Available Topics - [REAKT] Projecting Irregular Vehicle Positions on Tracks

Page / - last modified by Alexander Schulz-Rosengarten on 2024/02/26 12:43

[REAKT] Projecting Irregular Vehicle Positions on Tracks

last modified by Alexander Schulz-Rosengarten

on 2024/02/26 12:43

Table of Contents

Overview of topics (WIP)

Goals

Scope

Related Work/Literature

Involved Languages/Technologies

Supervised by

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.

(left) a railbike, the foundation of the upcoming autonomous draisine & (right) a stripped down LGB engine for a 45mm model track.

Kick-off meeting on Monday 7th Oct. at 10am in room 1115 CAP4

Overview of topics (WIP)

The solutions in all topics should be scalable for both demonstrators!

1. An end-user app and management system for on-demand train service [already assigned (App part only)]
This topic may be split up into two theses/project participants (app & management)

A mobile app to call a train to a desired location and communicate desired destination

Locations drawn from GNSS and appropriate abstraction for 1:32 scale for station-less entry or predefined locations

Management of multiple on-demand trains on a single track line

Schedules for cooperative passenger pick up

Provisions for passenger transfer on open track ("Begegnungsverkehr", see concept art here)

The inter train communication concept maybe based on a central or decentralized structure

2. An autonomous train controller with risk analysis using STPA [already assigned]

Control of an autonomous passenger train model (conceptually working for both demonstrators)

Capability for passenger transfer on open track (safe docking procedure; "Begegnungsverkehr", see concept art here)

Risk analysis for the controller using STPA (http://psas.scripts.mit.edu/home/get_file.php?name=STPA_handbook.pdf)

Safe behavior model generation using PASTA (https://marketplace.visualstudio.com/items?itemName=kieler.pasta)

Assumes preprocessed sensor input and destination determination (see other topics)

3. AI-based obstacle detection for autonomous train control using image recognition [already assigned]
This topic will be jointly advised with the AG Distributed Systems

Sensor processing of a train-mounted camera to detect objects (potential obstacles)

Tasks will involve:

Sensor mounting on the demonstrator

Collection of data (images, videos)

Labeling of data to enable training (esp. for small scale model)

Training of AI

Evaluation of quality

Live testing

Step-wise evaluation of the influence of vehicle speed on the detection quality

Evaluate applicability and influence of training data due to different environments for the demonstrators (i.e. indoors vs. outdoors)

(Optional) Trajectory detection to categorize safety threads of moving obstacles

(Optional) Evaluate performance on different hardware, e.g. Rasberry Pi vs. AI hardware

(Optional) Test and evaluate on the edge deployment

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.

Potential hardware (subject to changes):

https://www.raspberrypi.com/documentation/accessories/camera.html

https://www.axis.com/de-de/products/axis-p1455-le

4. Classic and AI-based distance sensing for autonomous train control using different sensors
This topic will be jointly advised with the AG Distributed Systems

Explore and evaluate different sensors and processing techniques for distance measuring in rail vehicles

Compare quality, ranges, and reliability w.r.t speed and size (demonstrator)

Sensors and approaches:

Ultrasonic sensor

Single camera with AI image recognition

(Multiple cameras)

(LiDAR)

(Sensorfusion)

Potential hardware (subject to changes):

https://www.elektronik-kompendium.de/sites/praxis/bauteil_ultrasonic-hcsr04p.htm

https://www.pi-shop.ch/lidar-ld06-lidar-module-with-bracket-entwicklungskit-fuer-raspberry-pi-sbc

https://www.blickfeld.com/de/produkte/cube-1/

5. A digital twin for an autonomous on-demand train service [already assigned]
Note: Tight interfacing with other topics

A digital twin for an autonomous passenger train

A virtual rebuild of the track using an 3D engine (i.e. Unreal Engine)

Simulation capabilities to test and replay behavior (virtual environment)

(Optional) Monitoring system for the state and location of the real vehicle

(Optional) Monitoring and economic analysis of on-demand service operation (integration/interfacing of management system)

(Optional) Reliability analysis/statistics to ensure transparency of autonomous operation

6. Remote control for rail vehicles [already assigned]
This topic will be jointly advised with the AG Distributed Systems
Note: Tight interfacing with other topics

Remote control of speed and brakes (interfacing with controller)

Live streaming of camera data and other sensors

Evaluation and setup of a wireless communication network with a high reliability

(Optional) Construction of a remote control panel

(Optional) Augmented reality integration to simulate training scenarios

7. A standalone sensor box for monitoring rail vehicles [already assigned]
This prototype will be tested (only) using the full-scale demonstrator and is intended for monitoring non-autonomous vehicles (not the REAKTOR)

Development of a sensor array to monitor rail vehicle operation

It should serve as a plugin solution inside the train's cockpit for monitoring operation and as preparation for autonomous control

Design for wireless communication of collected data

Possible sensors:

GPS

Accelerometer

Camera

Analysis of data for autonomous driving

Potential integration into digital twin infrastructure

Goals

TBA for each topic individually

Scope

Bachelor's or Master's Thesis, or Master's Project, with varying requirements to scientific scope.

Related Work/Literature

https://reakt.sh/

https://www.schiene-m-l.de/

Involved Languages/Technologies

TBA for each topic individually

Supervised by

Alexander Schulz-Rosengarten
als@informatik.uni-kiel.de