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Autonomous emergency manoeuvring and movement monitoring for road transport security

Periodic Reporting for period 1 - TransSec (Autonomous emergency manoeuvring and movement monitoring for road transport security)

Reporting period: 2018-02-01 to 2019-07-31

The TransSec project addresses a new danger in European countries, the increasing number of attacks conducted with road vehicles. Today the latest truck safety systems can prevent the most serious kinds of road accidents. They fail however in case of collisions that are intentionally caused by the driver. TransSec aims to initiate the development of supplementing security modules.
Project objective: Development and evaluation of systems built-in or to be used by trucks for secure road transport of (dangerous) goods. Preventing trucks and transport of goods to be misused for other purposes that may cause serious damages.

Specific objectives:
• Precise vehicle positioning and navigation on road (lane) and off road
• Vehicle movement monitoring for dangerous goods with critical area alarm/eCall
• Vehicle communication security for critical information exchange
• Onboard precrash environment detection of vulnerable objects on and off road
• Non-defeatable autonomous emergency manoeuvring for crash prevention on and off road

TransSec is therefore a substantial contribution to improve road transport safety and security.
1. Precise vehicle positioning and navigation using satellite navigation including the european global navigation satellite system Galileo.
A positioning quality requirements analysis has been conducted with the TransSec use cases. A Galileo Positioning System has been developed. The focus was on a multi-frequency, multi-constellation measurement engine that provides GNSS pseudorange, carrier phase and Doppler observations to a Kalman filter which estimates the state of the vehicle. Authentication of GNSS Signals, additional measures against sensor manipulation and spoofing proection has been developed. A test of leading GNSS receivers, positioning services, inertial navigation systems and onboard sensors has been conducted in a truck driving on public roads. An integrated positioning system for trucks has been build up.

2. Road and Environment Map
Road and environment map uses a commercial map navigation enhanced with additional information. The availability of map geometry, topology and attributes has been investigated and the assessment of geometric map accuracies has been carried out using GNSS-based reference trajectories. Existing map-matching algorithms and electronic horizon providers have been analysed and extended to support TransSec use cases with focus on illegal path identification. Map-Aiding has been develop to replace classical map-matching algorithm.

3. Environment Object Detection
The first task focused on the specification of traffic scene monitoring vehicle-mounted sensors, recording hardware and software development, and integration for data recording and synchronisation as well as meta-data generation. The second task on real-time 3D visual scene reconstruction and static/dynamic object determination uses visual Simultaneous Localisation and Mapping (v-SLAM) Technology to construct a real-time 3D model of the scene surrounding the vehicle. The developed reconstruction approach based on the LiDAR data is able to obtain vehicle relative motion (odometry) and sparse 3D point clouds of vehicle surroundings.

4. Vehicle Movement Monitoring
Vehicle movement monitoring provides two security modules, a map-based movement monitoring with critical area alarm and a driving situation analysis and classification based on dynamic environment sensing. The first task movement monitoring with critical area alarm/eCall uses driving restrictions to identify illegal paths, identify critical areas and launching an alarm. The second task driving situation analysis and classification comprises definition of risk situations to detect in the context of TransSec.

5. V-2-X Communication
Task Risk Communication and Protocols Requirements specified the overall system architecture and summarized the relevant techniques and standards that could be used. Task Risk communication to Entities (V2X) included vehicle to vehicle (V2V) communications, vehicle to pedestrian (V2P) communications and also vehicle to infrastructure (V2I) communications. Task V2X Security and Data Protection addressed security and privacy issues and specified the security architecture and protection services for ITS communications. Task Alert /eCall Service started the integration of the European eCall system into V-2-X communication System.

6. Vehicle Integration and Testing
A methodology for testing and validation was developed and documented to support the forthcoming activities in year 2 and 3. Year 1 Test and Demo Precise Vehicle Positioning results:
• Multi-Constellation, multi-frequency GNSS receivers provide locally a sufficient number of satellites under difficult conditions with reliable positioning on a road.
• Galileo satellites improve reliable and accurate positioning.
• Multi-Constellation GNSS receivers with Positioning Services provide positioning accuracy on centimeter level.
• Routes with tunnels need Multi-Constellation GNSS receivers with dead reckoning or inertial navigation for continuous positioning.
• Reliable positioning accuracy on decimeter level currently achievable with positioning services.
• Future Galileo Service with 20 cm accuracy provides required decimeter accuracy.
Testing of available new GNSS Receivers, positioning services and inertial navigation systems will be continued. Expected results: Cost efficient automotive positioning system and a precise autonomous positioning system.

Map-Aiding will be completed and replace map-matching of electronic horizon provider. Expected result: 360 degree electronic horizon provider.

Real-time detection and classification of static and dynamic objects will be completed. Expected result: Reliable detection of obstacles, vehicles and any kind of vulnerable objects around the vehicle.

The static data of 360 degree electronic horizon provider will be fused with dynamic data from onboard radar, camera and Lidar sensors. Expected result: Onboard, realtime local dynamic map.

Based on the local dynamic map the situation-specific prediction of context evolution and identification of potential collisions will be implemented. Expected result: Collision warning system for complex traffic situations.

V-2-X communication implementation is completed with pedestrians, infrastructure alarms using eCall. Expected result: Secure vehicle communication system.

Autonomous emergency manoeuvres for collision prevention will be implementied. Expecte result: Automated collision prevention system for accidental and intentional collisions.

Beyond state of the is precise vehicle positioning, sensor data fusion in a local dynamic map, V-2-X communication including eCall and automated collison prevention covering intentional collisions.

The prevention of collisions will further reduce damages caused by road traffic and transport of goods. Road safety and security in public areas is improved.
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