1. | EXECUTIVE SUMMARY AND CONCLUSIONS |
1.1. | Purpose of this report |
1.2. | SAE levels of automation in land vehicles |
1.3. | Ten primary conclusions |
1.3.1. | The dream and the basics for getting there |
1.3.2. | Specification of a robot shuttle |
1.3.3. | Very different from a robotaxi |
1.3.4. | Smart shuttles will address megatrends in society |
1.3.5. | Robot shuttle business cases from bans and subsidies |
1.3.6. | Robot shuttle business cases from exceptional penetration of locations |
1.3.7. | Intensive use business cases are compelling |
1.3.8. | Campuses are not a quick win |
1.3.9. | The robot shuttle opportunity cannot be addressed by adapting existing vehicles |
1.3.10. | The leaders so far |
1.3.11. | Upfront cost and other impediments |
1.3.12. | Dramatic technical improvements are coming |
1.4. | Two generations of robot shuttle |
1.4.1. | Envisaged applications compared |
1.4.2. | Second generation robot shuttle 2025-2040 |
1.5. | Robot shuttles: the good things |
1.5.1. | Many benefits |
1.5.2. | Building on the multi-purposing of the past |
1.6. | Robot shuttles: the bad things |
1.7. | Analysis of 36 robot shuttles and their dreams |
1.8. | Geographical, size, deployment distribution of 36 robot shuttles |
1.8.1. | Manufacture by country |
1.8.2. | Manufacture by major region |
1.8.3. | Designs by size |
1.8.4. | Number deployed |
1.9. | Timelines and forecasts |
1.9.1. | Technology and launch roadmap 2020-2030 |
1.9.2. | Predicting when the robot shuttle has lower up-front price than a legal diesel midibus 2020-2040 |
1.9.3. | Hype 2018-2040 |
1.9.4. | Robot shuttles total market size in unit numbers thousand |
1.9.5. | Robot shuttles total market size in US$ million |
1.9.6. | Bus and shuttle global market number projection by size 2020-2040 |
1.9.7. | Bus and shuttle global market number projection by size by % 2020-2040: growth of shuttle and smaller buses |
1.9.8. | Market share Level 4 and Level 5 autonomy in buses projection by size 2020-2040 |
1.9.9. | Global bus market by level of autonomy and projection by bus/ robot shuttle size 2018-2040 |
1.9.10. | Bus and robot shuttle total market projection by level of autonomy 2020-2030 |
1.9.11. | Cost projection of pure electric bus and shuttle (minus autonomy) 2020-2040 |
1.9.12. | Cost of autonomy 2020-2040 |
1.9.13. | Total 20-year market forecast for all bus/shuttle sizes and levels of autonomy |
1.9.14. | Total 20-year market forecast (purpose-built shuttles and small-sized buses) |
1.9.15. | Total 20-year market forecast (medium and large sized buses) |
1.9.16. | Accumulated fleet size projected number 2020-2040 |
1.9.17. | Service revenue forecast $ billion 2020-2040 |
1.9.18. | Total revenue forecast $ billion 2020-2030 |
2. | INTRODUCTION |
2.1. | Bus and robot shuttle types compared |
2.2. | Bus population worldwide by types 2020 |
2.3. | Pure electric buses for lowest TCO |
2.4. | Peak car coming: global passenger car sales forecast 2020-2040 - moderate scenario (unit numbers) |
2.5. | Background to robot shuttles |
2.6. | Tough for robot shuttles to compete |
2.7. | Second generation robot shuttles |
2.8. | Michigan Mobility Challenge: seniors, disabled, veterans |
2.9. | Texas trials: downtown circulator |
2.10. | Trials in Japan |
2.11. | Schaeffler: mechanically repurposed shuttle |
2.12. | Einride Sweden: not quite a robot shuttle |
2.13. | Rinspeed dreams embrace robot shuttles |
3. | ROBOT SHUTTLES IN ACTION - 37 TYPES IN 15 COUNTRIES |
3.1. | 2getthere Netherlands |
3.1.1. | Business |
3.1.2. | Product/Solution |
3.2. | 5GX shuttle SKT Korea |
3.3. | ANA collaboration Japan |
3.4. | Apollo Apolong: Baidu King Long China |
3.5. | Apple VWT6 USA |
3.6. | Astar Golden Dragon China |
3.7. | Aurrigo UK |
3.8. | AUVE Tech. Estonia |
3.9. | BlueSG/ Nanyang France Singapore |
3.10. | Capri AECOM UK |
3.11. | Coast Autonomous |
3.12. | DeLijn Belgium |
3.13. | e-BiGO Dubai |
3.14. | eGo Mover Germany |
3.15. | E-Palette Toyota |
3.16. | EZ10 EasyMile France |
3.17. | GACHA Sensible4 Finland |
3.18. | Heathrow pod ULTraFairwood UK |
3.19. | Hino Poncho SB Drive Japan |
3.20. | IAV HEAT Germany |
3.21. | iCristal Torc Robotics USA |
3.22. | KAMAZ shuttles Russia |
3.23. | KTI Hyundai Korea |
3.24. | LG Korea |
3.25. | Myla: May Mobility USA |
3.26. | Navya France |
3.27. | NEVS Sweden |
3.28. | Ohmio Automation New Zealand |
3.29. | Olli: Local Motors USA |
3.30. | Optimus Ride USA |
3.31. | Ridecell Auro USA |
3.32. | Scania NXT - a second generation robot shuttle Sweden |
3.33. | Sedric Germany |
3.34. | ST Engineering Land Systems Singapore |
3.35. | Tony: Perrone Robotics USA |
3.36. | Volkswagen ID Buzz Germany |
3.37. | Yutong Xiaoyu China |
3.38. | Zoox USA |
4. | ROBOT SHUTTLE TECHNOLOGY BEYOND AUTONOMY |
4.1. | Overview |
4.2. | Challenges being addressed |
4.3. | How eight key enabling technologies for robot shuttles are improving to serve 10 primary needs |
4.4. | How to reduce diesel shuttle parts by 90% with advanced electrics |
4.5. | Big change in relative importance of parts |
4.6. | Future electric vehicle powertrains - relevance to robot shuttles |
4.7. | Platform evolution |
4.7.1. | Overview |
4.7.2. | Toyota REE chassis: huge advances |
4.8. | Voltage trends |
4.9. | Typical pure electric bus technology |
4.10. | Electric motors |
4.10.1. | Overview |
4.10.2. | Synchronous or asynchronous |
4.10.3. | Operating principles for most EV uses |
4.10.4. | Electric motor choices for robot shuttles and their current EV uses |
4.10.5. | Electric motors for pure electric cars, vans: lessons for shuttle buses |
4.10.6. | Company experience and designer preferences |
4.10.7. | Motor material cost trends spell trouble |
4.11. | In-wheel motors |
4.12. | Sideways steerable wheels |
4.13. | 360 degree wheels with in-wheel motor: Protean and Productiv |
4.14. | Energy storage for pure electric buses |
4.14.1. | Conventional buses see batteries shrink |
4.14.2. | Robot shuttles stay battery hungry |
4.14.3. | Even better batteries and supercapacitors a real prospect: future W/kg vs Wh/kg |
4.14.4. | Location and protection of batteries |
4.14.5. | Bus battery type, performance, future for 31 manufacturers |
4.14.6. | Best of both worlds? |
4.15. | Charger standardisation: bus/truck commonality |
4.16. | Energy Independent Electric Vehicles EIEV |
4.17. | Stella Vie showing the way to an energy positive robot shuttle? |
5. | AUTONOMY TECHNOLOGY |
5.1. | Overview |
5.1.1. | The automation levels in detail |
5.1.2. | Functions of autonomous driving at different levels |
5.1.3. | Future mobility scenarios: autonomous and shared |
5.1.4. | Chess pieces: autonomous driving tasks |
5.1.5. | Typical toolkit for autonomous cars |
5.1.6. | Perception technologies and AI |
5.1.7. | Anatomy of an autonomous vehicle |
5.1.8. | Evolution of sensor suite from Level 1 to Level 5 |
5.1.9. | What is sensor fusion? |
5.1.10. | Sensor fusion: past and future |
5.2. | Lidars |
5.2.1. | 3D Lidar: market segments & applications |
5.2.2. | 3D Lidar: four important technology choices |
5.2.3. | Comparison of Lidar, Radar, Camera & Ultrasonic sensors |
5.2.4. | Automotive Lidar: SWOT analysis |
5.2.5. | Emerging technology trends |
5.2.6. | Comparison of TOF & FMCW Lidar |
5.2.7. | Laser technology choices |
5.2.8. | Comparison of common laser type & wavelength options |
5.2.9. | Beam steering technology choices |
5.2.10. | Comparison of common beam steering options |
5.2.11. | Photodetector technology choices |
5.2.12. | Comparison of common photodetectors & materials |
5.2.13. | Mechanical Lidar players, rotating & non-rotating |
5.2.14. | Micromechanical Lidar players, MEMS & other |
5.2.15. | Pure solid-state Lidar players, OPA & liquid crystal |
5.2.16. | Pure solid-state Lidar players, 3D flash |
5.2.17. | Players by technology & funding secured |
5.2.18. | Average Lidar cost per vehicle by technology |
5.3. | Radars |
5.3.1. | Why are radars essential to ADAS and autonomy? |
5.3.2. | Towards ADAS and autonomous driving: increasing radar use |
5.3.3. | SRR, MRR and LRR: different functions |
5.3.4. | Radar: which parameters limit the achievable KPIs |
5.3.5. | Towards the radar of the future |
5.3.6. | Evolution of semiconductor technology in automotive radar |
5.3.7. | Benchmarking of semiconductor technologies for mmwave radars |
5.3.8. | Many chip makers are on-board |
5.3.9. | Function integration trends: towards true radar-in-a-chip |
5.3.10. | Evolution of radar chips towards all-in-one designs |
5.3.11. | Board trends: from separate RF board to hybrid to full package integration? |
5.3.12. | The evolving role of the automotive radar towards full 360degree imaging |
5.3.13. | AI trend: moving beyond just presence detection |
5.3.14. | Other trends: increasing range, angular and elevation resolution |
5.3.15. | Radar data: challenges of spare point cloud |
5.3.16. | Data fusion challenge: mismatch in point cloud densities |
5.3.17. | Training neutral networks on radar data: the labelling challenge |
5.3.18. | Automatic data labelling: early fusion of camera, lidar and radar data |
5.4. | AI software and computing platform |
5.4.1. | Terminologies explained: AI, machine learning, artificial neural networks, deep neural networks |
5.4.2. | Artificial intelligence: waves of development |
5.4.3. | Classical method: feature descriptors |
5.4.4. | Typical image detection deep neutral network |
5.4.5. | Algorithm training process in a single layer |
5.4.6. | Towards deep learning by deepening the neutral network |
5.4.7. | The main varieties of deep learning approaches explained |
5.4.8. | There is no single AI solution to autonomous driving |
5.4.9. | Application of AI to autonomous driving |
5.4.10. | End-to-end deep learning vs classical approach |
5.4.11. | Imitation learning for trajectory prediction: Valeo (1) |
5.4.12. | Imitation learning for trajectory prediction: Valeo (2) |
5.4.13. | Hybrid AI for Level 4/5 automation |
5.4.14. | Hybrid AI for sensor fusion |
5.4.15. | Hybrid AI for motion planning |
5.4.16. | Autonomous driving requires different validation system |
5.4.17. | Validation of deep learning system? |
5.4.18. | The vulnerable road user challenge in city traffic |
5.4.19. | Multi-layered security needed for vehicle system |
5.5. | High-definition (HD) map |
5.5.1. | Lane models: uses and shortcomings |
5.5.2. | Localization: absolute vs relative |
5.5.3. | HD mapping assets: from ADAS map to full maps for level-5 autonomy |
5.5.4. | Many layers of an HD map for autonomous driving |
5.5.5. | HD map as a service |
5.5.6. | Who are the players? |
5.5.7. | Why Vehicle-to-everything (V2X) is important for future autonomous vehicles |
5.5.8. | Use cases of 5G NR C-V2X for autonomous driving |
6. | COST AND INCOME ANALYSIS |
6.1. | Robot shuttle cost overview 2018-2040 |
6.1.1. | Cost and price overview |
6.1.2. | Cost per passenger km vs eVTOL taxis |
6.1.3. | The example of Japan |
6.1.4. | Example of Germany: Robot shuttles will help eliminate subsidies |