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1		-[REAKT] Project REAKTOR
	1	+[REAKT] Projecting Irregular Vehicle Positions on Tracks

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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 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.
	1	+The REAKT DATA project (https://reakt.sh/) includes visualizing rail vehicle positions on the track based on a set of position data from GNNS trackers. These position data are sparse and include errors and variation, yet it can be safely assumed that the rail vehicle will not leave the track in normal operation. Hence, this topic will investigate an algorithm to process the data and project the position of the vehicles onto the track.
2	2
3		-[[image:image-20240912102452-3.jpeg||height="219" width="292"]][[image:image-20240912102840-4.jpeg||height="217" width="264"]]
	3	+[[image:position.png]]
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 in for a 45mm model track.//
	5	+== Goals ==
6	6
7		-== Overview of topics (WIP) ==
	7	+* Develop and implement an algorithm for computing a best-effort projection of a vehicle position on a track
	8	+* Evaluate the algorithm (and potential variants of the algorithm) with the real-world data collected on the Malente-Lütjenburg track
8	8
9		-**The solutions in all topics should scalable for both demonstrators!**
	10	+==== Consiterations for the Algorithm ====
10	10
11		-~1. An end-user app and management system for on-demand train service
12		-// This topic may be split up into two theses (app & management)//
	12	+* Errors in GNNS data
	13	+* Gaps in GNNS data (missing network)
	14	+* Different accuracy of tracking devices (Smartphones vs. dedicated Trackers)
	15	+* Showing estimates of expected movement or potential location areas
	16	+* Handling inconsistencies
	17	+* Unrealistic position jumps
	18	+* Passing other vehicles (quickly) on single-lane track
	19	+* Vehicles changing direction without stopping
13	13
14		-* A mobile app to call a train to a desired location and communicate desired destination
15		-* Locations drawn from GNSS and appropriate abstraction for 1:32 scale for station-less entry or predefined locations
16		-* Management of multiple on-demand trains on a single track line
17		-* Schedules for cooperative passenger pick up
18		-* Provisions for passenger transfer on open track ("Begegnungsverkehr", see concept art [[here>>https://cloud.rz.uni-kiel.de/index.php/s/ZMZSoLTerJCJi7L]])
19		-* The inter train communication concept maybe based on a central or decentralized structure
20		-
21		-2. An autonomous train controller with risk analysis using STPA
22		-
23		-* Control of an autonomous passenger train model (conceptually working for both demonstrators)
24		-* 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]])
25		-* Risk analysis for the controller using STPA ([[http:~~/~~/psas.scripts.mit.edu/home/get_file.php?name=STPA_handbook.pdf>>url:http://psas.scripts.mit.edu/home/get_file.php?name=STPA_handbook.pdf]])
26		-* Safe behavior model generation using PASTA ([[https:~~/~~/marketplace.visualstudio.com/items?itemName=kieler.pasta>>https://marketplace.visualstudio.com/items?itemName=kieler.pasta]])
27		-* Assumes preprocessed sensor input and destination determination (see other topics)
28		-
29		-3. AI-based image recognition for autonomous train control
30		-// This topic will be jointly advised with the AG Distributed Systems//
31		-
32		-* Sensor processing of a train mounted camera
33		-* Obstacle detection at speeds up to 50 km/h
34		-* Potential hardware (subject to changes):
35		-** [[https:~~/~~/www.raspberrypi.com/documentation/accessories/camera.html>>https://www.raspberrypi.com/documentation/accessories/camera.html]]
36		-** (((
37		-https:~/~/www.axis.com/de-de/products/axis-p1455-le
38		-)))
39		-* [Optional] Distance measuring using multiple cameras
40		-
41		-4. AI-based sensor processing for autonomous train control
42		-// This topic will be jointly advised with the AG Distributed Systems//
43		-
44		-* Sensor processing of train mounted LiDAR or ultrasonic sensor
45		-* Potential hardware (subject to changes):
46		-** [[https:~~/~~/www.elektronik-kompendium.de/sites/praxis/bauteil_ultrasonic-hcsr04p.htm>>https://www.elektronik-kompendium.de/sites/praxis/bauteil_ultrasonic-hcsr04p.htm]]
47		-** [[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]]
48		-** (((
49		-https:~/~/www.blickfeld.com/de/produkte/cube-1/
50		-)))
51		-* Obstacle detection at speeds up to 50 km/h
52		-* Distance measuring (ultrasonic sensor)
53		-
54		-5. A digital twin for an autonomous on-demand train service
55		- // Note: Tight interfacing with other topics//
56		-
57		-* A digital twin for an autonomous passenger train
58		-* Monitoring system for the state and location of the vehicle
59		-* Remote control capabilities //(interfacing with controller)//
60		-* Monitoring and economic analysis of on-demand service operation (//integration/interfacing of management system//)
61		-* Reliability analysis/statistics to ensure transparency of autonomous operation
62		-
63		-== Goals ==
64		-
65		-* TBA for each topic individually
66		-
67	67	== Scope ==
68	68
69		-Bachelor's or Master's Thesis, with varying requirements to scientific scope.
	23	+Bachelor's Thesis
70	70
71	71	== Related Work/Literature ==
72	72
73	73	* https://reakt.sh/
74		-* [[https:~~/~~/www.schiene-m-l.de/>>https://www.schiene-m-l.de/)]]
	28	+* https://github.com/kieler/RailTrail/wiki/Data-processing#computation-of-vehicle-position-speed-and-heading
75	75
76	76	== Involved Languages/Technologies ==
77	77
78		-* TBA for each topic individually
	32	+* Python
79	79
80	80	== Supervised by ==
81	81

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