scholarly journals Evaluating Localization Accuracy of Automated Driving Systems

Sensors ◽  
2021 ◽  
Vol 21 (17) ◽  
pp. 5855
Author(s):  
Karl Rehrl ◽  
Simon Gröchenig
Keyword(s):  
Ground Truth ◽  
Vehicle Body ◽  
Automated Driving ◽  
High Definition ◽  
Localization Accuracy ◽  
Confidence Levels ◽  
Accurate Localization ◽  
Localization Test ◽  
Pros And Cons ◽  
Localization Systems

Automated driving systems are in need of accurate localization, i.e., achieving accuracies below 0.1 m at confidence levels above 95%. Although during the last decade numerous localization techniques have been proposed, a common methodology to validate their accuracies in relation to a ground-truth dataset is missing so far. This work aims at closing this gap by evaluating four different methods for validating localization accuracies of a vehicle’s position trajectory to different ground truths: (1) a static driving-path, (2) the lane-centerline of a high-definition (HD) map with validated accuracy, (3) localized vehicle body overlaps of the lane-boundaries of a HD map, and (4) longitudinal accuracy at stop points. The methods are evaluated using two localization test datasets, one acquired by an automated vehicle following a static driving path, being additionally equipped with roof-mounted localization systems, and a second dataset acquired from manually-driven connected vehicles. Results show the broad applicability of the approach for evaluating localization accuracy and reveal the pros and cons of the different methods and ground truths. Results also show the feasibility of achieving localization accuracies below 0.1 m at confidence levels up to 99.9% for high-quality localization systems, while at the same time demonstrate that such accuracies are still challenging to achieve.

Reducing Tracking Error in RFID Real-Time Localization Systems Using Kalman Filters

2014 ◽  
Vol 5 (3) ◽  
pp. 1-24
Author(s):  
Benjamin Sanda ◽  
Ikhlas Abdel-Qader ◽  
Abiola Akanmu
Keyword(s):  
Real Time ◽  
Radio Frequency Identification ◽  
Kalman Filters ◽  
Tracking Error ◽  
Time Of Arrival ◽  
Indoor Environments ◽  
Real World Data ◽  
Localization Accuracy ◽  
Accurate Localization ◽  
Localization Systems

The use of Radio Frequency Identification (RFID) has become widespread in industry as a means to quickly and wirelessly identify and track packages and equipment. Now there is a commercial interest in using RFID to provide real-time localization. Efforts to use RFID technology in this way experience localization errors due to noise and multipath effects inherent to these environments. This paper presents the use of both linear Kalman filters and non-linear Unscented Kalman filters to reduce the error rate inherent to real-time RFID localization systems and provide more accurate localization results in indoor environments. A commercial RFID localization system designed for use by the construction industry is used in this work, and a filtering model based on 3rd order motion is developed. The filtering model is tested with real-world data and shown to provide an increase in localization accuracy when applied to both raw time of arrival measurements as well as final localization results.

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.

Accuracy analysis of BLE beacon-based localization in smart buildings

2021 ◽  
pp. 1-20
Author(s):  
Rosen Ivanov
Keyword(s):  
Use Case ◽  
Accuracy Analysis ◽  
Localization Algorithm ◽  
Computing Power ◽  
Smart Buildings ◽  
Localization Accuracy ◽  
Positioning Systems ◽  
Deployment Strategy ◽  
Accurate Localization ◽  
Localization Algorithms

The majority of services that deliver personalized content in smart buildings require accurate localization of their clients. This article presents an analysis of the localization accuracy using Bluetooth Low Energy (BLE) beacons. The aim is to present an approach to create accurate Indoor Positioning Systems (IPS) using algorithms that can be implemented in real time on platforms with low computing power. Parameters on which the localization accuracy mostly depends are analyzed: localization algorithm, beacons’ density, deployment strategy, and noise in the BLE channels. An adaptive algorithm for pre-processing the signals from the beacons is proposed, which aims to reduce noise in beacon’s data and to capture visitor’s dynamics. The accuracy of five range-based localization algorithms in different use case scenarios is analyzed. Three of these algorithms are specially designed to be less sensitive to noise in radio channels and require little computing power. Experiments conducted in a simulated and real environment show that using proposed algorithms the localization accuracy less than 1 m can be obtained.

Dosimetric and localization accuracy of Elekta high definition dynamic radiosurgery

2018 ◽  
Vol 54 ◽  
pp. 146-151 ◽  
Author(s):  
Daniel L. Saenz ◽  
Ying Li ◽  
Karl Rasmussen ◽  
Sotirios Stathakis ◽  
Evangelos Pappas ◽  
...  
Keyword(s):  
High Definition ◽  
Localization Accuracy

scholarly journals DSCP: Depthwise Separable Convolution-Based Passive Indoor Localization Using CSI Fingerprint

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Chong Han ◽  
Wenjing Xun ◽  
Lijuan Sun ◽  
Zhaoxiao Lin ◽  
Jian Guo
Keyword(s):  
Indoor Localization ◽  
Wireless Sensing ◽  
Training Phase ◽  
Training Time ◽  
Localization Accuracy ◽  
Localization System ◽  
Complex Models ◽  
Indoor Scenarios ◽  
Trained Network ◽  
Localization Systems

Wi-Fi-based indoor localization has received extensive attention in wireless sensing. However, most Wi-Fi-based indoor localization systems have complex models and high localization delays, which limit the universality of these localization methods. To solve these problems, a depthwise separable convolution-based passive indoor localization system (DSCP) is proposed. DSCP is a lightweight fingerprint-based localization system that includes an offline training phase and an online localization phase. In the offline training phase, the indoor scenario is first divided into different areas to set training locations for collecting CSI. Then, the amplitude differences of these CSI subcarriers are extracted to construct location fingerprints, thereby training the convolutional neural network (CNN). In the online localization phase, CSI data are first collected at the test locations, and then, the location fingerprint is extracted and finally fed to the trained network to obtain the predicted location. The experimental results show that DSCP has a short training time and a low localization delay. DSCP achieves a high localization accuracy, above 97%, and a small median localization distance error of 0.69 m in typical indoor scenarios.

scholarly journals Static and Dynamic Evaluation of an UWB Localization System for Industrial Applications

Sci ◽  
2020 ◽  
Vol 2 (1) ◽  
pp. 7 ◽  
Author(s):  
Mickaël Delamare ◽  
Remi Boutteau ◽  
Xavier Savatier ◽  
Nicolas Iriart
Keyword(s):  
Motion Capture ◽  
Indoor Environment ◽  
Indoor Localization ◽  
Ground Truth ◽  
Industrial Applications ◽  
Ultra Wideband ◽  
Complex Environments ◽  
Experimental Protocol ◽  
Localization Systems ◽  
Do So

Many applications in the context of Industry 4.0 require precise localization. However, indoor localization remains an open problem, especially in complex environments such as industrial environments. In recent years, we have seen the emergence of Ultra WideBand (UWB) localization systems. The aim of this article is to evaluate the performance of a UWB system to estimate the position of a person moving in an indoor environment. To do so, we implemented an experimental protocol to evaluate the accuracy of the UWB system both statically and dynamically. The UWB system is compared to a ground truth obtained by a motion capture system with a millimetric accuracy.

scholarly journals Comparison of Tracking Techniques on 360-Degree Videos

2019 ◽  
Vol 9 (16) ◽  
pp. 3336 ◽  
Author(s):  
Tzu-Wei Mi ◽  
Mau-Tsuen Yang
Keyword(s):  
Augmented Reality ◽  
Object Tracking ◽  
Ground Truth ◽  
Physical Object ◽  
Future Research ◽  
Scale Change ◽  
Tracking Algorithms ◽  
Viewpoint Change ◽  
Pros And Cons

With the availability of 360-degree cameras, 360-degree videos have become popular recently. To attach a virtual tag on a physical object in 360-degree videos for augmented reality applications, automatic object tracking is required so the virtual tag can follow its corresponding physical object in 360-degree videos. Relative to ordinary videos, 360-degree videos in an equirectangular format have special characteristics such as viewpoint change, occlusion, deformation, lighting change, scale change, and camera shakiness. Tracking algorithms designed for ordinary videos may not work well on 360-degree videos. Therefore, we thoroughly evaluate the performance of eight modern trackers in terms of accuracy and speed on 360-degree videos. The pros and cons of these trackers on 360-degree videos are discussed. Possible improvements to adapt these trackers to 360-degree videos are also suggested. Finally, we provide a dataset containing nine 360-degree videos with ground truth of target positions as a benchmark for future research.

Improved Obstacle Mitigation and Localization Accuracy in Narrowband Ultrasonic Localization Systems Using RoBCUL Algorithm

2020 ◽  
Vol 69 (5) ◽  
pp. 2315-2324
Author(s):  
Sebastian Haigh ◽  
Janusz Kulon ◽  
Adam Partlow ◽  
Paul Rogers ◽  
Colin Gibson
Keyword(s):  
Localization Accuracy ◽  
Localization Systems
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