware-in-the-loop environments for sub-system testing • Software-in-the-loop environments for replay andsystem andcomponent testing hardware, andintegrated system testing, including: Finally, we maintain arichset of environments for software,

30 LYFT 2020 SELF-DRIVING SAFETY REPORT Human Machine Interface (HMI) Human MachineInterface HMI from thesafety operator perspective stop functionality. primary vehicle’s braking, steering, throttle, andother controls aswell asemergency autonomy can betriggered. For example, operators can prompt adisengagement through the As noted above, safety operators have awiderange of surfaces by which disengagement from support functions. notifications to inform operators andriders about tripupdates, AV system status, andcustomer transition to manualcontrol of thevehicle. The secondary audiosystem provides awiderange of element informs operators of any disengagement from autonomous control, allowing smooth In additionto thevisualHMIelements, Lyft’s AVs are outfitted withtwo layers of audioHMI. One and system control, whennecessary. surroundings, intent, andsystem health. The co-pilot’s HMIalsoprovides amethod of note-taking is amore comprehensive visualinterface that provides greater detail about thevehicle status, robust, andeasily-interpreted manner to minimize distraction, asshown above. The co-pilot’s HMI For instance, thedriver-facing visualHMIelement displays thestate of the AV system inasimple, allowing themto take over thevehicle asneededintheevent of asystem disengagement. information at theright timeto keep safety operators abreast of critical AV system performance, reliability. Using both visualandaudioelements, thegoalof our HMIs isto deliver theright Lyft’s on-board humanmachineinterface (HMI)isdesignedfor simplicity, robustness, andhigh

31 LYFT 2020 SELF-DRIVING SAFETY REPORT Human MachineInterface (continued) support requests that riders mayhave. about therider, their current ride, and the AV system status to provide timelyresolution to any any timeduringaride. These representatives have acomprehensive displaywithinformation Additionally, allpassengers inthevehicle have immediate access to remote assistance agents at information intended to convey how the AV isableto safely interact withtheworld around it. along theroute andstatus of critical safety systems. This displayalsoprovides riders with Once insidethevehicle, allriders have access to ride-critical information, includingtheir location experience, suchasthenumber of riders thevehicle supports. Lyft appimmediately provides therider withadditionaleducation related to thesafety of their components to share necessary safety information. When arider requests aself-driving ride, the touch point withtheself-driving vehicle, andit works hand-in-handwithon-board HMI design passenger HMIs that enableriders to feel safe andcomfortable. The Lyft appisriders’ first As acustomer service andsafety-oriented company, we leverage user experience research to HMI from thepassenger perspective

32 LYFT 2020 SELF-DRIVING SAFETY REPORT Cybersecurity connected system. therefore beprotected against suchanattack to protect other vehicles andassets inthe for anadversary to attack thecloudbackend that managesthe fleet. Thecloudbackend must needs to becarefully controlled andmonitored. Finally, anindividual AV maybeanentry point integrity andprovenance of recorded data usedto generate machine-learningmodelsandmaps Defending theconfidentiality of sensitive data, both in transit andat rest, isalsoessential. The Keeping thevehicle safe from avariety of potential threats isof paramount importance. AVs utilize andrecord avariety of sensor data that hassignificant security and privacy implications. but alsothevehicle’s larger connected system. have beencompromised. Accordingly, our digital securitygoalscover not onlythe vehicle’s safety The safety of avehicle system cannot befullymaintained if its security, or thesystems it relies on, Lyft advocates that astrong approach to cybersecurity isessential to asafe autonomous program.

33 LYFT 2020 SELF-DRIVING SAFETY REPORT Cybersecurity Lyft’s cybersecurity standards. level andtested through eachlayer andat various integration levels to ensure alignment with these product requirements. These designsare thenimplemented at theindividualcomponent and thendevelop detailed engineeringdesignsthat spantheentire connected system to meet defenses. Basedonthisprioritization, we develop theproduct requirements around theseassets, Following thisapproach, we identify adversarial risks andprioritize critical assets withappropriate followed by theIT industry, aswell asguidance provided by NHTSA We take amethodical approach to securitydesign,basedoncybersecurity best practices Our methodology Compute (continued) Implementation Network Functions, Interfaces, Roles, Requirements Access Rights Defensible Product Assets Goals ...

Backend

andAuto-ISAC. Verificaiton Ops

34 LYFT 2020 SELF-DRIVING SAFETY REPORT Cybersecurity • Data Protection thebasevehicle backend to the AV system. dynamicdata duringupdates, repairs, andoperation. Authenticating various directives issuedby • avariety of intruders usingamulti-layered approach. • We are pursuing asecuritydesignthat stands onfive pillars, including: Security pillars • Incident Response generated andconsumed incloudenvironments. • CloudSecurity-Securingthecloudbackend to protect theintegrity of thevarious assets eavesdropping. intheconnected system, aswell asthecontinuously evolving securitylandscape.

Authentication - Authenticating every piece of hardware andsoftware, aswell asstatic and Network Security-Securingthevarious networks, both insideandoutside the AVs against (continued) - Protecting data captured by thevehicle against tampering and - Monitoring andresponding inreal-time to any anomaliesdetected Incident Response Cloud Security Data Protection Authentication Network Security

35 LYFT 2020 SELF-DRIVING SAFETY REPORT Crashworthiness attempt to reduce thepotential for VRU injury incase of contact. the AV sensor suite to provide rounded, minimally-protruding, andcontact-friendly surfaces inan Additionally, since VRUs can andeventually willimpact the AV at nofault of the AV, we strive to design provides ahighpotential to detect andreact to VRUs whenpossibleto prevent or mitigate acollision. constant view of visibleandrelevant road users, including VRUs, aspart of theoverall road scene. This get distracted, sleepy, or otherwise inattentive. Our AV sensor suite isdesignedto provide adirect and over humandrivers whenit comes to detecting vulnerable road users: they are always alert anddonot and protects thesafety of other road users. While nosensor isperfect, AVs have apotential advantage In additionto thesafety of our passengers, Lyft is committed to designingan AV system that considers the basevehicle remains fullyoperational. testing where appropriate to verify thedesign. We alsoensure that thecrash avoidance technology of the basevehicle’s structure andrestraint systems are maintained whileperforming simulationand that could affect vehicle structure andcrashworthiness, we carefully engineer modifications toensure to not affect their operation. In cases where additionalhardware and systems equipment isadded maintaining thebasevehicle’s structure. We donot modifytherestraints andairbags,are diligent manufacturer (OEM). We purposelyminimize any modifications to OEMsafety systems, including on significant engineeringand testing accomplishments of thebase vehicle by theoriginalequipment hardware. The crashworthiness, occupant protection, andcompliance of thisapproach rely heavily capable traditional passenger vehicle that maintains well-understood seatingarrangements and During our current phaseof AV development, our platform isbased onmodifications to ahighly- road users. well-established safety approaches for AV occupants; and(2)innovative considerations for vulnerable focus isinmitigatingthefrequency andtheimpact severity of crashes whileproviding: (1)reliable and be involved inincidents includingbeingstruck by other vehicles andother road users. Therefore, Lyft’s the potential to significantly reduce thenumber of crashes, it willnever avoid all collisions, andit willstill developed andproven injuryprotection technology intheevent of acrash. While AV technology has Lyft believes that occupants of AVs, just like allother passenger vehicles, shouldhave access to well- Safety Cage Crumple Zone Typical deformation to rear structure inFMVSS crash test (left) andthesimulation(right) Safety Cage Crumple Zone

36 LYFT 2020 SELF-DRIVING SAFETY REPORT Post Crash ADS Behavior control of thebaseOEMvehicle platform. ADS willbringthevehicle to asafe-stopped state, engageemergency flashers, anddisengageits vehicle, suchashigh-voltage runs,are clearlymarked for first responders. Infuture generations, our base vehicle (e.g. power systems) inanunmodifiedstate. Additionally, allmodifications tothebase underlying basevehicle intheevent of acrash. For first responders, the ADSisolationleaves the Lyft’s current Automated DrivingSystem (ADS) isautomatically isolated from controlling the applicable) incompletion of post-crash protocols. rapid response teams to thescene to assist theoperators andany impacted third-party (if Upon receipt of notification that anincident hasoccurred, we immediately dispatch one of our AV Operators andthird-party occupants (if applicable) protocol to managesuchincidents. incidents onaminute-by-minute basis,operating against thecompany’s proprietary response world-class Customer Experience and Trust team across theglobe that manageandtriage While we take every reasonable step to prevent vehicle collisions, they are inevitable. Lyft hasa notifying law enforcement intheevent of injury. every operator must befamiliar withLyft’s incident response andescalation process, including We train our operators to approach collisions withasafety-first mindset and attitude. Accordingly, Incident protocol

37 LYFT 2020 SELF-DRIVING SAFETY REPORT Data Recording ADS to minimize therecurrence of suchanevent. The logshelpusanalyze anincident if andwhenit occurs, andmake any updates needed to the • How the basevehicle responded to thesecommands • What the AV commanded thebasevehicle to do • How the AV plannedto interact withtheperceived world • What the AV perceived from thissensor data • What raw sensor data was available to thesystem The goalof theselogsisto helpdetermine: to make adetermination of thedecisionsthat the AV madegiven thesurroundings it encountered. executed, andvehicle actuator responses. Intheevent of anincident, theselogswillbeanalyzed including what the AV’s sensors see, objects detected andtracked, maneuvers plannedand vehicle isinautonomous mode. It iscapable of loggingcomplete ADS input andoutput parameters, Lyft’s self-driving system includesadata loggingsystem that isoperational at alltimeswhenthe

38 LYFT 2020 SELF-DRIVING SAFETY REPORT Federal, State, andLocal Laws our program. Lyft looks forward to theopportunity to work withother stakeholders aswe further expand traditional auto manufacturers. technology-neutral policy solutions,ensuringalevel playingfield for allparticipants, not just engage inactive discussionswithgovernmental stakeholders to advocate for theadoption of To promote innovation andenable AV technology to reach its fullpotential, Lyft willcontinue to leaders like Lyft increating theappropriate environment for thesafe adoption of AV technology. federal, state, andlocal policymakers to evaluate current safety standards andto work withindustry As theregulatory requirements for AVs become more defined, we applaud effortsby made

39 Conclusion

Safety is at the heart of Lyft’s approach to autonomous vehicle technology development and deployment. Beginning with our core safety principles and focus on our customers, down to our rigorous engineering and testing, driver training and consumer education processes, the safety of our riders and our communities guides our decision making every step of the way. This will never stop as we strive to realize a future of transportation that is built around people, and not cars.

LYFT 2020 SELF-DRIVING SAFETY REPORT SAFETY SELF-DRIVING 2020 LYFT Lyft’s AV safety program is guided by our mission to improve people’s lives with the world’s best transportation, and is based on the core principles of improving autonomous technology, guarding the safety of all road users, quantifying safety through metrics, collaborating with others, and most importantly, maintaining the trust of our users and all stakeholders. We employ a strategic customer-focused systems safety approach, including a conservative and diligent validation and testing regime focused on operational safety and quantified objectively by meaningful metrics. We employ rigorous validation and verification methodologies for hardware, software, and integrated systems, and well-executed HMI, cybersecurity, and data systems. We also mitigate risks by ensuring proper functionality of crashworthiness, crash avoidance, and data recording technologies. We collaborate with other developers, regulators, and stakeholders to improve the technology and develop appropriate rules, regulations, and laws.

With each iteration of Lyft’s AVs, our ultimate goal is to produce technology that can improve transportation and reduce collisions caused by human error and limit their severity. Though the task is challenging, by collaborating with industry partners and regulators, it is surmountable. Together, we can realize a transportation future that increases safety, mobility, and accessibility for all.

40 LYFT 2020 SELF-DRIVING SAFETY REPORT Legal Disclaimer the forward-looking statements. or occur, andactualresults, events or circumstances could differ materially from thosedescribedin the results, events andcircumstances reflected inthe forward-looking statements willbe achieved forward-looking statements contained inthissubmissionandCEO letter. We cannot assure you that not possiblefor usto predict allrisks anduncertainties that could have animpact onthe and rapidly changingenvironment. New risks anduncertainties emerge from time to timeandit is Quarterly Report onForm 10-QfiledonMay8,2020. Moreover, we operate ina very competitive including thosedescribedinthesectiontitled“Risk Factors” andelsewhere intheCompany’s described intheseforward-looking statements issubject to risks, uncertainties andother factors, business, financial condition, results of operations andprospects. Theoutcome of the events expectations andprojections about future events andtrends that we believe mayaffect our looking statements contained inthissubmissionandletter from theCEO primarilyonour current upon forward-looking statements aspredictions of future events. We have basedtheforward- terms or expressions that concern our expectations, strategy, plansor intentions. You shouldnot rely “believe,” “estimate,” “predict,” “potential” or “continue” or thenegative of thesewords or other similar “may,” “will,” “should,” “expect,” “plan,” “anticipate,” “could,” “intend,” “target,” “project,” “contemplate,” some cases, you can identify forward-looking statements because they contain words suchas statements generally relate to future events or our future financialor operating performance. In forward-looking statements, whichinvolve substantial risks anduncertainties. Forward-looking This submission,includingbut not limited to theletter from CEO Logan Green, contains Lyft, Inc.’s

41 LYFT 2020 SELF-DRIVING SAFETY REPORT Glossary of TermsGlossary VSSA: VRU: SAE: PAVE: OEM: OEDR: ODD: NHTSA: LiDAR: ISO: HMI: HD: HARA: FTA: FMEA: AVSC: Automated Vehicle Safety Consortium AV: Auto-ISAC: ADS: ADAS: Autonomous Vehicle High-Definition International Organization for Standardization Fault Tree Analysis Society of Automotive Engineers Vulnerable Road User (e.g. pedestrians,bicyclists, andscooter riders) Human MachineInterface Automated DrivingSystem Operational DesignDomain Original Equipment Manufacturer Partners for Automated Vehicle Education Voluntary Safety Self-Assessment Advanced Driver Assistance Systems Hazard andRisk Analysis Failure ModeandEffect Analysis Object andEvent Detection andResponse Light Detection andRanging National Highway Traffic Safety Administration Automotive Information Sharing& Analysis Center 42 LYFT 2020 SELF-DRIVING SAFETY REPORT SAFETY SELF-DRIVING 2020 LYFT

lyft.com/self-driving