Changes for page [REAKT] Project REAKTOR

Last modified by Alexander Schulz-Rosengarten on 2024/10/09 15:19
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edited by Alexander Schulz-Rosengarten
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1 -[REAKT] Projecting Irregular Vehicle Positions on Tracks
1 +[REAKT] Project REAKTOR
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1 -Theses.Topics for Student Theses.WebHome
1 +Theses.Current Theses.WebHome
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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.
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 -![[position.png|image:attach:position.png]]
3 +[[image:image-20240912102452-3.jpeg||height="219" width="292"]][[image:image-20240912102840-4.jpeg||height="217" width="264"]]
4 4  
5 -# Goals
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 -* 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
7 +== Overview of topics (WIP) ==
9 9  
10 -#### Consiterations for the Algorithm
9 +All solutions should be scalable for both demonstrators!
11 11  
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
11 +~1. An end-user app and management system for on-demand train service [Maybe split into two topics]
20 20  
21 -# Scope
13 +* App to call a train to a desired location and communicate desired destination
14 +* Locations drawn from GNSS and appropriate abstraction in 1:32 scale
15 +* Management of multiple trains on a single track line
16 +* Schedules for cooperative passenger pick up
17 +* Provisions for passenger transfer on open track
18 +* Either based on a central or decentralized communication concept
22 22  
23 -Bachelor's Thesis
20 +2. An autonomous train controller with risk analysis using STPA
24 24  
25 -# Related Work/Literature
22 +* Control of an autonomous passenger train model (conceptually working for both demonstrators)
23 +* Capability for passenger transfer on open track (safe docking procedure)
24 +* Risk analysis for the controller using STPA
25 +* Safe behavior model generation using PASTA?
26 +* Assumes preprocessed sensor input and destination determination (see other topics)
26 26  
27 -*
28 +3. AI-based image recognition for autonomous train control [In cooperation with AG Distributed Systems]
28 28  
29 -[https://reakt.sh/](https://reakt.sh/) *
30 +* Sensor processing of a train mounted camera
31 +* Obstacle detection at speeds up to 50 km/h
32 +* [Optional] Distance measuring using multiple cameras
30 30  
31 -[https://github.com/kieler/RailTrail/wiki/Data-processing#computation-of-vehicle-position-speed-and-heading](https://github.com/kieler/RailTrail/wiki/Data-processing#computation-of-vehicle-position-speed-and-heading)
34 +4. AI-based sensor processing for autonomous train control [In cooperation with AG Distributed Systems]
32 32  
33 -# Involved Languages/Technologies
36 +* Sensor processing of train mounted LiDAR or ultrasonic sensor
37 +* Obstacle detection at speeds up to 50 km/h
38 +* Distance measuring (ultrasonic sensor)
34 34  
35 -* Python
40 +5. A digital twin for an autonomous on-demand train service [Tight interfacing with other topics]
36 36  
37 -# Supervised by
42 +* A digital twin for an autonomous passenger train
43 +* Monitoring system for the state and location of the vehicle
44 +* Remote control capabilities
45 +* Monitoring and economic analysis of on-demand service operation [Integration of management system]
46 +* Reliability analysis to ensure transparency of autonomous operation
38 38  
48 +== Goals ==
49 +
50 +* TBA for each topic individually
51 +
52 +== Scope ==
53 +
54 +Bachelor's or Master's Thesis, with varying requirements to scientific scope.
55 +
56 +== Related Work/Literature ==
57 +
58 +* https://reakt.sh/
59 +* [[https:~~/~~/www.schiene-m-l.de/>>https://www.schiene-m-l.de/)]]
60 +
61 +== Involved Languages/Technologies ==
62 +
63 +* TBA for each topic individually
64 +
65 +== Supervised by ==
66 +
39 39  Alexander Schulz-Rosengarten
40 -[[als@informatik.uni-kiel.de|path:mailto:als@informatik.uni-kiel.de]]
68 +[[als@informatik.uni-kiel.de>>mailto:als@informatik.uni-kiel.de]]
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