20171016-匯豐銀行-全球-科技行業(yè)-自動(dòng)駕駛通向ai之路的起點(diǎn)-hsbc-nomadic_investor_autonomous_vehiclesthe_beginning_of_the_ai_road

1、16 October 2017Autonomous vehicles (AVs) are set to mark the beginning of the autonomous ageThe transition to AVs could be faster than many expect; we explore the lessons learnt so far from the migration to electricWe look at the core AV ecosystem and infrastructure, and highlight companies exposed

2、to this likely new megatrendDavey Jose* Thematic Strategist HSBC Bank +44 20 7991 1489Ashim Paun, CAIA Climate Change Strategist HSBC Bank plc +44 20 7992 3591* Employed by a non-US affiliate of HSBC Securities (USA) Inc, and is not registered/ qualified pu

3、rsuant to FINRA regulationsThe autonomous revolutionWe believe that today society is on the cusp of the autonomous age where machines operate physical world objects that previously required human brainpower and manual dexterity, all through the power of modern Artificial Intelligence (AI), all by th

4、emselves and without supervision. The first big visually noticeable application of this trend is likely to be AVs because of the volume of key industry stakeholders already involved, readying the technology for mass market commercialisation on a global scale (see Global autos Disruptive threats: Car

5、makers versus new entrants, 19 September 2017).In this report we build on our previous thematic work (see Transport shock: autonomous today, virtual tomorrow, 19 October 2016) by looking at the ingredientsof autonomous transportation, drawing parallels and lessons from another disruptive force withi

6、n transport, the evolution of electric vehicles (EVs).Adoption of AVs could be faster than expectedRapid modern day advances in AI technology suggest that this new method of transportation could be adopted faster than many expect. Unlike the adoption of EVs, where progress has been limited (up until

7、 very recently) by battery capacity and associated high costs, the adoption of AVs is unlikely to face the same restrictions.This is because the pace of advancement in AVs is governed by computertechnology (given Moores Law) and is likely to be much more rapid.Where to look for AI exposureWe believe

8、 that now is the time for investors to understand the wider implications from AV rollout and also the new ecosystem required to support its growth over the coming years. Our Asia technology team has published a companion note called Artificial Intelligence: Chips with everything, 16 October 2017, in

9、 which they take a deep-dive into the hardware required for AI and hence AVs. We highlight four themes within this AV ecosystem: computer vision, AV brain, connectivity, and automobile hardware (page 2).MiFID II ResearchIs your access agreed?CONTACT us todayIssuer of report: HSBC Bank plcDisclosures

10、 & DisclaimerThis report must be read with the disclosures and the analyst certifications in the Disclosure appendix, and with the Disclaimer, which forms part of it.View HSBC Global Research at:Nomadic Investor updateAutonomous vehicles: the beginning of the AI roadTHEMA

11、TICGLOBALTHEMATIC GLOBAL16 October 2017Autonomous transportation ecosystem and infrastructureAutonomous vehicle (AV) brain:High performance computer processors andAI softwareAutomobile hardware:Computer vision: Cameras, radar and LiDAR (Light Detection and Ranging)Connectivity: Enabling real-time da

12、ta exchange within AV systemSensors convert real-world visual information into data AI can understandFusion of hardware and software creates AI brain to process and understand visual dataAVs are essentially datacentres on wheels and communicate between other AVs and infrastructureAuto OEMs and suppl

13、iers can partner with new AV tech playersSensor ecosystem:3D Lumentum, Himax, Infineon, LG InnotekMotion Samsung LSIRadar Infineon, NXP, STMicro, Tung ThihLiDAR Velodyne, Delphi, QuanergyImage Sony, Samsung system LSI, Omnivision, On Semiconductor, PanasonicProcessing ecosystem:Autonomous driving pl

14、atform solution nVidia (Drive PX2), Intel (GO). Qualcomm (Snapdragon S820Am)CPU (central processing unit)nVidia, Intel, QualcommNPU (neural processing unit) Huawei (NPU in Krin AP), Apple (A11), Google (TPU), Qualcomm (Zeroth), Nvidia (Drive PX2), IBM (TrueNorth), Intel (Mobileye), AMD (radeon MI/RX

15、 Vega), Samsung, Nepes (NM500)Memory Samsung, SK Hynix, Micron, Western Digital, ToshibaGeneral and auto AI framework TensorFlow, Caffe2, Theano, Torch, MXNet, Deeplearning4j. Keras/CNTK, BigDL/Open, NEO with OpenPilot (Comma.ai)Connectivity ecosystem:5G modern development Qualcomm (Snapdragon X50),

16、 Intel (5G Goldbridge), Samsung (5G RFIC), MediatekServer/datacentre HP, Lenovo, Quanta, IBM, Inspur, Oracle, Sugon, ChinaCacheCloud computing:Public cloud AT&T, BT, A, Telefonica, Cleversafe, Swisscom, SKT, Olleh KT, Softbank, Rackspace, VerizonPrivate cloud Openstack, Citrix, VMware, Micr

17、osoft, Redhat, HPHyperscale cloud Amazon, Microsoft Azure, SoftlayerAutomotive ecosystem:OEM Hyundai, BMW, GM, Benz, Honda, Volvo, AudiAutomotive semi/components Continental, Bosch, Delphi, Honeywell, Valeo, Hyundai, Samsung, LG Innotek, SEMCO, Largan, Chin-Poon Industrial Renesas, Texas InstrumentI

18、CT giants Google/Waymo, Baidu, nVidia, DeNA, SB Drive, Intel, Naver LabsMobility-as-service Uber,Lyft, Zipcar, Otto, Didig, OlaNew vehicle Tesla, BYD, Ninebot, Stealth Source: HSBC Research 2THEMATIC GLOBAL16 October 2017Introduction S Sell the house. Sell the car. Sell the kids. Find someone else.

19、Forget it. Im never coming back. Forget it.Apocalypse Now (1979)Riffing off a line from the 1979 motion picture, Apocalypse Now, directed by Francis Ford Coppola, we dont recommend one necessarily to sell their kids or other worldly assets. However, in the near future, it might be possible to sell y

20、our human-driven automobile and purchase (or ride-hail) a new kind of vehicle, one that makes your life easier, cheaper and safer: an AI-infused autonomous personal transportation vehicle. The idea is that once one embarks on the road to autonomous, one might never want to go back.Sell the car. Go a

21、utonomous.Even before then, the world of personal transportation is already going through substantial disruption. Today, vehicles are migrating from the 100 plus year-old technology of the internal combustion engine (ICE) and transitioning towards modern day electrification. After electric vehicles

22、(EVs), the next step, as we outlined in a previous thematic report, Transport shock: autonomous today, virtual tomorrow (19 October 2016), is widely suggested to be autonomy, facilitated by artificial intelligence.In that note we looked at the implications of autonomous transportation for jobs, leis

23、ure, consumption, infrastructure and how the changing nature of young and old demographics could be supportive of this new autonomous vehicle (AV) landscape. More recently, Horst Schneider, HSBCs head of autos equity research, together with Henning Cosman, published a deep-dive report called Global

24、autos Disruptive threats: Carmakers versus new entrants (19 September 2017). In that report, they outline that carmakers can cope with challenges from EVs but they face more significant disruption from self-driving cars.Transport shock is already hereMoreover, recent media coverage has highlighted t

25、hat this autonomous future might be closer than one thinks. It has been suggested that Googles spin-off Waymo may be readying its own fleet of fully autonomous self-driving cars for public consumption, on the streets of Phoenix (Arizona), as soon this autumn.1 If this materialises, it could fuel and

26、 accelerate the AVcompetition, marking a significant inflection point for the future of transportation.Autonomous todayThe primary difference between AVs and EVs is that EV is to do with energy storage (hence chemistry) and AVs build out from computer technologies derived from Moores Law (computatio

27、nal ability essentially doubles but halves in cost every 18-24 months and has been driving our microprocessor fuelled technological advances over the last 50 years). So even though AV and EVs are both transport technologies, they differ in their foundational technologies (energy and arguably the law

28、s of thermodynamics vs computational processing).Nevertheless, even taking these differences into account, we believe the transition we have seen so far to EVs can provide some useful indicators and lessons on the likely road to fullyautonomous vehicles (Table 1).The difference between AVs and EVs1

29、Fully driverless cars could be months away, Ars Technica, October 2017.3THEMATIC GLOBAL16 October 2017Table 1. Autonomous read-across and open questions (vs EV lessons learnt)ThemeAVvs. EV2ConvenienceProductivity time gained from not driving. Also from potential fleet traffic efficiencies.Charging t

30、ime is bottleneck. However, this duration could fall for a full charge with technological improvements.4Climate changeRoll-out of ride-hailing AV has unknown climate change implications today. Some suggest fewer vehicles on road due to ride-hailing AVs, others suggest easier access to AVs imply more

31、 vehicle miles travelled. Datacentres powering AV ecosystem could be green.Emission regulations in favour of EV.6EM-DM bridgeAI AVs may be able to learn more on the sometimesRapidly developing EM nation cities have anchaotic streets of EMs than DMs. Some EMs may be able incentive to shift to EV to m

32、ake them moreto pass AV-friendly regulations faster than DMs.pleasant cities.State-sponsored AV data sharing in some EM nations, eg China, could aid domestic AI AV systems to leapfrog their DM AV counterparts.8Technology & infrastructureADAS to level 5 autonomous require improvements and price commo

33、ditisation in:Battery storage and charging are improving. Lots of charging stations in city and rural areas(a) Computer vision: sensors and components like cameras, are required to reduce range anxiety. Is there a radar and LiDAR (light imagine, detection and ranging). difference between DM and EM (

34、eg China)?(b) AV brain: combination of high compute processors (eg CPUs, GPUs, TPUs, NPUs central, graphical, tensor and neural processing units) and AI software.(c) Connectivity and networks to make AV ecosystem communicate in real-time and have vehicle-to-everything infrastructure (V2X).10Maintena

35、nce & ownershipOTA (over-the-air) software (s/w) updates, eg iPhone/Android mobile phones.EV likely to be highly software oriented, so also over-the-air (OTA) updates.Likely to reduce vehicle ownership within an AV sharing economy (eg ride-hailing).Reduce ownership and sales of ICE, once price falls

36、.AI AVs could use advanced self-diagnostics for maintenance, ultimately leading to robots fixing robots, taking human labour out of the loop in the day-to-day operation of AV fleets, in the consumer, business and industrial space.Generally EVs have fewer parts so easier to maintain.Source: HSBC esti

37、mates49Suppliers & value Large sunk costs - with unknown payoff until fully AV.Large sunk costs for R&D and production. Pay- chainHowever, lower levels of autonomy (0 to 3) may helpoff suggested to be within reach, more thanease income stream.previous times.Full value chain unknown as technology is

38、still inValue chain a known quantity. Key today are development and testing phase. Lack of legacy maybe an volume and pricing.advantage to new AV players.7Timing & transition Timing is tricky but many AV participants suggest earlyRepeated inflection point has not come to pass. 2020s to all the way t

39、o 2035 for fully AV.Is it different this time?Iterative improvements from ADAS to level 5 autonomyMight impact second-hand ICE vehicle prices might impact second-hand AV-less ICE/EV vehicles.and inventory.5Social inclusivity Likely to increase independency for the elderly andToday the waiting time i

40、nvolved with charging immobile and save the state and families both time andmight be more tiring for the elderly than the money related to in situ care provision.faster ICE refuelling equivalent. In the futurecharging could be faster.3Regulation &Safety is crucial. Early AV accidents could increaseG

41、overnments globally support EV (electric safetyregulations and stifle adoption. On the flip side, good AV vehicle) in relation to climate change andcould lead to regulation to encourage AV adoption.cleaner cities to reduce carbon emissions.Might an increase in travelling safety due to AVs fosterVari

42、ous EV tax credits available globally. pro-AV regulation like AV only lanes, taxing humandrivers or tax breaks?1Pricing systemsAre extra electronic component costs easier tojustify byIs larger battery (vs ICE, internal combustion autonomous convenience gained? Component costs likely to engine) cost

43、justified for consumer? Prices likely increase from level 1 to 5 but commoditise over time.to decrease with time though.Pricing systems from outright ownership, ride-hailing to open-source AV (autonomous vehicle) platforms.THEMATIC GLOBAL16 October 2017Autonomous now but what can AVs learn from EVs?

44、We attempt to make some read-across assumptions for AVs (versus EV lessons learnt),following the below sub-themes:Pricing systems and convenience offeredOne of the crucial bottlenecks for EV adoption is pricing, which depends on battery cost. As battery technology improves and production volume/capa

45、city increases, EVs naturally become affordable. See Asia EV and Battery: how China is helping to crack the cost conundrum, 6 April 2016). We outline three pricing models that could play a part in AV adoption: outright ownership, ride-hailing/sharing AVs (RAVs) and open-source (including crowd-sourc

46、ed) platforms.Another bottleneck for EVs is the question of convenience, for example today it generally takes longer to charge an EV than re-fuel an ICE vehicle. We suggest the time saved when in an AV could offer increased productivity within society.ESG and regulationsRegulations have been support

47、ive of the development of EVs, in relation to the climate change issues raised by ICE vehicles. We believe regulations could also be supportive of AV development and adoption, through its increased safety offered on roads. At the moment there are several moving parts to determine whether AVs could b

48、e a positive or a negative for climate change, so this remains an open question.Social inclusivity is another angle we look into. We suggest that AVs are likely to benefit the elderly and the demographic shifts globally (see An age-old question for a detailed demographic study, 30 November 2015). Th

49、is is in contrast to EVs, where the driver has to spend more time waiting for charging. This waiting could be tiring for the elderly versus quicker ICE re-fuelling today.Bottlenecks for EV, could be opportunity for AVsLike regulations for EVs, they could be also supportive for AVsDM vs. EMRapidly de

50、veloping EM nations generally have an incentive to be supportive of EVs to combat pollution. We suggest that counter-intuitively, the less developed infrastructure of EM cities might produce better AI AVs than the DMs and that some EM nations might be able to pass AV-friendly regulations quicker tha

51、n DMs. AVs could be a leapfrog technology for EM, just as wireless internet is potentially for them. For example in Kenya, mobiles have been instrumental in the widespread adoption of mobile payments (see Unbundling the City: Beyond urbanisation, 2 May 2017).AVs could be a leapfrog technology for EM

52、Timing and transitioning issuesThere have been repeated false dawns for EV take-up in the past2 but today a number of factors are highly supportive of electrification, including regulation and technology. The main questions are on the timing and transition towards AVs. Many AV participants suggest r

53、ollout from early 2020s to 2030s for fully AVs. Nevertheless, as the potential Waymo deployment reports suggest, one could see fully AVs in driverless-friendly (weather, regulations and extensively tested roads) specific locations like Arizona well before then. In other less highly-mapped and tested

54、 locations, however, we are likely to see various stages of advanced driver-assistance systems (ADAS) before reaching level 5 (fully autonomous) from today to the 2030s. See Global autos Disruptive threats: Carmakers versus new entrants (19 September 2017). Migration to EVs might impact the cost of

55、and hence the market for second-hand ICE vehicles. A similar scenario could be possible with the transition to AVs for vehicles with lower levels of autonomy.ADAS improvements lead to fully AVs by early 2020s to 2030s2 Asia EV and Battery: how China is helping to crack the cost conundrum”, Will Cho,

56、 HSBC, April 2016.5THEMATIC GLOBAL16 October 2017The core technology ecosystem and infrastructure requiredBattery technology is constantly improving and is projected to continue to do so (see Chart 1, page 10). Other infrastructure for EV rollout is charging stations. What about the technology for A

57、Vs? Although we dont yet have fully AVs today, we look at the core technology ecosystem and infrastructure that is required for a fully AV world, including computer vision,AV brain and connectivity technologies. See page 2 for the infographic Autonomous transportation ecosystem and infrastructure.EV

58、 technology is known and improving. AV is still developingSupplier dilemmas: legacy issues and possible value-chains questionsThe EV industry has had sunk costs for R&D and production for a number of years now. EV growth over the coming years can pay off for those companies that invested in these technologies. However, the development and deployment of AVs will also likely requir