EVP, Products & Strategy Strategy Session - MaaS Erez Dagan - PowerPoint PPT Presentation

EVP, Products & Strategy Strategy Session - MaaS Erez Dagan

Mobility Market – Inefficiencies & opportunity The Mobility Supply challenge Serve individual A-to-B-at-T demand instances, while minimizing latencies , costs and collateral/societal burden . Existing solutions Economical Inefficiencies • Vehicle ownership ➔ 94% Idle time, parking space • Driver on demand: Taxi ➔ Dispatch inefficiencies, DPP • Driver on demand : Hailing ➔ fleet-level inefficiencies, DPP • Public transport ➔ Stiff route, size & time, ETA Societal burden Reduced Traffic flow & street space • Mobility affordability and accessibility is limited • Inefficient energy use • Noise & air pollution •

Mobility Market – Inefficiencies & opportunity Exemplified by cost/mile, relative units Vehicle ownership Mobility on demand Public transport Other Fleet level dispatch automation Car/AV Driver’s owned vehicle Maintenance Driver commission, commoditized, is still ~75% of cost Expensive driver acquisition, high attrition Other No driver Light Centralized , coordinated fleet optimized utilization of capital & energy Higher capital and maintenance *V PRT >>V B Light Driver Driver Medium (2 riders on avg) Other commission commission Capital Medium Other Capital Car/AV Capital Medium Operating Heavy Car/AV costs Operating Operating Heavy Maintenance Heavy costs costs Maintenance Taxi Ride hailing Robotaxi RT-pooling Metropolitan Urban Sub urban Bus Commuter rail Heavy rail ~1% of US mobility miles

Mobility Market – Inefficiencies & opportunity TAM for MaaS (B of $) RT MaaS TAM is expected to reach $160B at 2030 ,by conservative estimates representing a 30% take of MOD market ~550 Bike-share/Scooters ~1600 cities by 2030 # of trips by city size 160B$ Robotaxi Avg annual spend 160-240$ ~350 RT CAGR ~50% ~230 ~150 Traditional RH ~105 2018 2021 2024 2027 2030

The future value of Consumer-Facing Mobility service Visual perception Mobility : The next economical revolution to unfold Transportation is a commonly unaccounted-for transaction cost. Mobility and phy physi sical tra raff ffic are both shaping up as marketplaces for optimizing this inefficient behemoth economical factor. Vehicle ownership Mobility Consumer AV Driver on demand Marketplace Vehicle on demand Mobility as a Traffic service Marketplace Public transport Hence - Mobility demand-exposure & supply-management - will evolve to fuel a broad set of new transaction types and mobility products. Peer-to-Peer AV Inward/outward traffic bundles City planning tool

Passenger Economy expectations Visual perception While Robotaxi TAM expectation is $160 billion by 2030 - The overall pas passenger ec economy – as high as $7 trillion by 2050 Global Passenger Economy Service Revenues 2030-2050 (US$, Millions) $165B

MaaS : corridor to consumer vehicle automation Visual perception Consumer autonomy - The next market-wide automotive product. - Self driving systems will constitute a sizeable portion of the vehicle value. M Vehicles L1/2 35 MaaS : self- driving-system ’ s first productization arena ME/Intel MaaS proposition will forge our self-driving product 30 towards its mass-market phase : consumer AV 25 Geo expansion Cost/Value optimization L2+ Safety & Regulation 20 Maa aaS will go govern vern self self- dri drivi ving pro produc ductization pac pace 15 Consumer AV market will be time med by SDS productization and 10 consequent cost/value optimization steps within MaaS Consumer AV 5 Dev Developing Maa aaS and and dr drivi ving ng It It to qui quick con conve verg rgence is s cr critic ical l to RT sec secur ure our ur SDS SDS pr produc duct fit, and and to do domin minate the he con consum sumer AV V ra ramp mp 0 up p ahe ahead of the e indus dustry y lea earni rning curve curve. 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 1” Accelerating the Future: The Economic Impact of the Emerging Passenger Economy Report”, June 2017, Strategy Analytics

MaaS : corridor to consumer vehicle automation Visual perception Consumer autonomy - The next market-wide automotive product. - Self driving systems will constitute a sizeable portion of the vehicle value. M Vehicles L1/2 35 MaaS : self- driving-system ’ s first productization arena ME/Intel MaaS proposition will forge our self-driving product 30 towards its mass-market phase : consumer AV 25 Geo expansion Cost/Value optimization L2+ Safety & Regulation Not Unlike … Consumer ADAS 20 Retrofit ADAS Maa aaS will go govern vern self self- dri drivi ving pro produc ductization pac pace 15 Consumer AV market will be time med by SDS productization and 2007 2008 2009 2010 10 consequent cost/value optimization steps Consumer AV 5 Dev Developing Maa aaS and and dr drivi ving ng It It to qui quick con conve verg rgence is s cr critic ical l to RT sec secur ure our ur SDS SDS pr produc duct fit, and and to do domin minate the he con consum sumer AV V ra ramp mp 0 up p ahe ahead of the e indus dustry y lea earni rning curve curve. 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 1 ” Accelerating the Future: The Economic Impact of the Emerging Passenger Economy Report ” , June 2017, Strategy Analytics

MaaS, at scale, is Imperative to our roadmap Visual perception MaaS plays a crucial role in shaping Self-Driving-Systems as a commercial product : • Battle-testing and certifying the technology globally. • Gaining regulatory and market credibility • Cardinal data generator to fuel the future advances of this industry 1. Optimization : To optimize the SDS product-fit towards the consumer AV phase, all factors above must be maximally amplified by operating at scale 2. Co-Optimization: SDS is undoubtedly the value-engine that propels MaaS. Its characteristics have profound impact on shaping all value nodes on top : + Teleoperation protocols + Self driving vehicle interfaces and design + Rider experience and HMI + Control center + Fleet operation and diagnostics routine All the way up to the customer facing service layer and GTM strategy .

MaaS layers & crosstalk Service & in-ride experience MaaS Layer 5 Value Determinants Cost Determinants Mobility Intelligence MaaS Layer 4 HW- Vehicle & SDS Optimized SLA & ETA ▪ ▪ Capital Utilization Experience & Services ▪ ▪ Fleet Operations MaaS Layer 3 Efficient Teleoperation support Safety & Safety perception ▪ ▪ Mixed fleet burdens ▪ Self-Driving Vehicles MaaS Layer 2 Self-Driving System MaaS Layer 1

MaaS layers & crosstalk Service & in-ride experience MaaS Layer 5 Technical ➔ Psychological safety ETA estimations GTM for maximal utilization Mobility Intelligence MaaS Layer 4 Supported ODD Realtime diagnostics HD map status and growth Fleet Operations MaaS Layer 3 Diagnostics Maintenance Repair Self-Driving Vehicles MaaS Layer 2 Interfaces Installation Connectivity Homologation Self-Driving System Safety schemes MaaS Layer 1

Cardinal differentiation pivots Self Driving System (SDS) EQ Overall HW costs and power consumption REM Seamless, selective geo scaling , ramp up Service & ride experience MaaS UX RSS Technical/Psychological Safety & Ride duration L. 5 Content Advertisement / O2O True redundancy validation costs , generalization, ramp up Mobility Intelligence Mobility Frontend Layer 4 Mobility Backend Fleet Intelligence Platform Mixed Fleet Fleet Operations Layer 3 Fleet Operations Platform Service Hubs/Depots Fleet Financing/Insurance Rider Sensing Self-Driving Vehicles Layer 2 MaaS UX HW Completion Centers Base Vehicle + L4 ready Self-Driving System TeleOperation Layer 1 HD Map / Data Services (AV-System/-Kit) SDS Software SDS Hardware

Decision making delegated to human operator Teleoperation SDS executes into control commands Service & ride experience MaaS UX L. 5 Content Advertisement / O2O Control Center Mobility Intelligence Mobility Frontend Layer 4 Mobility Backend Fleet Intelligence Platform Real Time Policy Data Feed Interventions Mixed Fleet Fleet Operations Layer 3 Fleet Operations Platform Service Hubs/Depots Fleet Financing/Insurance Edge Cases Rider Sensing Self-Driving Vehicles Layer 2 MaaS UX HW Completion Centers Base Vehicle + L4 ready Self-Driving System TeleOperation Layer 1 HD Map / Data Services (AV-System/-Kit) Primary and essential SDS extension, by regulation, tightly couples ▪ SDS Software Operator-to-cars ratio - key cost efficiency factor ▪ SDS Hardware Incident response/resolve time – key service level factor ▪