scholarly journals Motorway Measurement Campaign to Support R&D Activities in the Field of Automated Driving Technologies

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2169
Author(s):  
Viktor Tihanyi ◽  
Tamás Tettamanti ◽  
Mihály Csonthó ◽  
Arno Eichberger ◽  
Dániel Ficzere ◽  
...  
Keyword(s):  
Ground Truth ◽  
Global Navigation Satellite Systems ◽  
Sensor Data ◽  
Automated Driving ◽  
High Definition ◽  
Data Set ◽  
Measurement Campaign ◽  
Satellite Systems ◽  
Road Geometry ◽  
Global Navigation Satellite

A spectacular measurement campaign was carried out on a real-world motorway stretch of Hungary with the participation of international industrial and academic partners. The measurement resulted in vehicle based and infrastructure based sensor data that will be extremely useful for future automotive R&D activities due to the available ground truth for static and dynamic content. The aim of the measurement campaign was twofold. On the one hand, road geometry was mapped with high precision in order to build Ultra High Definition (UHD) map of the test road. On the other hand, the vehicles—equipped with differential Global Navigation Satellite Systems (GNSS) for ground truth localization—carried out special test scenarios while collecting detailed data using different sensors. All of the test runs were recorded by both vehicles and infrastructure. The paper also showcases application examples to demonstrate the viability of the collected data having access to the ground truth labeling. This data set may support a large variety of solutions, for the test and validation of different kinds of approaches and techniques. As a complementary task, the available 5G network was monitored and tested under different radio conditions to investigate the latency results for different measurement scenarios. A part of the measured data has been shared openly, such that interested automotive and academic parties may use it for their own purposes.

scholarly journals Motorway Measurement Campaign to Support R&D Activities in the Field of Automated Driving Technologies

2021 ◽  
Author(s):  
Viktor Tihanyi ◽  
Tettamanti Tamás ◽  
Mihály Csonthó ◽  
Arno Eichberger ◽  
Dániel Ficzere ◽  
...  
Keyword(s):  
Ground Truth ◽  
Global Navigation Satellite Systems ◽  
Added Value ◽  
Sensor Data ◽  
Automated Driving ◽  
High Definition ◽  
Measurement Campaign ◽  
Satellite Systems ◽  
Road Geometry ◽  
Global Navigation Satellite

The paper presents the measurement campaign carried out on a real-world motorway stretch of Hungary with the participation of both industrial and academic partners from Austria and Hungary. The measurement included vehicle based as well as infrastructure based sensor data. The obtained results will be extremely useful for future automotive R&D activities due to the available ground truth for static and dynamic content. The aim of the measurement campaign was twofold. On the one hand, road geometry was mapped with high precision in order to build Ultra High Definition (UHD) map of the test road. On the other hand, the vehicles - equipped with differential Global Navigation Satellite Systems (GNSS) for ground truth localization - carried out special test scenarios while collecting detailed data using different sensors. All test runs were recorded by both vehicles and infrastructure. As a complementary task, the available 5G network was monitored and tested. The paper also showcases application examples based on the measurement campaign data, in which the added value of having access to the ground truth labeling and the created UHD map of the motorway section becomes apparent. In order to present our work transparently, a part of the measured data have been shared openly such that interested automotive as well as academic parties may use it for their own purposes.

scholarly journals Seamless Vehicle Positioning by Lidar-GNSS Integration: Standalone and Multi-Epoch Scenarios

2021 ◽  
Vol 13 (22) ◽  
pp. 4525
Author(s):  
Junjie Zhang ◽  
Kourosh Khoshelham ◽  
Amir Khodabandeh
Keyword(s):  
Autonomous Driving ◽  
Measurement Model ◽  
Urban Environments ◽  
Global Navigation Satellite Systems ◽  
High Definition ◽  
Satellite Systems ◽  
The Road ◽  
Gnss Receivers ◽  
Vehicle Positioning ◽  
Global Navigation Satellite

Accurate and seamless vehicle positioning is fundamental for autonomous driving tasks in urban environments, requiring the provision of high-end measuring devices. Light Detection and Ranging (lidar) sensors, together with Global Navigation Satellite Systems (GNSS) receivers, are therefore commonly found onboard modern vehicles. In this paper, we propose an integration of lidar and GNSS code measurements at the observation level via a mixed measurement model. An Extended Kalman-Filter (EKF) is implemented to capture the dynamic of the vehicle movement, and thus, to incorporate the vehicle velocity parameters into the measurement model. The lidar positioning component is realized using point cloud registration through a deep neural network, which is aided by a high definition (HD) map comprising accurately georeferenced scans of the road environments. Experiments conducted in a densely built-up environment show that, by exploiting the abundant measurements of GNSS and high accuracy of lidar, the proposed vehicle positioning approach can maintain centimeter-to meter-level accuracy for the entirety of the driving duration in urban canyons.

scholarly journals DESIGN AND VALIDATION OF A SURFACE PROFILING APPARATUS FOR AGRICULTURAL TERRAIN ROUGHNESS MEASUREMENTS

2019 ◽  
Vol 59 (3) ◽  
pp. 169-180 ◽  
Author(s):  
Jianguo Yan ◽  
Chunguang Wang ◽  
Shengshi Xie ◽  
Lijuan Wang
Keyword(s):  
Global Navigation Satellite Systems ◽  
Sensor Data ◽  
Measurement Unit ◽  
Full Description ◽  
Ongoing Research ◽  
Satellite Systems ◽  
Surface Profiling ◽  
Laser Sensors ◽  
Global Navigation Satellite ◽  
Flat Section

How to accurately and efficiently measure the profiles of the terrain on which agricultural machines operate has been an ongoing research topic. In this study, a surface profiling apparatus (profiler) was developed to measure agricultural terrain profiles along parallel tracks. The profiler is mainly composed of sensor frames, an RTK-GNSS system (Real Time Kinematics-Global Navigation Satellite Systems), laser sensors, an Inertial Measurement Unit (IMU) sensor and a data acquisition system. Along with a full description of how the terrain profiles were produced, a methodology to compensate for the tractor motion was included in the sensor data analysis. In field profiling validation, two trapezoidal bumps with known dimensions were used to assess the ability of the terrain profiler to reproduce the vertical profiles of the bumps, resulting in root mean square error (RMSE) of 3.6-4.7 mm and 4.5-5.1 mm with profiling speeds of 1.02 and 2.56 km/h, respectively. In addition, a validation test was also conducted on an asphalt road by profiling a flat road with the measuring wheels of the profiler rolling on the flat section but with the tractor wheels driving over a trapezoidal bump to excite the tractor pitch and roll motion. The measured profiles then also exhibited a flat road, which showed the ability of the profiler to remove the tractor motion from the profiling measurements.

scholarly journals Comparing atmospheric data and models at station Wettzell during CONT17

2019 ◽  
Vol 50 ◽  
pp. 1-7
Author(s):  
Daniel Landskron ◽  
Johannes Böhm ◽  
Thomas Klügel ◽  
Torben Schüler
Keyword(s):  
Water Vapor ◽  
Mapping Function ◽  
Global Navigation Satellite Systems ◽  
Radiosonde Data ◽  
Data Set ◽  
Mapping Functions ◽  
Satellite Systems ◽  
Long Baseline ◽  
Global Navigation Satellite ◽  
Troposphere Delays

Abstract. During the Continuous Very Long Baseline Interferometry (VLBI) Campaign 2017 (CONT17), carried out from 28 November through 12 December 2017, an extensive data set of atmospheric observations was acquired at the Geodetic Observatory Wettzell. In addition to in situ measurements of temperature, humidity, pressure or wind speed at the surface, radiosonde ascents yielded meteorological parameters continually up to 25 km height, and integrated water vapor (IWV) was obtained at several elevations and azimuths from a water vapor radiometer. Troposphere delays estimated from Global Navigation Satellite Systems (GNSS) observations plus comparative values from two different Numerical Weather Models (NWMs) complete the abundance of data. In this presentation, we compare these data sets to parameters of the Vienna Mapping Functions 1 and 3 (VMF1 & VMF3), which are based on NWM data by the ECMWF, and to estimates of VLBI analysis using the Vienna VLBI and Satellite Software (VieVS). On the one hand, we contrast the variety of troposphere delays in zenith direction with each other, while on the other hand we utilize radiosonde data and meteorological observations at the site to create local mapping functions which can then be compared to VMF3 and VMF1 at Wettzell. In general, we thus received very good accordance between the different solutions. Also in terms of the mapping functions, the local radiosonde mapping function is in consistence with VMF1 and VMF3 with differences less than 5 mm at 5∘ elevation.

scholarly journals Sensitivity of TDS-1 GNSS-R Reflectivity to Soil Moisture: Global and Regional Differences and Impact of Different Spatial Scales

2018 ◽  
Vol 10 (11) ◽  
pp. 1856 ◽  
Author(s):  
Adriano Camps ◽  
Mercedes Vall·llossera ◽  
Hyuk Park ◽  
Gerard Portal ◽  
Luciana Rossato
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Incidence Angle ◽  
Spatial Scales ◽  
Ground Truth ◽  
Global Navigation Satellite Systems ◽  
Satellite Systems ◽  
Left Hand ◽  
The Uk ◽  
Global Navigation Satellite

The potential of Global Navigation Satellite Systems-Reflectometry (GNSS-R) techniques to estimate land surface parameters such as soil moisture (SM) is experimentally studied using 2014–2017 global data from the UK TechDemoSat-1 (TDS-1) mission. The approach is based on the analysis of the sensitivity to SM of different observables extracted from the Delay Doppler Maps (DDM) computed by the Space GNSS Receiver–Remote Sensing Instrument (SGR-ReSI) instrument using the L1 (1575.42 MHz) left-hand circularly-polarized (LHCP) reflected signals emitted by the Global Positioning System (GPS) navigation satellites. The sensitivity of different GNSS-R observables to SM and its dependence on the incidence angle is analyzed. It is found that the sensitivity of the calibrated GNSS-R reflectivity to surface soil moisture is ~0.09 dB/% up to 30° incidence angle, and it decreases with increasing incidence angles, although differences are found depending on the spatial scale used for the ground-truth, and the region. The sensitivity to subsurface soil moisture has been also analyzed using a network of subsurface probes and hydrological models, apparently showing some dependence, but so far results are not conclusive.

scholarly journals Comparison of Different Hardware Configurations for 2D SLAM Techniques Based on Google Cartographer Use Case

2021 ◽  
Author(s):  
Łukasz Sobczak ◽  
Katarzyna Filus ◽  
Joanna Domańska ◽  
Adam Domański
Keyword(s):  
Real Life ◽  
Ground Truth ◽  
Cost Effective ◽  
Global Navigation Satellite Systems ◽  
Use Case ◽  
Indoor Environments ◽  
Satellite Systems ◽  
Localization And Mapping ◽  
Hardware Configuration ◽  
Global Navigation Satellite

Abstract One of the most challenging topics in Robotics is Simultaneous Localization and Mapping (SLAM) in the indoor environments. Due to the fact that Global Navigation Satellite Systems cannot be successfully used in such environments, different data sources are used for this purpose, among others LiDARs (Light Detection and Ranging), which have advanced from numerous other technologies. Other embedded sensors can be used along with LiDARs to improve SLAM accuracy, e.g. the ones available in the Inertial Measurement Units and wheel odometry sensors. Evaluation of different SLAM algorithms and possible hardware configurations in real environments is time consuming and expensive. For that reason, in this paper we evaluate the performance of different hardware configuration used with Google Cartographer SLAM algorithms in simulation framework proposed in 1. Our use case is an actual robot used for room decontamination. The results show that for our robot the best hardware configuration consists of three LiDARs 2D, IMU and wheel odometry sensors. The proposed simulation-based methodology is a cost-effective alternative to real-world evaluation. It allows easy automation and provides access to precise ground truth. It is especially beneficial in the early stages of product design and to reduce the number of necessary real-life tests and hardware configurations.

scholarly journals A High-Accuracy GNSS Dataset of Ground Truth Points Collected within Îles-de-Boucherville National Park, Quebec, Canada

Data ◽  
2021 ◽  
Vol 6 (3) ◽  
pp. 32
Author(s):  
Kathryn Elmer ◽  
Margaret Kalacska
Keyword(s):  
National Park ◽  
Hyperspectral Imagery ◽  
Ground Truth ◽  
High Accuracy ◽  
Global Navigation Satellite Systems ◽  
Validation Data ◽  
Ground Truth Data ◽  
Satellite Systems ◽  
Study Sites ◽  
Global Navigation Satellite

A new ground truth dataset generated with high-accuracy Global Navigation Satellite Systems (GNSS) positional data of the invasive reed Phragmites australis subsp. australis within Îles-de-Boucherville National Park (Quebec, Canada) is described. The park is one of five study sites for the Canadian Airborne Biodiversity Observatory (CABO) and has stands of invasive P. australis spread throughout the park. Previously, within the context of CABO, no ground truth data had been collected within the park consolidating the locations of P. australis. This dataset was collected to serve as training and validation data for CABO airborne hyperspectral imagery acquired in 2019 to assist with the detection and mapping of P. australis. The locations of the ground truth points were found to be accurate within one pixel of the hyperspectral imagery. Overall, 320 ground truth points were collected, representing 158 locations where P. australis was present and 162 locations where it was absent. Auxiliary data includes field photographs and digitized field notes that provide context for each point.

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