Changes for page [REAKT] Project REAKTOR

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Change comment: Renamed from xwiki:Theses.Topics for Student Theses.[REAKT] Projecting Irregular Vehicle Positions on Tracks.WebHome

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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 built 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 +[[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 for a 45mm model track.//
5 +== Goals ==
6 6  
7 -{{info}}
8 -Kick-off meeting on Monday 7th Oct. at 10am in room 1115 CAP4
9 -{{/info}}
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
10 10  
11 -== Overview of topics (WIP) ==
10 +==== Consiterations for the Algorithm ====
12 12  
13 -**The solutions in all topics should be scalable for both demonstrators!**
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
14 14  
15 -~1. An end-user app and management system for on-demand train service **[(partially) reserved]**
16 -// This topic may be split up into two theses/project participants (app & management)//
17 -
18 -* A mobile app to call a train to a desired location and communicate desired destination
19 -* Locations drawn from GNSS and appropriate abstraction for 1:32 scale for station-less entry or predefined locations
20 -* Management of multiple on-demand trains on a single track line
21 -* Schedules for cooperative passenger pick up
22 -* Provisions for passenger transfer on open track ("Begegnungsverkehr", see concept art [[here>>https://cloud.rz.uni-kiel.de/index.php/s/ZMZSoLTerJCJi7L]])
23 -* The inter train communication concept maybe based on a central or decentralized structure
24 -
25 -2. An autonomous train controller with risk analysis using STPA **[already reserved]**
26 -
27 -* Control of an autonomous passenger train model (conceptually working for both demonstrators)
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]])
29 -* 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]])
30 -* Safe behavior model generation using PASTA ([[https:~~/~~/marketplace.visualstudio.com/items?itemName=kieler.pasta>>https://marketplace.visualstudio.com/items?itemName=kieler.pasta]])
31 -* Assumes preprocessed sensor input and destination determination (see other topics)
32 -
33 -3. AI-based obstacle detection for autonomous train control using image recognition
34 -// This topic will be jointly advised with the AG Distributed Systems//
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.
50 -* Potential hardware (subject to changes):
51 -** [[https:~~/~~/www.raspberrypi.com/documentation/accessories/camera.html>>https://www.raspberrypi.com/documentation/accessories/camera.html]]
52 -** (((
53 -[[https:~~/~~/www.axis.com/de-de/products/axis-p1455-le>>https://www.axis.com/de-de/products/axis-p1455-le]]
54 -)))
55 -
56 -4. Classic and AI-based distance sensing for autonomous train control using different sensors **[already reserved]**
57 -// This topic will be jointly advised with the AG Distributed Systems//
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)
67 -* Potential hardware (subject to changes):
68 -** [[https:~~/~~/www.elektronik-kompendium.de/sites/praxis/bauteil_ultrasonic-hcsr04p.htm>>https://www.elektronik-kompendium.de/sites/praxis/bauteil_ultrasonic-hcsr04p.htm]]
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 -** (((
71 -[[https:~~/~~/www.blickfeld.com/de/produkte/cube-1/>>https://www.blickfeld.com/de/produkte/cube-1/]]
72 -)))
73 -
74 -5. A digital twin for an autonomous on-demand train service **[already reserved]**
75 -// Note: Tight interfacing with other topics//
76 -
77 -* A digital twin for an autonomous passenger train
78 -* A virtual rebuild of the track using an 3D engine (i.e. [[Unreal Engine>>https://www.unrealengine.com]])
79 -* Simulation capabilities to test and replay behavior (virtual environment)
80 -* (Optional) Monitoring system for the state and location of the real vehicle
81 -* (Optional) Monitoring and economic analysis of on-demand service operation (//integration/interfacing of management system//)
82 -* (Optional) Reliability analysis/statistics to ensure transparency of autonomous operation
83 -
84 -6. Remote control for rail vehicles
85 -//This topic will be jointly advised with the AG Distributed Systems//
86 -//Note: Tight interfacing with other topics//
87 -
88 -* Remote control of speed and brakes //(interfacing with controller)//
89 -* Live streaming of camera data and other sensors
90 -* Evaluation and setup of a wireless communication network with a high reliability
91 -* (Optional) Construction of a [[remote control panel>>https://cloud.rz.uni-kiel.de/index.php/s/jCxitwKzddqEctD]]
92 -* (Optional) Augmented reality integration to simulate training scenarios
93 -
94 -7. A standalone sensor box for monitoring rail vehicles **[already reserved]**
95 -//This prototype will be tested (only) using the full-scale demonstrator and is intended for monitoring non-autonomous vehicles (not the REAKTOR)//
96 -
97 -* Development of a sensor array to monitor rail vehicle operation
98 -* It should serve as a plugin solution inside the train's cockpit for monitoring operation and as preparation for autonomous control
99 -* Design for wireless communication of collected data
100 -* Possible sensors:
101 -** GPS
102 -** Accelerometer
103 -** Camera
104 -* Analysis of data for autonomous driving
105 -* Potential integration into digital twin infrastructure
106 -
107 -== Goals ==
108 -
109 -* TBA for each topic individually
110 -
111 111  == Scope ==
112 112  
113 -Bachelor's or Master's Thesis, or Master's Project, with varying requirements to scientific scope.
23 +Bachelor's Thesis
114 114  
115 115  == Related Work/Literature ==
116 116  
117 117  * https://reakt.sh/
118 -* [[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
119 119  
120 120  == Involved Languages/Technologies ==
121 121  
122 -* TBA for each topic individually
32 +* Python
123 123  
124 124  == Supervised by ==
125 125  
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