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From version < 36.1 >
edited by Alexander Schulz-Rosengarten
on 2024/09/30 08:25
To version < 25.1 >
edited by Alexander Schulz-Rosengarten
on 2024/09/12 10:08
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1 -Theses.Topics for Student Theses.WebHome
1 +Theses.Current Theses.WebHome
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4 4  
5 5  //(left) a railbike, the foundation of the upcoming autonomous draisine & (right) a stripped down [[LGB>>https://www.lgb.de/lp/20/willkommen-bei-lgb]] engine for a 45mm model track.//
6 6  
7 -{{info}}
8 -Kick-off meeting on Monday 7th Oct. at 10am in room 1115 CAP4
9 -{{/info}}
10 -
11 11  == Overview of topics (WIP) ==
12 12  
13 13  **The solutions in all topics must be scalable for both demonstrators!**
14 14  
15 -~1. An end-user app and management system for on-demand train service **[(partially) reserved]**
11 +~1. An end-user app and management system for on-demand train service
16 16  // This topic may be split up into two theses (app & management)//
17 17  
18 18  * A mobile app to call a train to a desired location and communicate desired destination
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22 22  * Provisions for passenger transfer on open track ("Begegnungsverkehr", see concept art [[here>>https://cloud.rz.uni-kiel.de/index.php/s/ZMZSoLTerJCJi7L]])
23 23  * The inter train communication concept maybe based on a central or decentralized structure
24 24  
25 -2. An autonomous train controller with risk analysis using STPA **[already reserved]**
21 +2. An autonomous train controller with risk analysis using STPA
26 26  
27 27  * Control of an autonomous passenger train model (conceptually working for both demonstrators)
28 28  * Capability for passenger transfer on open track (safe docking procedure; "Begegnungsverkehr", see concept art [[here>>https://cloud.rz.uni-kiel.de/index.php/s/ZMZSoLTerJCJi7L]])
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30 30  * Safe behavior model generation using PASTA ([[https:~~/~~/marketplace.visualstudio.com/items?itemName=kieler.pasta>>https://marketplace.visualstudio.com/items?itemName=kieler.pasta]])
31 31  * Assumes preprocessed sensor input and destination determination (see other topics)
32 32  
33 -3. AI-based obstacle detection for autonomous train control using image recognition
29 +3. AI-based image recognition for autonomous train control
34 34  // This topic will be jointly advised with the AG Distributed Systems//
35 35  
36 -* Sensor processing of a train-mounted camera to detect objects (potential obstacles)
37 -* Tasks will involve:
38 -** Sensor mounting on the demonstrator
39 -** Collection of data (images, videos)
40 -** Labeling of data to enable training (esp. for small scale model)
41 -** Training of AI
42 -** Evaluation of quality
43 -** Live testing
44 -* Step-wise evaluation of the influence of vehicle speed on the detection quality
45 -* Evaluate applicability and influence of training data due to different environments for the demonstrators (i.e. indoors vs. outdoors)
46 -* (Optional) Trajectory detection to categorize safety threads of moving obstacles
47 -* (Optional) Evaluate performance on different hardware, e.g. Rasberry Pi vs. AI hardware
48 -* (Optional) Test and evaluate on the edge deployment
49 -* For interfacing with the controller, the sensor should provide an assessment how safe the area in front of the train is, such that the controller can adjust its speed.
32 +* Sensor processing of a train mounted camera
33 +* Obstacle detection at speeds up to 50 km/h
50 50  * Potential hardware (subject to changes):
51 51  ** [[https:~~/~~/www.raspberrypi.com/documentation/accessories/camera.html>>https://www.raspberrypi.com/documentation/accessories/camera.html]]
52 52  ** (((
53 -[[https:~~/~~/www.axis.com/de-de/products/axis-p1455-le>>https://www.axis.com/de-de/products/axis-p1455-le]]
37 +https:~/~/www.axis.com/de-de/products/axis-p1455-le
54 54  )))
39 +* [Optional] Distance measuring using multiple cameras
55 55  
56 -4. Classic and AI-based distance sensing for autonomous train control using different sensors
41 +4. AI-based sensor processing for autonomous train control
57 57  // This topic will be jointly advised with the AG Distributed Systems//
58 58  
59 -* Explore and evaluate different sensors and processing techniques for distance measuring in rail vehicles
60 -* Compare quality, ranges, and reliability w.r.t speed and size (demonstrator)
61 -* Sensors and approaches:
62 -*1. Ultrasonic sensor
63 -*1. Single camera with AI image recognition
64 -*1. (Multiple cameras)
65 -*1. (LiDAR)
66 -*1. (Sensorfusion)
44 +* Sensor processing of train mounted LiDAR or ultrasonic sensor
67 67  * Potential hardware (subject to changes):
68 68  ** [[https:~~/~~/www.elektronik-kompendium.de/sites/praxis/bauteil_ultrasonic-hcsr04p.htm>>https://www.elektronik-kompendium.de/sites/praxis/bauteil_ultrasonic-hcsr04p.htm]]
69 69  ** [[https:~~/~~/www.pi-shop.ch/lidar-ld06-lidar-module-with-bracket-entwicklungskit-fuer-raspberry-pi-sbc>>https://www.pi-shop.ch/lidar-ld06-lidar-module-with-bracket-entwicklungskit-fuer-raspberry-pi-sbc]]
70 70  ** (((
71 -[[https:~~/~~/www.blickfeld.com/de/produkte/cube-1/>>https://www.blickfeld.com/de/produkte/cube-1/]]
49 +https:~/~/www.blickfeld.com/de/produkte/cube-1/
72 72  )))
51 +* Obstacle detection at speeds up to 50 km/h
52 +* Distance measuring (ultrasonic sensor)
73 73  
74 -5. A digital twin for an autonomous on-demand train service **[already reserved]**
75 -// Note: Tight interfacing with other topics//
54 +5. A digital twin for an autonomous on-demand train service
55 + // Note: Tight interfacing with other topics//
76 76  
77 77  * A digital twin for an autonomous passenger train
78 78  * Monitoring system for the state and location of the vehicle
79 -* Simulation capabilities to test and replay behavior (virtual environment)
59 +* Remote control capabilities //(interfacing with controller)//
80 80  * Monitoring and economic analysis of on-demand service operation (//integration/interfacing of management system//)
81 81  * Reliability analysis/statistics to ensure transparency of autonomous operation
82 82  
83 -6. Remote control for rail vehicles
84 -//Note: Tight interfacing with other topics//
85 -
86 -* Remote control of speed and brakes //(interfacing with controller)//
87 -* Live streaming of camera data and other sensors
88 -* Evaluation and setup of a wireless communication network with a high reliability
89 -* (Optional) Construction of a [[remote control panel>>https://cloud.rz.uni-kiel.de/index.php/s/jCxitwKzddqEctD]]
90 -* (Optional) Augmented reality integration to simulate training scenarios
91 -
92 -7. A standalone sensor box for monitoring rail vehicles **[already reserved]**
93 -//This prototype will be tested (only) using the full-scale demonstrator and is intended for monitoring non-autonomous vehicles (not the REAKTOR)//
94 -
95 -* Development of a sensor array to monitor rail vehicle operation
96 -* It should serve as a plugin solution inside the train's cockpit for monitoring operation and as preparation for autonomous control
97 -* Design for wireless communication of collected data
98 -* Possible sensors:
99 -** GPS
100 -** Accelerometer
101 -** Camera
102 -* Analysis of data for autonomous driving
103 -* Potential integration into digital twin infrastructure
104 -
105 105  == Goals ==
106 106  
107 107  * TBA for each topic individually