1. | EXECUTIVE SUMMARY |
1.1. | Heavy-duty autonomous vehicles report |
1.2. | What makes it a roboshuttle? |
1.3. | Distribution of roboshuttle cities |
1.4. | Autonomous bus introduction |
1.5. | Categories of bus |
1.6. | Autonomous trucking - the right conditions right now |
1.7. | Why Automate Trucks? |
1.8. | Technology Readiness |
1.9. | Different powertrains for different vehicles |
1.10. | Types of service for roboshuttles and buses |
1.11. | Business model options for autonomous trucks |
1.12. | Number Of Active Companies |
1.13. | The Sensor Trifactor |
1.14. | Sensor suites for heavy-duty autonomous vehicles |
1.15. | SWOT analysis and comparisons for roboshuttles, autonomous buses and autonomous trucks. |
1.16. | Commercial readiness and opportunity comparison, roboshuttle, autonomous buses, autonomous trucks. |
1.17. | IDTechEx predicted timelines |
1.18. | Roboshuttle fleet size and unit sales 2020-2043 |
1.19. | Roboshuttle revenues, vehicle sales and passenger fares 2020-2043 |
1.20. | Autonomous bus unit sales 2023-2043 |
1.21. | Autonomous bus revenue 2023-2043 |
1.22. | Heavy Duty Trucking Unit Sales 2022-2042 |
1.23. | Heavy Duty Trucking Revenue 2022-2042 |
1.24. | Heavy Duty Autonomous Unit Sales 2023-2043 |
1.25. | Heavy Duty Autonomous Revenue 2023-2043 |
1.26. | Sensors for Heavy Duty Autonomous Vehicles 2023-2043 |
1.27. | Access to 20 IDTechEx Portal Company Profiles |
2. | ROBOSHUTTLES: PLAYERS AND ANALYSIS |
2.1. | Introduction |
2.1.1. | Key Takeaways For Roboshuttles |
2.1.2. | What Makes it a Roboshuttle? - Part 1 |
2.1.3. | What Makes it a Roboshuttle? - Part 2 |
2.1.4. | Table Comparison Of Active Companies (1) |
2.1.5. | Table Comparison Of Active Companies (2) |
2.1.6. | Table Comparison Of Active Companies (3) |
2.1.7. | Funding |
2.1.8. | EasyMile |
2.1.9. | EasyMile Real World Trials And Testing |
2.1.10. | EasyMile Business Model |
2.1.11. | Navya |
2.1.12. | Navya Testing Locations |
2.1.13. | Navya Use Case Examples |
2.1.14. | Navya's Installation Process |
2.1.15. | Navya's Business Model |
2.1.16. | ZF - A Robot Shuttle Future. |
2.1.17. | ZF - Robot Shuttle Deployment |
2.1.18. | ZF 2getthere Trial in Saudi Arabia |
2.1.19. | Coast |
2.1.20. | Cruise Origin |
2.1.21. | Toyota e-PALETTE |
2.1.22. | Sensible 4 - GACHA |
2.1.23. | IAV and the HEAT project |
2.1.24. | Lohr, Torc and Transdev |
2.1.25. | Torc/Lohr i-Cristal Sensor Suite |
2.1.26. | May Mobility |
2.1.27. | NEVS |
2.1.28. | Ohmio - Lift |
2.1.29. | Yutong |
2.1.30. | Apollo - Autonomous Branch of Baidu |
2.1.31. | Higer |
2.1.32. | Zoox |
2.1.33. | Zoox Sensor Suite |
2.1.34. | Service Providers |
2.2. | Roboshuttle projects that have discontinued |
2.2.1. | Continental |
2.2.2. | Bosch |
2.2.3. | Local Motors - Olli |
2.2.4. | e.Go Moove |
2.2.5. | DGWORLD |
2.2.6. | Projects That Are No Longer Active (1) |
2.2.7. | Projects That Are No Longer Active (2) |
2.2.8. | Projects That Are No Longer Active (3) |
2.3. | Roboshuttles analysis and conclusions |
2.3.1. | Technology Readiness |
2.3.2. | Decline in Roboshuttle Companies |
2.3.3. | Technology Readiness - Still Active |
2.3.4. | Where Players Exit |
2.3.5. | Where Are Players In The Value Chain |
2.3.6. | Speed And Distance |
2.3.7. | Passenger Capacity |
2.3.8. | Total Cost of Ownership Analysis |
2.3.9. | Reasons Roboshuttles Will Succeed |
2.3.10. | Reasons Roboshuttles Will Fail |
2.3.11. | IDTechEx Opinion On Roboshuttles |
3. | AUTONOMOUS BUSES: PLAYERS AND ANALYSIS |
3.1. | Introduction |
3.1.1. | Categories of Bus |
3.1.2. | Bus Category Sizing |
3.1.3. | Reasons to automate |
3.1.4. | Types Of Autonomous Services |
3.1.5. | Challenges Of Automating |
3.1.6. | Table Comparison Of Active Players (1) |
3.1.7. | Table Comparison Of Active Players (2) |
3.1.8. | Table Comparison Of Active Players (3) |
3.2. | Players - Minibuses |
3.2.1. | King Long |
3.2.2. | Aurrigo |
3.2.3. | Hyundai Autonomous Bus |
3.2.4. | Volkswagen |
3.2.5. | Volkswagen ID.Buzz - Sensor Suite |
3.2.6. | Volkswagens MOIA Project |
3.2.7. | Perrone Robotics - Overview |
3.2.8. | Perrone Robotics - Sensor Suite |
3.2.9. | Perrone Robotics - Deployment And Planned Rollout |
3.3. | Players - Midibuses |
3.3.1. | ADASTEC and Karsan |
3.3.2. | ADASTEC And Karsan - Sensor Suite |
3.3.3. | Golden Dragon ASTAR |
3.3.4. | QCraft |
3.3.5. | QCraft - Sensor Suite |
3.3.6. | LILEE |
3.3.7. | Zhongtong |
3.4. | Players - City Buses |
3.4.1. | Fusion Processing - Overview |
3.4.2. | Fusion Processing - Testing and Trials |
3.4.3. | ST Engineering |
3.4.4. | ANA and BYD - Airport Bus Trials |
3.4.5. | New Flyer - Overview |
3.4.6. | New Flyer - Sensor Suite |
3.4.7. | Irizar |
3.4.8. | Iveco |
3.4.9. | DeepBlue |
3.5. | Companies No Longer Active In Autonomous Buses |
3.5.1. | Daimler |
3.5.2. | Scania |
3.5.3. | Proterra |
3.5.4. | Other Big Players Either Not Involved Or Stopped |
3.6. | Autonomous Bus Analysis |
3.6.1. | Bus Sizes |
3.6.2. | Activity |
3.6.3. | Technology Readiness |
3.6.4. | Few Large Trials |
3.6.5. | Vehicle Type Vs Company Type |
3.6.6. | Lack Of Start-Ups, Driven By Established OEMs |
3.6.7. | Options For Early Deployments Of Autonomous Tech |
3.6.8. | Autonomous Bus Deployments In Other ODDs |
3.6.9. | Companies Spread Across The World |
3.6.10. | Drivetrains - Most Are Thinking Electric |
3.6.11. | Reasons Autonomous Buses Will Be A Success |
3.6.12. | Reasons Autonomous Buses Will Fail |
3.6.13. | IDTechEx Opinion On Autonomous Buses |
4. | AUTONOMOUS TRUCKS: PLAYERS AND ANALYSIS |
4.1. | Introduction |
4.1.1. | Pain points in the trucking industry |
4.1.2. | Why Automate Trucks? |
4.1.3. | SAE levels of automation |
4.1.4. | Level-2 And Level-4 Trucking |
4.1.5. | Level-4 MaaS for trucking |
4.1.6. | Authorities for regulating autonomous driving |
4.1.7. | The Autonomous Legal Race |
4.2. | Players - Start-ups |
4.2.1. | Funding and Maturity |
4.2.2. | TuSimple - Overview |
4.2.3. | TuSimple's AFN |
4.2.4. | TuSimple's unique perception solution |
4.2.5. | Perception system of TuSimple's autonomous trucks |
4.2.6. | TuSimple's enhanced night vision camera system |
4.2.7. | World's first fully autonomous semi-truck operating on public roads without human intervention |
4.2.8. | TuSimple's Business Model |
4.2.9. | Embark - Overview |
4.2.10. | Embark - Sensors |
4.2.11. | Embark - Trials And Rollout |
4.2.12. | Einride - Overview |
4.2.13. | Einride: a closer look into the T-pod and E-truck |
4.2.14. | Kodiak Robotics - Overview |
4.2.15. | Kodiak - Sensor Suite |
4.2.16. | Kodiak - Trials And Business Model |
4.2.17. | Plus - Overview |
4.2.18. | Plus - Sensor Suite |
4.2.19. | Plus - Testing, Trials and Deployments |
4.2.20. | Inceptio - Overview |
4.2.21. | Inceptio - Sensor Suite |
4.2.22. | Inceptio - Driverless Test |
4.2.23. | Waymo - Background |
4.2.24. | Waymo - Sensor Suite |
4.2.25. | Waymo - Trials |
4.2.26. | Torc Robotics - Overview |
4.2.27. | Torc Robotics - Sensor Suite |
4.2.28. | Torc Robotics - Testing And Trials |
4.2.29. | Aurora |
4.2.30. | Aurora - Sensor Suite |
4.2.31. | Aurora - Trials, Rollout And Business Model |
4.2.32. | Pony.ai |
4.2.33. | Pony.ai Sensor Suite (Robotaxi version) |
4.2.34. | Tesla |
4.2.35. | Solo AVT |
4.2.36. | DeepWay - A Baidu Founded Start-up |
4.3. | Player - Established Truck OEMs |
4.3.1. | Volvo Truck - Overview |
4.3.2. | Volvo Truck - Vera And VNL |
4.3.3. | Daimler |
4.3.4. | MAN |
4.3.5. | Scania |
4.3.6. | Hyundai catching up in the autonomous trucking race |
4.4. | Trucking Players That Are No Longer Active |
4.4.1. | Why Starsky Robotics Failed |
4.4.2. | Ike |
4.4.3. | Uber and Otto |
4.5. | Redundancy In Autonomous Trucks |
4.5.1. | Redundancy in Different Systems |
4.5.2. | Redundant Systems |
4.5.3. | Daimler Trucks - Redundancy in Braking Control |
4.5.4. | Daimler Trucks - Steering and Communication |
4.5.5. | Continental - Brakes (not Heavy Duty Specific) |
4.5.6. | Bosch - Brakes and Steering (not Heavy Duty Specific) |
4.5.7. | TuSimple - Functional Safety |
4.5.8. | TuSimple - Hardware Failure Tolerance |
4.5.9. | TuSimple - Software Fault Tolerance |
4.5.10. | TuSimple - Functional Safety Overview |
4.5.11. | Plus.AI - Single Sensor Type Redundancy |
4.5.12. | Kodiak - Localisation Redundancy |
4.5.13. | Aurora |
4.5.14. | Mobileye - A Different Approach To Redundancy |
4.5.15. | Redundancy in Connected Technologies |
4.6. | Truck analysis |
4.6.1. | Technology Maturity Status Definitions |
4.6.2. | Market readiness level of L4 autonomous truck companies |
4.6.3. | Maturity |
4.6.4. | Testing Distances |
4.6.5. | Company Backgrounds |
4.6.6. | Autonomous Trucking Activity |
4.6.7. | Company Locations |
4.6.8. | Business Model Options For Start-ups |
4.6.9. | Business Model Adoption |
4.6.10. | Key Drivers For Autonomous Trucks |
4.6.11. | Key Drivers For Autonomous Trucks |
4.6.12. | Remaining Hurdles For Autonomous Trucks |
4.6.13. | IDTechEx Opinion |
5. | SENSOR SUITES AND COMPUTERS FOR COMMERCIAL AUTONOMOUS VEHICLES |
5.1. | The Sensor Trifactor |
5.2. | Sensors for Roboshuttles |
5.3. | Sensors for autonomous buses |
5.4. | Sensors for autonomous trucks |
5.5. | Comparison to robotaxis |
5.6. | Computation for heavy-duty autonomous vehicles |
5.7. | Main computer supplier - Nvidia |
5.8. | Main computer supplier - Mobileye |
5.9. | Main LiDAR suppliers - Velodyne and Ouster |
5.10. | Sensor suite attributes |
5.11. | Conclusions |
6. | SUMMARY OF AUTONOMOUS ACTIVITY AND PROGRESS ACROSS TRUCKS, BUSES, ROBOSHUTTLES |
6.1. | Number Of Active Companies |
6.2. | Big Map of Activity Across The World |
6.3. | Locations Split By Vehicle Types |
6.4. | Table Of Vehicles And Players |
6.5. | Value Chain Position Of Companies In Commercial Autonomy |
6.6. | Technology Readiness |
6.7. | Ones To Watch - Roboshuttles (1) |
6.8. | Ones To Watch - Roboshuttles (2) |
6.9. | Ones to watch - Autonomous buses (1) |
6.10. | Ones to watch - Autonomous buses (2) |
6.11. | Ones To Watch - Autonomous Trucks |
6.12. | SWOT analysis and comparisons for roboshuttles, autonomous buses and autonomous trucks. |
6.13. | Commercial readiness and opportunity comparison, roboshuttle, autonomous buses, autonomous trucks. |
6.14. | IDTechEx predicted timelines |
6.15. | Conclusions |
7. | ENABLING TECHNOLOGIES: CAMERAS |
7.1. | RGB/Visible light camera SWOT |
7.2. | CMOS image sensors vs CCD cameras |
7.3. | Key Components of CMOS |
7.4. | Front vs backside illumination |
7.5. | Reducing Cross-talk |
7.6. | Global vs Rolling Shutter |
7.7. | TPSCo: leading foundry for global shutter |
7.8. | Sony: CMOS Breakthrough? |
7.9. | Sony: BSI global shutter CMOS with stacked ADC |
7.10. | OmniVision: 2.µm global shutter CMOS for automotive |
7.11. | Hybrid organic-Si global shutter CMOS |
7.12. | Event-based Vision: a New Sensor Type |
7.13. | What is Event-based Sensing? |
7.14. | General event-based sensing: Pros and cons |
7.15. | What is Event-based Vision? (I) |
7.16. | What is Event-based Vision? (II) |
7.17. | What is event-based vision? (III) |
7.18. | What does event-based vision data look like? |
7.19. | Event Based Vision in Autonomy? |
8. | ENABLING TECHNOLOGIES: THERMAL CAMERAS |
8.1. | Segmenting the Electromagnetic Spectrum |
8.2. | Thermal camera SWOT |
8.3. | IR Cameras |
8.4. | The Need for NIR |
8.5. | OmniVision: Making Silicon CMOS Sensitive to NIR |
8.6. | OmniVision: Making Silicon CMOS Sensitive to NIR |
8.7. | Motivation For Short-Wave Infra-Red (SWIR) Imaging |
8.8. | Why SWIR in Autonomous Mobility |
8.9. | Other SWIR Benefits: Better On-Road Hazard Detection |
8.10. | SWIR Sensitivity of Materials |
8.11. | SWIR Imaging: Incumbent and Emerging Technology Options |
8.12. | The Challenge of High Resolution, Low Cost IR Sensors |
8.13. | Silicon Based SWIR Detection - TriEye |
9. | ENABLING TECHNOLOGIES: QUANTUM DOTS AS OPTICAL SENSOR MATERIALS FOR IR, NIR, SWIR |
9.1. | Quantum Dots as Optical Sensor Materials |
9.2. | Quantum Dots: Choice of the Material System |
9.3. | Other Ongoing Challenges |
9.4. | Advantage of Solution Processing |
9.5. | QD-Si CMOS at IR and NIR |
9.6. | Hybrid QD-Si Global Shutter CMOS at IR and NIR |
9.7. | Emberion: QD-Graphene SWIR Sensor |
9.8. | Emberion: QD-Graphene-Si Broadrange SWIR sensor |
9.9. | SWIR Vision Sensors: First QD-Si Cameras and/or an Alternative to InVisage? |
9.10. | QD-ROIC Si-CMOS integration Examples (IMEC) |
9.11. | QD-ROIC Si-CMOS Integration Examples (RTI International) |
9.12. | QD-ROIC Si-CMOS Integration Examples (ICFO) |
9.13. | QD-ROIC Si-CMOS Integration Examples (ICFO) |
10. | ENABLING TECHNOLOGIES: LIDAR |
10.1. | LiDAR classifications |
10.2. | Automotive LiDAR: Operating process |
10.3. | Automotive LiDAR: Requirements |
10.4. | LiDAR system |
10.5. | LiDAR working principle |
10.6. | Laser range finder function for the first production car |
10.7. | Comparison of lidar product parameters |
10.8. | TOF vs. FMCW LiDAR |
10.9. | LiDAR scanning categories |
10.10. | Comparison of Common Beam Steering Options |
10.11. | Overview of beam steering technologies |
10.12. | Summary of lidars with various beam steering technologies |
10.13. | Point cloud |
10.14. | LiDAR signal applications |
10.15. | 3D point cloud modelling |
10.16. | LiDAR challenges |
10.17. | Poor weather performance: challenges & solutions |
10.18. | Autonomous mobility goes beyond cars |
10.19. | Early possible adoption of LiDAR |
10.20. | Velodyne lidar portfolios |
10.21. | Valeo SCALA |
10.22. | Livox: Risley prisms |
10.23. | Automotive lidar players by technology |
11. | ENABLING TECHNOLOGIES: RADAR |
11.1. | Radar SWOT |
11.2. | Radars are common in private vehicles |
11.3. | Radar Has a Key Place in Automotive Sensors |
11.4. | Front Radar Applications |
11.5. | The Role of Side Radars |
11.6. | Radars Limited Resolution |
11.7. | Radar Performance Trends |
11.8. | Radar Trilemma |
11.9. | Radar Anatomy |
11.10. | Primary Radar Components - The Antenna |
11.11. | Primary Radar Components - The RF Transceiver |
11.12. | Primary Radar Components - MCU |
11.13. | Automotive Radars: Frequency Trends |
11.14. | Trends in Transceivers |
11.15. | Two Approaches to Larger Channel Counts |
11.16. | Radar Board Trends |
11.17. | Radar Suppliers: Tier 1s and Start Ups |
11.18. | Leading players - tier 1 suppliers |
11.19. | Transceiver suppliers |
11.20. | Supply chain |
11.21. | Example products from a tier 1 - Continental |
11.22. | Example products from a tier 1 - Bosch |
11.23. | Example of radar start-up - Arbe |
11.24. | Arbe and its Investors |
11.25. | Example of radar start-up - Zadar |
12. | FORECASTS |
12.1. | Notes on the forecasts chapter |
12.2. | Forecasts: Roboshuttles |
12.2.1. | Method |
12.2.2. | Vehicle assumptions |
12.2.3. | Cities Considered |
12.2.4. | Adoption within cities |
12.2.5. | Current and forecasted city roll out 2020-2043 |
12.2.6. | Distribution of roboshuttle cities |
12.2.7. | Roboshuttle fare pricing for different economies |
12.2.8. | Roboshuttle price decline |
12.2.9. | Roboshuttle fleet size and unit sales 2020-2043 |
12.2.10. | Roboshuttle revenues, vehicle sales and passenger fares 2020-2043 |
12.2.11. | Sensors for roboshuttles 2020-2043 |
12.3. | Forecasts: Autonomous Buses |
12.3.1. | Method |
12.3.2. | Minibus utilization, adoption and city roll-out |
12.3.3. | Autonomous bus adoption |
12.3.4. | Autonomous bus unit sales 2023-2043 |
12.3.5. | Vehicle pricing |
12.3.6. | Autonomous bus revenue 2023-2043 |
12.3.7. | Seating capacity in autonomous buses and roboshuttles |
12.3.8. | Roboshuttle and autonomous bus sales revenue 2023-2043 |
12.3.9. | Powertrains of autonomous buses 2023-2043 |
12.3.10. | Sensors for autonomous buses |
12.4. | Forecasts: Autonomous Trucking |
12.4.1. | Method |
12.4.2. | Heavy Duty Trucking Unit Sales 2022-2042 |
12.4.3. | Autonomous truck pricing |
12.4.4. | Heavy Duty Trucking Revenue 2022-2042 |
12.4.5. | Miles and service revenue for autonomous trucks 2023-2043 |
12.4.6. | Autonomous truck powertrains 2023-2043 |
12.4.7. | Sensors for autonomous trucks |
12.5. | Forecast: Unit sales and sales revenues for roboshuttles, autonomous buses and autonomous trucks combined |
12.5.1. | Heavy duty autonomous unit sales: 2023-2043 |
12.5.2. | Heavy-duty autonomous revenue 2023-2043 |
12.5.3. | Sensors for heavy duty autonomous vehicles 2023-2043 |