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] 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 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 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 +![[position.png|image:attach: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 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 must be 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
21 +# Scope
20 20  
21 -2. An autonomous train controller with risk analysis using STPA **[already reserved]**
23 +Bachelor's Thesis
22 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)
25 +# Related Work/Literature
28 28  
29 -3. AI-based obstacle detection for autonomous train control using image recognition
30 -// This topic will be jointly advised with the AG Distributed Systems//
31 -
32 -* Sensor processing of a train mounted camera to detect objects (potential obstacles)
33 -* Tasks will involve:
34 -** Sensor mounting on the demonstrator
35 -** Collection of data (images, videos)
36 -** Labeling of data to enable training (esp. for small scale model)
37 -** Training of AI
38 -** Evaluation of quality
39 -* Step-wise evaluation of the influence of vehicle speed on the detection quality
40 40  *
41 -*
42 -* Potential hardware (subject to changes):
43 -** [[https:~~/~~/www.raspberrypi.com/documentation/accessories/camera.html>>https://www.raspberrypi.com/documentation/accessories/camera.html]]
44 -** (((
45 -[[https:~~/~~/www.axis.com/de-de/products/axis-p1455-le>>https://www.axis.com/de-de/products/axis-p1455-le]]
46 -)))
47 47  
48 -4. AI-based sensor processing for autonomous train control
49 -// This topic will be jointly advised with the AG Distributed Systems//
29 +[https://reakt.sh/](https://reakt.sh/) *
50 50  
51 -* Sensor processing of train mounted LiDAR or ultrasonic sensor
52 -* Potential hardware (subject to changes):
53 -** [[https:~~/~~/www.elektronik-kompendium.de/sites/praxis/bauteil_ultrasonic-hcsr04p.htm>>https://www.elektronik-kompendium.de/sites/praxis/bauteil_ultrasonic-hcsr04p.htm]]
54 -** [[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]]
55 -** (((
56 -[[https:~~/~~/www.blickfeld.com/de/produkte/cube-1/>>https://www.blickfeld.com/de/produkte/cube-1/]]
57 -)))
58 -* Obstacle detection at speeds up to 50 km/h
59 -* Distance measuring (ultrasonic sensor)
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)
60 60  
61 -5. A digital twin for an autonomous on-demand train service **[already reserved]**
62 -// Note: Tight interfacing with other topics//
33 +# Involved Languages/Technologies
63 63  
64 -* A digital twin for an autonomous passenger train
65 -* Monitoring system for the state and location of the vehicle
66 -* Remote control capabilities //(interfacing with controller)//
67 -* Monitoring and economic analysis of on-demand service operation (//integration/interfacing of management system//)
68 -* Reliability analysis/statistics to ensure transparency of autonomous operation
35 +* Python
69 69  
70 -6. A standalone sensor box for monitoring rail vehicles
71 - //This prototype will be tested (only) using the full-scale demonstrator and is intended for monitoring non-autonomous vehicles (not the REAKTOR)//
37 +# Supervised by
72 72  
73 -* Development of a sensor array to monitor rail vehicle operation
74 -* It should serve as a plugin solution inside the train's cockpit for monitoring operation and as preparation for autonomous control
75 -* Design for wireless communication of collected data
76 -* Possible sensors:
77 -** GPS
78 -** Accelerometer
79 -** Camera
80 -* Analysis of data for autonomous driving
81 -* Potential integration into digital twin infrastructure
82 -
83 -== Goals ==
84 -
85 -* TBA for each topic individually
86 -
87 -== Scope ==
88 -
89 -Bachelor's or Master's Thesis, with varying requirements to scientific scope.
90 -
91 -== Related Work/Literature ==
92 -
93 -* https://reakt.sh/
94 -* [[https:~~/~~/www.schiene-m-l.de/>>https://www.schiene-m-l.de/)]]
95 -
96 -== Involved Languages/Technologies ==
97 -
98 -* TBA for each topic individually
99 -
100 -== Supervised by ==
101 -
102 102  Alexander Schulz-Rosengarten
103 -[[als@informatik.uni-kiel.de>>mailto:als@informatik.uni-kiel.de]]
40 +[[als@informatik.uni-kiel.de|path:mailto:als@informatik.uni-kiel.de]]
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