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1		-Theses.Topics for Student Theses.WebHome
	1	+Theses.Current Theses.WebHome

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1		-The REAKT project (https://reakt.sh/ & https://www.schiene-m-l.de/) aims at developing new mobility concepts to reactivate rural rail lines. This project will evolve around developing an autonomous rail vehicle, the **REAKTOR**, to flexibly provide on-demand service on single track lines. A prototype will be build in 1:32 scale for 45 mm gauge, as well as a full scale version for the railway track Malente-Lütjenburg.
	1	+The REAKT project (https://reakt.sh/ & https://www.schiene-m-l.de/) aims at developing new mobility concepts to reactivate rural rail lines. This project will evolve around developing an autonomous on-demand rail vehicle to flexibly provide service on single track lines. The **REAKTOR**. A prototype will be build in 1:32 scale, as well as a full scale version for the railway track Malente-Lütjenburg.
2	2
3	3	[[image:image-20240912102452-3.jpeg||height="219" width="292"]][[image:image-20240912102840-4.jpeg||height="217" width="264"]]
4	4
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.//
	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 in 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		-**The solutions in all topics must be scalable for both demonstrators!**
	9	+**The solutions in all topics should 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]])
...	...	@@ -30,78 +30,40 @@
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