Periodic Reporting for period 1 - AWARD (All Weather Autonomous Real logistics operations and Demonstrations)
Reporting period: 2021-01-01 to 2022-06-30
The Logistic Industry's next main leap in productivity should come from safe, 24/7 operations under all external conditions. Automation, based on high end sensors, adapted heavy duty vehicles, advanced autonomous driving AIs could deliver those radical improvements in the coming years and decades. Future autonomous solutions will allow for safer, faster and more reliable operations, leading to lower costs for consumers, safer and more fullfilling work environement for logistic supervisors and better competitiveness for logistic center operators.
With this goal in mind, the AWARD consortium gathers the whole value chain for future autonomous logistic operations: from sensor manufacturer to end users and including ADS (Auonomous Driving Systems) providers and top level research institutes. The AWARD project shall deliver 4 real world use cases in which Autonomous Heavy Duty Vehicle will perform partial or complete logistic processes within real industrial flows. As a first ambitious step into higher automation of logistic operations, AWARD will also try to improve ADS performances under all weather conditions.
With this goal in mind, the AWARD consortium gathers the whole value chain for future autonomous logistic operations: from sensor manufacturer to end users and including ADS (Auonomous Driving Systems) providers and top level research institutes. The AWARD project shall deliver 4 real world use cases in which Autonomous Heavy Duty Vehicle will perform partial or complete logistic processes within real industrial flows. As a first ambitious step into higher automation of logistic operations, AWARD will also try to improve ADS performances under all weather conditions.
1) To ensure that the AWARD solution will address logistics needs.
Stakeholder needs and requirements for the AWARD Autonomous Goods Transportation Systems (AGTS) have been identified. Completeness and representativeness of stakeholders’ and users’ groups have been assured by defining a comprehensive stakeholder taxonomy that was taken as a reference frame for data gathering and analysis. The detailed ODD (Operational Design Domain) which consists of elements describing the physical infrastructure, the environmental conditions and the operational constraints of the automated vehicles has been created to provide a reference base for the functional requirements.
2) To develop a safe and scalable autonomous driving system able to manage harsh weather condition qualified for heavy duty vehicles.
The ADS system uses AWARD sensor set to feed the localization and perception software functions. Radar localization will be used as a redundant localization source modality to the odometry, GNSS/RTK and LIDAR localization functions. Object output from the stereo and thermal cameras system coupled with powerful analysis embedded algorithm, as well as radar object detection, will increase the vehicles performances towards “all-weather” real-time object 360° detection and synthesis. AWARD team performed specific safety-oriented analysis (HARA, safety goals and functional safety concepts were defined).The AWARD ADS is compliant with the 4 AWARD platforms (from the luggage tractor to the Forklift), which demonstrates the high level of scalability of the solution and ensures a “standardized” solution, adaptable to various HDV.
3) To improve efficiency of logistics operations with autonomous heavy-duty vehicles.
AWARD fleet management design was done in accordance with the use cases and in coordination with the team' objectives. Interfaces/connections to the surrounding systems including the logistics systems (e.g.: Terminal Operating System API), road units and sensors (traffic lights, gates, weather stations) and the different platforms were defined. The API development was supported by simulation to validate software development and demonstrate how the fleet manager will access the different streams of data. A major achievement was the first successful test of the AWARD FMS in controlled testing grounds at the EasyMile Francazal proving ground. This opened the first successful deployment of the FMS for AVINOR (Airport use case).
4) To perform innovative autonomous heavy duty vehicles missions in real logistics operations.
The consortium defined with each OEM (Original Equipment Manufacturer) for each platform the generic drive by wire and control command requirements and all the technical requirements. The generic AWARD sensor sets architecture was also defined. Then the team started to perform the definition of the platform architecture, the design of the ADS components that will be integrated in the vehicle, the development of the different low-level softwares to ensure the control of the platform and a set of safety functions.
The consortium also worked to obtain the tests permissions with the local authorities. Site visits were done to review and validate the scenarios and deployment timings. The consortium also laid a methodologic foundation to evaluate the objective and related KPIs during reporting period 1. A baseline Telemetry data table was defined according to the project data needs.
5) To provide insights and recommendations on the standardisation and harmonisation of certification processes and type approval at EU level and on regulation that ensure both safety and economic viability of automated transport systems.
The consortium mainly worked on the demonstration of the economic viability of automated transport. The study is focused on the business analysis of all different deployment opportunities related to connected and automated heavy-duty vehicles in real-life logistics operations. Analysis of the market and competition was performed as well as a benchmark of existing HDV (Heavy duty Vehicle) platforms in logistics environment.
Stakeholder needs and requirements for the AWARD Autonomous Goods Transportation Systems (AGTS) have been identified. Completeness and representativeness of stakeholders’ and users’ groups have been assured by defining a comprehensive stakeholder taxonomy that was taken as a reference frame for data gathering and analysis. The detailed ODD (Operational Design Domain) which consists of elements describing the physical infrastructure, the environmental conditions and the operational constraints of the automated vehicles has been created to provide a reference base for the functional requirements.
2) To develop a safe and scalable autonomous driving system able to manage harsh weather condition qualified for heavy duty vehicles.
The ADS system uses AWARD sensor set to feed the localization and perception software functions. Radar localization will be used as a redundant localization source modality to the odometry, GNSS/RTK and LIDAR localization functions. Object output from the stereo and thermal cameras system coupled with powerful analysis embedded algorithm, as well as radar object detection, will increase the vehicles performances towards “all-weather” real-time object 360° detection and synthesis. AWARD team performed specific safety-oriented analysis (HARA, safety goals and functional safety concepts were defined).The AWARD ADS is compliant with the 4 AWARD platforms (from the luggage tractor to the Forklift), which demonstrates the high level of scalability of the solution and ensures a “standardized” solution, adaptable to various HDV.
3) To improve efficiency of logistics operations with autonomous heavy-duty vehicles.
AWARD fleet management design was done in accordance with the use cases and in coordination with the team' objectives. Interfaces/connections to the surrounding systems including the logistics systems (e.g.: Terminal Operating System API), road units and sensors (traffic lights, gates, weather stations) and the different platforms were defined. The API development was supported by simulation to validate software development and demonstrate how the fleet manager will access the different streams of data. A major achievement was the first successful test of the AWARD FMS in controlled testing grounds at the EasyMile Francazal proving ground. This opened the first successful deployment of the FMS for AVINOR (Airport use case).
4) To perform innovative autonomous heavy duty vehicles missions in real logistics operations.
The consortium defined with each OEM (Original Equipment Manufacturer) for each platform the generic drive by wire and control command requirements and all the technical requirements. The generic AWARD sensor sets architecture was also defined. Then the team started to perform the definition of the platform architecture, the design of the ADS components that will be integrated in the vehicle, the development of the different low-level softwares to ensure the control of the platform and a set of safety functions.
The consortium also worked to obtain the tests permissions with the local authorities. Site visits were done to review and validate the scenarios and deployment timings. The consortium also laid a methodologic foundation to evaluate the objective and related KPIs during reporting period 1. A baseline Telemetry data table was defined according to the project data needs.
5) To provide insights and recommendations on the standardisation and harmonisation of certification processes and type approval at EU level and on regulation that ensure both safety and economic viability of automated transport systems.
The consortium mainly worked on the demonstration of the economic viability of automated transport. The study is focused on the business analysis of all different deployment opportunities related to connected and automated heavy-duty vehicles in real-life logistics operations. Analysis of the market and competition was performed as well as a benchmark of existing HDV (Heavy duty Vehicle) platforms in logistics environment.
- Improvement of the architecture of the ADS:
AWARD will demonstrate the added value of the RADAR localization modality for harsh weather condition navigation (precision of the partners radar localization will be evaluated and used as a redundant source of localization in parallel of the LIDAR, Odometry and GNSS/RTK positioning). Moreover, AWARD sensor set object output will be used to detect and classify object surrounding the platform for various weather conditions. In addition, an embedded teleoperation platform will be integrated to handling any “edge case” on the road or high ambiguity situation, by referring to human intelligence that can intervene safely from remote.
- Demonstration of ADS integrated in different heavy-duty vehicles in real-life logistics operations.
AWARD ADS architecture will compliant with the safety standards guidelines and adaptable to various industrial platforms (from the port truck to the forklift).
Testing phases (integration tests, SOTIF tests) of the 4 heavy-duty platforms from the baggage airport tractor to the port truck will allow the project to deploy the vehicles in real-life logistics operation with mixed traffic segment between warehouses.
- Validation of efficiency increase of fleets using trucks with ADS
The project will present a standardised interfaces for efficient and safe communication with vehicles, road infrastructure, logistics systems and other relevant road users, allowing the achieved design to be implemented in any desired system. The new fleet management system, concerted unification of TOS, V2X services and road sensors will demonstrate a more efficient and reliable fleet, decreasing handling times, emissions and need for human interaction while increasing reliability and safety.
AWARD will demonstrate the added value of the RADAR localization modality for harsh weather condition navigation (precision of the partners radar localization will be evaluated and used as a redundant source of localization in parallel of the LIDAR, Odometry and GNSS/RTK positioning). Moreover, AWARD sensor set object output will be used to detect and classify object surrounding the platform for various weather conditions. In addition, an embedded teleoperation platform will be integrated to handling any “edge case” on the road or high ambiguity situation, by referring to human intelligence that can intervene safely from remote.
- Demonstration of ADS integrated in different heavy-duty vehicles in real-life logistics operations.
AWARD ADS architecture will compliant with the safety standards guidelines and adaptable to various industrial platforms (from the port truck to the forklift).
Testing phases (integration tests, SOTIF tests) of the 4 heavy-duty platforms from the baggage airport tractor to the port truck will allow the project to deploy the vehicles in real-life logistics operation with mixed traffic segment between warehouses.
- Validation of efficiency increase of fleets using trucks with ADS
The project will present a standardised interfaces for efficient and safe communication with vehicles, road infrastructure, logistics systems and other relevant road users, allowing the achieved design to be implemented in any desired system. The new fleet management system, concerted unification of TOS, V2X services and road sensors will demonstrate a more efficient and reliable fleet, decreasing handling times, emissions and need for human interaction while increasing reliability and safety.