Tight integration of EGNSS and on-board sensors for port vehicle automation

Project Information

LOGIMATIC

Grant agreement ID: 687534

DOI

10.3030/687534

Project closed

EC signature date 11 February 2016

Start date 1 March 2016

End date 31 August 2019

Funded under

• INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies – Space

Total cost

€ 2 386 925,00

EU contribution

€ 2 002 910,00

Coordinated by

FUNDACIO EURECAT
Spain

Periodic Reporting for period 2 - LOGIMATIC (Tight integration of EGNSS and on-board sensors for port vehicle automation)

Reporting period: 2017-09-01 to 2019-08-31

Summary of the context and overall objectives of the project

Total annual volume of container shipping in seaborne trade is continuously growing since the 80's. This increase will push container terminals to work consistently above the optimum thresholds for yard occupancy and utilization, increasing congestion and reducing efficiency. The usual way for ports to cope with this increasing demand is to expand the port in the original site. However, there is scarcity of land available in densely populated urban areas and the investment costs associated are high. This fact is causing that container terminals have congestion and capacity problems. Therefore, port managers are searching for more efficient and cost-effective means in the handling of containers while still trying to introduce innovative technical solutions. Container handling equipment (CHE) automation is an innovative technological solution that contributes to improve the utilization rate of equipment and to reduce operating costs as well as to improve efficiency and workig conditions. LOGIMATIC proposes an ad-hoc advanced location and navigation solution to enable the automation of existing port vehicles with a significant lower cost. The project demonstrated an innovative location and navigation solution for the automation of the operations of straddle carriers in container terminals which is robust to spoofing and jamming attacks and is able to interoperate with existing Terminal Operating Systems (TOS) through a GIS-based central control interface. The exploitation of the results of the project will improve productivity by increasing operational efficiency, increasing task accuracy, reducing errors and allowing faster cycle times in port operations. Therefore, the overall cost for port management will be reduced, increasing European ports competitiveness. Mid-size ports will increase their operational capacities without increasing worker strain and stress and therefore reducing safety incidents. The exploitation of the results will potentially create new jobs by requiring higher-skilled job profiles in the port operations staff.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

During the execution of the project the following results were performed: (i) an hybridized localization unit combining EGNSS and on board sensors enabling autonomous navigation; (ii) a GIS connected with the Terminal Operating System providing job orders and monitoring the port vehicles; and (iii) a security strategy to withstand cyber-attacks and GNSS-related threats. Four pillars contitute the focus of the advanced automated navigation solution: EGNSS global localization, local localization with onboard sensors, autonomous navigation and the integration of the three. The initial work included the selection of the GNSS localization methods and the architecture of the system and the design of the self-localization strategy based on simultaneous localization and mapping (SLAM) algorithms. Two different signal processing methods were implemented for global localization: computation of fixed estimates and computation of the displacement vector via single differences. A SLAM algorithm was developed to self-localize vehicles using the onboard sensors including data from wheel encoders, lidars, the GNSS fix, and the GNSS single differences displacement vector which renders an occupancy map online used by the navigation system. The navigation system was integrated with the previous components achieving autonomous navigation. Given the map and the localization provided by the SLAM algorithm, the trajectory planner designs collision free trajectories along the map. Specific high and low level controllers were designed for the port vehicle. Collision avoidance uses data directly from the sensors in real time with the objective of avoiding dynamic obstacles not included in the initial map. The GIS solution interfaced to existing TOS via a well-established interface providing vehicle geolocation on yard map as well as continuous monitoring of vehicles load status. The system includes a Planning module providing job assignments to port vehicles and their routing, taking into account collision avoidance criteria. GNSS-related and cyber-attack countermeasures were developed by a software solution for auto-detection of spoofing/jamming attacks of the GNSS signal and identifying measures to enforce the IT security taking into account the pertaining guidelines from ISO 27000 family. GNSS signal threats (i.e. jamming, spoofing) are detected looking for signal anomaly. Detection algorithms were selected in compliance with relevant regulations and implemented using a GNSS software-defined receiver and tested progressively by functional testing of jamming and spoofing detection.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

The progress beyond the SoA includes the following: (i) Precise GNSS is commercially available and has become an enabler for plenty of new applications and research. However, it faces certain limitations when applied in challenging realistic scenarios. The signal in port is highly affected and degraded due to multi-path and occlusion. The levels of accuracy required for interaction with the port environments calls for additional localization means that support and complement the localization accuracy of GNSS. On the other hand, sensor-based localization such as visual odometry and laser SLAM have been demonstrated with reasonable good performance in research projects and there have already been attempts to fuse GNSS and inertial mesurements for robotics applications in controlled scenarios. LOGIMATIC integrates EGNSS (GALILEO and EGNOS) and in-vehicle mounted sensors to provide real time localization enabling autonomous driving of port vehicles in realistic scenarios. The fusion of multiple sensors aims at increasing the Required Navigation Performance (RPN) indicators and provide the system with a continuously available and reliable navigation solution. (ii) One of the key issues underlying to the need of having a reliable solution is the provision of a certain level of security to ensure that the signal will not be spoofed or corrupted. In particular, the requirement of a measure that indicates with what level of confidence a navigation information may be used constitutes a key factor to achieve position reliability and at the same time an effective way to fully exploit the strength of the applications and services offered by GALILEO. LOGIMATIC uses mathematical approaches for detecting and reducing interference and/or trajectory disturbances by the combined use of multiple GNSS signals and integrity information. In such way, the space-time cross-correlation is exploited for assessing signal coherency, trust and reliability of signal parameters. (iii) Existing TOS solutions handle the overall assignment of container movement orders to Container Handling Equipment and monitor the execution of the order. The operations are performed based on specific plans for container movements as defined through Yard stacking planning of a TOS. Different approaches are followed by TOS solutions for container movement assignments and most of them do not use the localization for planning due to the lack of information. LOGIMATIC allows for improved planning of vehicles' movements within the yard and an overall monitoring of logistics by developing a GIS-based solution with welldefined interfaces to existing TOS in order to get all needed information and which in turn handles all needed routing of the CHE to ensure optimized path planning and monitoring.

Project concept

Container Handling Equipment

LOGIMATIC cabin