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. |
Einride Sweden: not quite a robot shuttle |
2.12. |
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. |
BlueSG/ Nanyang France Singapore |
3.9. |
Capri AECOM UK |
3.10. |
Coast Autonomous |
3.11. |
DeLijn Belgium |
3.12. |
e-BiGO Dubai |
3.13. |
eGo Mover Germany |
3.14. |
E-Palette Toyota |
3.15. |
EZ10 EasyMile France |
3.16. |
GACHA Sensible4 Finland |
3.17. |
Heathrow pod ULTraFairwood UK |
3.18. |
Hino Poncho SB Drive Japan |
3.19. |
IAV HEAT Germany |
3.20. |
iCristal Torc Robotics USA |
3.21. |
KAMAZ shuttles Russia |
3.22. |
KTI Hyundai Korea |
3.23. |
LG Korea |
3.24. |
Myla: May Mobility USA |
3.25. |
Navya France |
3.26. |
NEVS Sweden |
3.27. |
Ohmio Automation New Zealand |
3.28. |
Olli: Local Motors USA |
3.29. |
Optimus Ride USA |
3.30. |
Ridecell Auro USA |
3.31. |
Scania NXT - a second generation robot shuttle Sweden |
3.32. |
Sedric Germany |
3.33. |
ST Engineering Land Systems Singapore |
3.34. |
Tony: Perrone Robotics USA |
3.35. |
Volkswagen ID Buzz Germany |
3.36. |
Yutong Xiaoyu China |
3.37. |
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. |
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