1. | EXECUTIVE SUMMARY |
1.1. | Autonomous trucking - Industry Overview |
1.2. | Autonomous trucking - the right conditions right now |
1.3. | Why Automate Trucks? |
1.4. | Number Of Active Companies |
1.5. | The Sensor Trio |
1.6. | Different powertrains for different vehicles |
1.7. | Business model options for autonomous trucks |
1.8. | SWOT analysis for autonomous trucks |
1.9. | IDTechEx predicted timelines |
1.10. | Heavy-Duty Trucking Unit Sales 2019-2044 |
1.11. | Heavy-Duty Trucking Revenue 2023-2044 |
1.12. | Sensors for heavy-duty trucks 2021-2044 |
1.13. | Access More with an IDTechEx Subscription |
2. | AUTONOMOUS TRUCKS: PLAYERS AND ANALYSIS |
2.1. | Introduction |
2.1.1. | Pain points in the trucking industry |
2.1.2. | Why Automate Trucks? |
2.1.3. | SAE levels of automation |
2.1.4. | Level-2 and Level-4 Trucking |
2.1.5. | Level-4 MaaS for trucking |
2.1.6. | Authorities for regulating autonomous driving - US |
2.1.7. | Authorities for regulating autonomous driving - China |
2.1.8. | Authorities for regulating autonomous driving - EU |
2.2. | Players - Start-ups |
2.2.1. | Startups list |
2.2.2. | TuSimple - Overview |
2.2.3. | TuSimple - Overview |
2.2.4. | TuSimple's Timeline |
2.2.5. | Perception system of TuSimple's autonomous trucks |
2.2.6. | Plus - Overview |
2.2.7. | Plus - Sensor Suite |
2.2.8. | Plus - Testing, Trials and Deployments |
2.2.9. | Inceptio - Overview |
2.2.10. | Inceptio - Sensor Suite |
2.2.11. | Inceptio - Testing |
2.2.12. | Inceptio - Partners and Customers |
2.2.13. | Einride - Overview |
2.2.14. | Einride: A closer look into the T-pod and E-truck |
2.2.15. | Einride - Partners |
2.2.16. | Einride - The Grids Concept |
2.2.17. | Einride - The Grids Concept |
2.2.18. | Kodiak Robotics - Overview |
2.2.19. | Kodiak - Sensor Suite |
2.2.20. | Kodiak - Trials and Business Model (1) |
2.2.21. | Kodiak - Trials and Business Model (2) |
2.2.22. | Torc Robotics - Overview |
2.2.23. | Torc Robotics - Sensor Suite (Gen 2) |
2.2.24. | Torc Robotics - Testing and Trials (1) |
2.2.25. | Torc Robotics - Testing and Trials (2) |
2.2.26. | Aurora |
2.2.27. | Aurora - Sensor Suite |
2.2.28. | Aurora - Trials, Rollout and Business Model |
2.2.29. | Pony.ai |
2.2.30. | Pony.ai - Business Model |
2.2.31. | DeepWay - A Baidu Founded Start-up |
2.2.32. | DeepWay - Sensor Suites |
2.2.33. | DeepWay - Trials (1) |
2.2.34. | DeepWay - Trials (2) |
2.2.35. | Terraline (Formerly Solo AVT) |
2.2.36. | TrunkTech |
2.3. | Players - Established Truck OEMs |
2.3.1. | Volvo Truck - Overview |
2.3.2. | Volvo Truck - Vera and VNL |
2.3.3. | Tesla |
2.3.4. | Daimler (1) |
2.3.5. | Daimler (2) |
2.3.6. | MAN |
2.3.7. | Scania |
2.3.8. | Hyundai |
2.4. | Trucking Players That Are No Longer Active |
2.4.1. | Embark - Overview |
2.4.2. | Waymo - Background |
2.5. | Redundancy in Autonomous Trucks |
2.5.1. | Redundancy in Different Systems |
2.5.2. | Redundant Systems |
2.5.3. | Daimler Trucks - Redundancy in Braking Control |
2.5.4. | Daimler Trucks - Steering and Communication |
2.5.5. | Continental - Brakes (not Heavy-Duty Specific) |
2.5.6. | Bosch - Brakes and Steering (not Heavy-Duty Specific) |
2.5.7. | TuSimple - Functional Safety |
2.5.8. | TuSimple - Hardware Failure Tolerance |
2.5.9. | TuSimple - Software Fault Tolerance |
2.5.10. | TuSimple - Functional Safety Overview |
2.5.11. | Plus.AI - Single Sensor Type Redundancy |
2.5.12. | Kodiak - Localisation Redundancy |
2.5.13. | Aurora |
2.5.14. | Mobileye - A Different Approach to Redundancy |
2.5.15. | Redundancy in Connected Technologies |
2.6. | Truck analysis |
2.6.1. | Technology Maturity Status Definitions |
2.6.2. | Market readiness level of L4 autonomous truck companies 2022 |
2.6.3. | Market Readiness Level of L4 Autonomous Truck Companies 2024 |
2.6.4. | Maturity |
2.6.5. | Fundings Raised and Received (1) |
2.6.6. | Fundings Raised and Received (2) |
2.6.7. | Fundings |
2.6.8. | Fundings |
2.6.9. | Testing Mileage, Trails and Partners |
2.6.10. | L4 Autonomous Public Road Testing Time, Location, Speed and Approval Authority |
2.6.11. | Company Backgrounds |
2.6.12. | Autonomous Trucking Activity (1) |
2.6.13. | Autonomous Trucking Activity (2) |
2.6.14. | Total Cost of Ownership Analysis - Assumption and Breakdown |
2.6.15. | Total Cost of Ownership Analysis |
2.6.16. | Total Cost of Ownership Analysis |
2.6.17. | Company Locations (1) |
2.6.18. | Company Locations (2) |
2.6.19. | Business Model Options for Start-ups |
2.6.20. | Business and Operating Model Adoption |
2.6.21. | 6 Key Drivers for Autonomous Trucks (1) |
2.6.22. | 6 Key Drivers for Autonomous Trucks (2) |
2.6.23. | Remaining Hurdles for Autonomous Trucks |
2.6.24. | IDTechEx opinion |
3. | SUMMARY OF AUTONOMOUS ACTIVITY AND PROGRESS IN TRUCKS |
3.1. | Locations Split by Vehicle Types |
3.2. | Table of Vehicles and Value Chain Position of Companies in Commercial Autonomy |
3.3. | Ones to Watch - Autonomous Trucks |
3.4. | SWOT analysis and comparisons for autonomous trucks |
3.5. | Commercial readiness and opportunity comparison, roboshuttle, autonomous buses, autonomous trucks. |
3.6. | IDTechEx predicted timelines |
4. | ENABLING TECHNOLOGIES: CAMERAS |
4.1. | Cameras in Autonomous Trucks |
4.2. | RGB/Visible light camera |
4.3. | CMOS image sensors vs CCD cameras |
4.4. | Key Components of CMOS |
4.5. | Front vs backside illumination |
4.6. | Reducing Cross-talk |
4.7. | Global vs Rolling Shutter |
4.8. | TPSCo: Leading foundry for global shutter |
4.9. | Sony: CMOS Breakthrough? |
4.10. | Sony: BSI global shutter CMOS with stacked ADC |
4.11. | OmniVision: 2.µm global shutter CMOS for automotive |
4.12. | Hybrid organic-Si global shutter CMOS |
4.13. | Event-based Vision: A New Sensor Type |
4.14. | What is Event-based Sensing? |
4.15. | General event-based sensing: Pros and cons |
4.16. | What is Event-based Vision? (I) |
4.17. | What is Event-based Vision? (II) |
4.18. | What is event-based vision? (III) |
4.19. | What does event-based vision data look like? |
4.20. | Event Based Vision in Autonomy? |
5. | ENABLING TECHNOLOGIES: THERMAL CAMERAS |
5.1. | Thermal Cameras in Autonomous Trucks |
5.2. | Segmenting the Electromagnetic Spectrum |
5.3. | The Need for NIR |
5.4. | OmniVision: Making Silicon CMOS Sensitive to NIR |
5.5. | OmniVision: Making Silicon CMOS Sensitive to NIR |
5.6. | Motivation For Short-Wave Infra-Red (SWIR) Imaging |
5.7. | Why SWIR in Autonomous Mobility |
5.8. | Other SWIR Benefits: Better On-Road Hazard Detection |
5.9. | SWIR Sensitivity of Materials |
5.10. | SWIR Imaging: Incumbent and Emerging Technology Options |
5.11. | The Challenge of High Resolution, Low Cost IR Sensors |
5.12. | Silicon Based SWIR Detection - TriEye |
6. | ENABLING TECHNOLOGIES: QUANTUM DOTS AS OPTICAL SENSOR MATERIALS FOR IR, NIR, SWIR |
6.1. | Quantum Dots as Optical Sensor Materials |
6.2. | Quantum Dots: Choice of the Material System |
6.3. | Other Ongoing Challenges |
6.4. | Advantage of Solution Processing |
6.5. | QD-Si CMOS at IR and NIR |
6.6. | QD-Si CMOS at IR and NIR |
6.7. | Hybrid QD-Si Global Shutter CMOS at IR and NIR |
6.8. | Emberion: QD-Graphene SWIR Sensor |
6.9. | Emberion: QD-Graphene-Si Broadrange SWIR sensor |
6.10. | SWIR Vision Sensors: First QD-Si Cameras and/or an Alternative to InVisage? |
6.11. | SWIR Vision Sensors: First QD-Si Cameras and/or an Alternative to InVisage? |
6.12. | SWIR Vision Sensors: First QD-Si Cameras and/or an Alternative to InVisage? |
6.13. | SWIR Vision Sensors: First QD-Si Cameras and/or an Alternative to InVisage? |
6.14. | QD-ROIC Si-CMOS integration examples (IMEC) |
6.15. | QD-ROIC Si-CMOS Integration Examples (RTI International) |
6.16. | QD-ROIC Si-CMOS Integration Examples (ICFO) |
6.17. | QD-ROIC Si-CMOS Integration Examples (ICFO) |
7. | ENABLING TECHNOLOGIES: LIDAR |
7.1. | LiDAR in Autonomous Trucks |
7.2. | LiDAR classifications |
7.3. | Automotive LiDAR: Operating process |
7.4. | Automotive LiDAR: Requirements |
7.5. | LiDAR system |
7.6. | LiDAR working principle |
7.7. | Laser range finder function for the first production car |
7.8. | Comparison of lidar product parameters |
7.9. | TOF vs FMCW LiDAR |
7.10. | LiDAR scanning categories |
7.11. | Summary of lidars with various beam steering technologies |
7.12. | Comparison of common beam steering options |
7.13. | Overview of beam steering technologies |
7.14. | Point cloud |
7.15. | Lidar signal applications |
7.16. | 3D point cloud modelling |
7.17. | LiDAR challenges |
7.18. | Poor weather performance: Challenges & solutions |
7.19. | Early possible adoption of Lidar |
7.20. | Velodyne lidar portfolios |
7.21. | Valeo SCALA |
7.22. | Livox: Risley prisms |
7.23. | Automotive lidar players by technology |
8. | ENABLING TECHNOLOGIES: RADAR |
8.1. | Radar in Autonomous Trucks |
8.2. | Typical Sensor Suite for Autonomous Cars |
8.3. | Radar Has a Key Place in Automotive Sensors |
8.4. | The Need for and Emergence of Imaging Radar |
8.5. | 4D Radars and Imaging Radars |
8.6. | Radar Trends: Volume and Footprint |
8.7. | Radar Trends: Packaging and Performance |
8.8. | Radar Trends: Increasing Range |
8.9. | Radar Trends: Field of View |
8.10. | Radar Trilemma |
8.11. | Radar Anatomy |
8.12. | Radar Key Components |
8.13. | Primary Radar Components - The Antenna |
8.14. | Primary Radar Components - the RF Transceiver |
8.15. | Primary Radar Components - MCU |
8.16. | Automotive Radars: Frequency Trends |
8.17. | Trends in Transceivers |
8.18. | Two Approaches to Larger Channel Counts |
8.19. | Semiconductor Technology Trends in Radar |
8.20. | Funding for Radar Start-ups |
8.21. | Future Radar Packaging Choices |
8.22. | Leading players - tier 1 suppliers |
8.23. | Transceiver suppliers |
8.24. | Supply chain |
8.25. | Example products from a tier 1 - Continental |
8.26. | Example products from a tier 1 - Bosch |
8.27. | Example of radar start-up - Arbe |
8.28. | Arbe and its Investors |
8.29. | Example of radar start-up - Zadar |
9. | FORECASTS |
9.1. | Notes on the forecasts chapter |
9.2. | Method |
9.3. | Heavy-Duty Trucking Unit Sales 2023-2044 |
9.4. | Autonomous truck pricing 2018-2044 |
9.5. | Heavy-Duty Trucking Revenue 2023-2044 |
9.6. | Miles and service revenue for autonomous trucks 2023-2044 |
9.7. | Autonomous truck powertrains 2023-2044 |
9.8. | Sensors for autonomous trucks 2021-2044 |
10. | COMPANY PROFILES |
10.1. | Aurora |
10.2. | Bosch |
10.3. | Continental AG |
10.4. | DeepWay |
10.5. | Einride: Automating Logistics |
10.6. | Hyundai |
10.7. | Inceptio |
10.8. | Innoviz |
10.9. | Innoviz |
10.10. | Kodiak Robotics: Autonomous Trucking Start-up |
10.11. | Mobileye: ADAS & Autonomy Computation |
10.12. | Ouster |
10.13. | plus.ai |
10.14. | Pony.ai |
10.15. | Terraline |
10.16. | Tesla Motors |
10.17. | Torc: An Autonomous Technology Company in Roboshuttles and Trucks |
10.18. | Trunk Tech |
10.19. | TuSimple |
10.20. | Valeo |
10.21. | Velodyne LIDAR |
10.22. | Volvo Trucks - Truck Electrification |
10.23. | Waymo (2023) |
10.24. | Waymo (2024) |