UC:IS:DriverAdvisorySystem: Difference between revisions

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'''Use case / {{Deu|Anwendungsfall}} / {{Fra|Scénario d’utilisation}}:'''
{{useCase|IS|2.3|title=Driver Advisory System}}


{{UC title}}
Driver Advisory System (DAS); {{Deu|Fahrerassistentsystem}}; {{Fra|nom descriptif en Francais}}
Driver Advisory System (DAS); {{Deu|Fahrerassistentsystem}}; {{Fra|nom descriptif en Francais}}


 
{{UC description}}
'''Description / {{Deu|Beschreibung}} / {{Fra|Description}}'''
 
The Driver Advisory System (DAS) is an on-train driver support system which advises a driver on the most energy-efficient speed profile with which to meet the train’s current schedule.  The DAS receives as input the current schedule (which may be updated at any time) together with a range of static or near-static data relating to the track, namely: topology, topography, asset locations and speed restrictions; and various parameters relating to the vehicle itself.  
The Driver Advisory System (DAS) is an on-train driver support system which advises a driver on the most energy-efficient speed profile with which to meet the train’s current schedule.  The DAS receives as input the current schedule (which may be updated at any time) together with a range of static or near-static data relating to the track, namely: topology, topography, asset locations and speed restrictions; and various parameters relating to the vehicle itself.  


[[Datei:DAS use case.png|DAS use case.png]]  
[[Datei:DAS use case.png|DAS use case.png]]  


 
{{UC flows}}
 
'''Data Flows and Interfaces / {{Deu|Datenflüsse und Schnittstellen}} / {{Fra|Flux de données et interfaces}}'''
 
<u>Data inputs</u> <br>
<u>Data inputs</u> <br>
Track attributes (<i>Infrastructure</i>):
Track attributes (<i>Infrastructure</i>):
Line 61: Line 57:
* Driver entered parameters
* Driver entered parameters


 
{{UC interference}}
'''Interference with other railML<sup>®</sup> schemas / {{Deu|Interferenz mit anderen railML<sup>®</sup>-Schemen}} / {{Fra|Interaction avec autres schemas railML<sup>®</sup>}}'''
 
* rolling stock
* rolling stock
* timetable
* timetable


 
{{UC data}}
'''Characterizing Data / {{Deu|Charakterisierung der Daten}} / {{Fra|Caractérisation des données}}'''
 
This section serves to specify the required data regarding certain aspects.
This section serves to specify the required data regarding certain aspects.


<u>How often do the data change (update)?</u>
{{UC update}}
 
* Track attributes: nearly static except for TSRs and ESRs (weekly/daily)
* Track attributes: nearly static except for TSRs and ESRs (weekly/daily)
* Schedule attributes: daily, with realtime changes
* Schedule attributes: daily, with realtime changes
* Vehicle attributes: occasional changes (event-driven)
* Vehicle attributes: occasional changes (event-driven)


<u>How big are the data fragments to be exchanged (complexity)?</u>
{{UC complexity}}
 
* huge (region)
* huge (region)


<u>Which views are represented by the data (focus)?</u>
{{UC focus}}
 
* Train regulation
* Train regulation
* Energy
* Energy
{{UC elements}}
{{missing information|user=[[Benutzer:Ferri Leberl|Ferri Leberl]] ([[Benutzer Diskussion:Ferri Leberl|Diskussion]]) 18:04, 23. Jun. 2016 (CEST)|topic=affected elements}}

Revision as of 18:04, 23 June 2016

Driver Advisory System
Subschema: Infrastructure
Stift.png (version(s) 2.3)
For general information on use cases see UC:Use cases


Use case / Anwendungsfall

Driver Advisory System (DAS); Fahrerassistentsystem;

Description / Beschreibung

The Driver Advisory System (DAS) is an on-train driver support system which advises a driver on the most energy-efficient speed profile with which to meet the train’s current schedule. The DAS receives as input the current schedule (which may be updated at any time) together with a range of static or near-static data relating to the track, namely: topology, topography, asset locations and speed restrictions; and various parameters relating to the vehicle itself.

DAS use case.png

Data Flows and Interfaces / Datenflüsse und Schnittstellen

Data inputs
Track attributes (Infrastructure):

  • Track Centre Line (as a polyline)
  • Track altitude (polyline)
  • Geometry: Track curvature
  • Topology: Node-link model
  • Route IDs
  • Track IDs
  • Mileposts / kilometre posts id, location
  • Junctions id, location
  • Loop ends id, location
  • Platform ends platform ids, location
  • Tunnels id, location (,envelope)
  • Signals id, location, signal type
  • Permissible speeds including permanent speed restrictions (PSRs), qualified by direction of travel and train type
  • Temporary speed restrictions (TSRs), qualified by direction of travel and train type
  • Emergency speed restrictions (ESRs)
  • Locations of the following may also be required in the future (TBD):
    • Signal berths id, location
    • Bridges id, location
    • Road crossings id, location

Schedule attributes (Timetable):

  • Train Service Id
  • (Sequence of) scheduled locations
    • location name
    • location as Track attribute
  • For each passing location
    • passing time and tolerance (before and after)
  • For each stopping location
    • arrival and departure times

Vehicle attributes (Rollingstock):

  • Formation or consist
  • (mass, length) profile
  • Maximum speed
  • Braking parameters (braking curve, brake delay, brake build-up)
  • Traction parameters
  • Coefficients of resistance

Data outputs
DAS operating logs

  • Train id
  • Time
  • Train location
  • Train actual speed
  • Advised speed
  • Driver entered parameters

Interference with other railML® schemas / Interferenz mit anderen railML®-Schemen

  • rolling stock
  • timetable

Characterizing Data / Charakterisierung der Daten

This section serves to specify the required data regarding certain aspects.

How often do the data change (update)?

  • Track attributes: nearly static except for TSRs and ESRs (weekly/daily)
  • Schedule attributes: daily, with realtime changes
  • Vehicle attributes: occasional changes (event-driven)

How big are the data fragments to be exchanged (complexity)?

  • huge (region)

Which views are represented by the data (focus)?

  • Train regulation
  • Energy

Which specific data do you expect to receive/send (elements)?

Missinginformation.png In this article there is information missing with respect to affected elements. Please help improving the railML® wiki by filling the gaps. Possibly, you will find further details on the discussion pageFerri Leberl (Diskussion) 18:04, 23. Jun. 2016 (CEST)