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...	...	@@ -26,21 +26,34 @@
26	26	* Safe behavior model generation using PASTA ([[https:~~/~~/marketplace.visualstudio.com/items?itemName=kieler.pasta>>https://marketplace.visualstudio.com/items?itemName=kieler.pasta]])
27	27	* Assumes preprocessed sensor input and destination determination (see other topics)
28	28
29		-3. AI-based image recognition for autonomous train control
	29	+3. AI-based obstacle detection for autonomous train control using image recognition
30	30	// This topic will be jointly advised with the AG Distributed Systems//
31	31
32		-* Sensor processing of a train mounted camera
33		-* Obstacle detection at speeds up to 50 km/h
	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	+** Live testing
	40	+* Step-wise evaluation of the influence of vehicle speed on the detection quality
	41	+* Evaluate applicability and influence of training data due to different environments for the demonstrators (i.e. indoors vs. outdoors)
	42	+* (Optional) Trajectory detection to categorize safety threads of moving obstacles
	43	+* (Optional) Evaluate performance on different hardware, e.g. Rasberry Pi vs. AI hardware
	44	+* (Optional) Test and evaluate on the edge deployment
	45	+* 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.
34	34	* Potential hardware (subject to changes):
35	35	** [[https:~~/~~/www.raspberrypi.com/documentation/accessories/camera.html>>https://www.raspberrypi.com/documentation/accessories/camera.html]]
36	36	** (((
37	37	[[https:~~/~~/www.axis.com/de-de/products/axis-p1455-le>>https://www.axis.com/de-de/products/axis-p1455-le]]
38	38	)))
39		-* [Optional] Distance measuring using multiple cameras
40	40
41		-4. AI-based sensor processing for autonomous train control
	52	+4. Classic and AI-based distance sensing for autonomous train control using different sensors
42	42	// This topic will be jointly advised with the AG Distributed Systems//
43	43
	55	+* Explore and evaluate the applica
	56	+* Assess applicablilty of different sensors for use cases and ranges
44	44	* Sensor processing of train mounted LiDAR or ultrasonic sensor
45	45	* Potential hardware (subject to changes):
46	46	** [[https:~~/~~/www.elektronik-kompendium.de/sites/praxis/bauteil_ultrasonic-hcsr04p.htm>>https://www.elektronik-kompendium.de/sites/praxis/bauteil_ultrasonic-hcsr04p.htm]]
...	...	@@ -52,7 +52,7 @@
52	52	* Distance measuring (ultrasonic sensor)
53	53
54	54	5. A digital twin for an autonomous on-demand train service **[already reserved]**
55		- // Note: Tight interfacing with other topics//
	68	+// Note: Tight interfacing with other topics//
56	56
57	57	* A digital twin for an autonomous passenger train
58	58	* Monitoring system for the state and location of the vehicle
...	...	@@ -60,6 +60,19 @@
60	60	* Monitoring and economic analysis of on-demand service operation (//integration/interfacing of management system//)
61	61	* Reliability analysis/statistics to ensure transparency of autonomous operation
62	62
	76	+6. A standalone sensor box for monitoring rail vehicles
	77	+ //This prototype will be tested (only) using the full-scale demonstrator and is intended for monitoring non-autonomous vehicles (not the REAKTOR)//
	78	+
	79	+* Development of a sensor array to monitor rail vehicle operation
	80	+* It should serve as a plugin solution inside the train's cockpit for monitoring operation and as preparation for autonomous control
	81	+* Design for wireless communication of collected data
	82	+* Possible sensors:
	83	+** GPS
	84	+** Accelerometer
	85	+** Camera
	86	+* Analysis of data for autonomous driving
	87	+* Potential integration into digital twin infrastructure
	88	+
63	63	== Goals ==
64	64
65	65	* TBA for each topic individually