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Design of a simulation environment for testing the operation of autonomous vehicles
Šůstek, Jan ; Krejsa, Jiří (referee) ; Věchet, Stanislav (advisor)
This thesis deals with the design of simulation environment for testing autonomous vehicles. In the theoretical part, the search of available autonomous driving simulators was carried out. Furthermore, the tools commonly used in autonomous vehicles such as sensors or software modules were presented. In the practical part, the CARLA simulator was selected from the available solutions. Firstly, the installation of CARLA simulator is explained. Then, the simulation map was created by the Roadrunner to simulate a specific street in Brno. Afterwards, the work with the CARLA simulator is shown. Finally, the work with the CARLA simulator is evaluated and the concrete outputs of simulation are shown.
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Neural networks used in autonomous vehicles
Ryšavý, Jan ; Píštěk, Václav (referee) ; Kučera, Pavel (advisor)
This bachelor thesis deals with the use of neural networks in autonomous vehicles. The first part of the thesis presents the basic principles of neural networks and learning methods that are used in autonomous vehicles. Then the thesis describes the architecture and functions of neural networks. The second part of the thesis also describes the different types of autonomous vehicles, their classifications and an overview of the sensors used by autonomous vehicles. The last part of the thesis deals with the implementation of neural networks in ECUs using programming languages and libraries, and applications such as object detection and marker recognition.
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Využití umělé inteligence pro autonomní řízení vozidel
TUPÝ, Ondřej
The diploma thesis deals with the contribution of autonomous management to the development of transport. The work describes and explains the basic principles and ideas of autonomous management as one of the solutions to the environment and improve the traffic situation in the Czech Republic and in the world.
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Acquisition of inputs by image processing for controlling an autonomous vehicle
Midrla, Daniel ; Píštěk, Václav (referee) ; Kučera, Pavel (advisor)
This master’s thesis deals with data acquisition by image processing in order to control an autonomous vehicle. Firstly, the thesis offers a summary of theoretical knowledge relevant to the given topic. Then follows a description of creating an algorithm, which acquires basic inputs for autonomous vehicle control with the use of a stereo camera and an object detection neural network. The inputs gained from this algorithm are the class of the detected object and its distance. Finally, an experimental evaluation of the correct functionality is performed with an emphasis on optimizing the accuracy and range of the distance computation. An assessment of the ability to deploy the created algorithm in real time on a compact computer with limited computing power is also performed.
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Automatic On-Line Calibration and Calibration Monitoring of Cameras and Lidars
Moravec, Jaroslav ; Šikudová, Elena (advisor) ; Obdržálek, Štěpán (referee)
Title: Automatic On-Line Calibration and Calibration Monitoring of Cameras and Lidars Author: Jaroslav Moravec Department: Department of Software and Computer Science Education Supervisor: doc. RNDr. Elena Šikudová, Ph.D., Department of Software and Computer Science Education Abstract: Cameras and LiDARs are important devices in the automotive indus- try as their combination provides useful information (3D coordinates of a point, its colour and intensity) for perception, localization, mapping and prediction. Successful data fusion and interpretation requires accurate calibration of intrin- sic parameters of the sensors and their 6D relative pose. In this thesis, we present a target-less calibration method on three different calibration tasks. The solu- tion is based on a robust likelihood function constructed over the reprojection error of LiDAR edges relative to image edges. When the calibration slowly wears off, our online recalibration procedure can jointly follow the extrinsic calibration drift with an average error of 0.13◦ in rotation and 4 cm in translation. Based on this recalibration tool, we are also able to monitor the calibration and detect an abrupt decalibration in a couple of seconds. And we also present a fully automatic calibration routine that estimates both the extrinsic and intrinsic...
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Overview Of Approaches To Multisensor Fusion As Used In Adas And Av
Zemčík, Tomáš
This paper briefly summarises the state-of-the-art in the field of approaches to heterogeneous multisensory fusion as in use in autonomous vehicles and advanced driver assistance systems (ADAS). It first describes the basic perception principles, goes over the used sensors and their properties. Various approaches to sensor fusion are then explained with particular focus on their effects on road traffic safety. Conclusions suggest the most perspective approaches and possible improvements.
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Autonomous vehicles testing
Nágl, Jiří ; Tobiáš, Martin (referee) ; Porteš, Petr (advisor)
The aim of this bachelor’s thesis is the research of autonomous vehicles and their testing. In the first part, the work focuses on autonomous vehicles and connectivity between them. Subsequently, it deals with testing of autonomous vehicles on proving grounds and testing in real world. The last chapter includes virtual testing and dedicated software.
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Design of traffic sign detector using image processing methods
Šmíd, Josef ; Adámek, Roman (referee) ; Věchet, Stanislav (advisor)
This master thesis deals with the design of a traffic sign detector using the image processing methods. The OpenCV library for working with images in programming language Python is used for this. The first part reports on the using methods. In the next part, these methods were tested on images of traffic signs taken in traffic in different lighting conditions. The results of these tests led to the design of optimal methods and their settings, which were re-verified by verifying on video of driving in traffic. This also revealed the conditions under which they can operate in real-time systems. Finally, an optimization algorithm for compensation of detection errors was proposed from the monitoring of detection waveforms.
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Automatic On-Line Calibration and Calibration Monitoring of Cameras and Lidars
Moravec, Jaroslav ; Šikudová, Elena (advisor) ; Obdržálek, Štěpán (referee)
Title: Automatic On-Line Calibration and Calibration Monitoring of Cameras and Lidars Author: Jaroslav Moravec Department: Department of Software and Computer Science Education Supervisor: doc. RNDr. Elena Šikudová, Ph.D., Department of Software and Computer Science Education Abstract: Cameras and LiDARs are important devices in the automotive indus- try as their combination provides useful information (3D coordinates of a point, its colour and intensity) for perception, localization, mapping and prediction. Successful data fusion and interpretation requires accurate calibration of intrin- sic parameters of the sensors and their 6D relative pose. In this thesis, we present a target-less calibration method on three different calibration tasks. The solu- tion is based on a robust likelihood function constructed over the reprojection error of LiDAR edges relative to image edges. When the calibration slowly wears off, our online recalibration procedure can jointly follow the extrinsic calibration drift with an average error of 0.13◦ in rotation and 4 cm in translation. Based on this recalibration tool, we are also able to monitor the calibration and detect an abrupt decalibration in a couple of seconds. And we also present a fully automatic calibration routine that estimates both the extrinsic and intrinsic...
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