UC:IS:DriverAdvisorySystem

From wiki.railML.org
Jump to: navigation, search
Note.png This page is mirrored from page UC:IS:DriverAdvisorySystem in the railML® 3 wiki.
Driver Advisory System
(DASY)
Subschema: Infrastructure
 
Related subschemas: TT RS 
Reported by: IS
Stift.png                   (version(s) 2.4)
For general information on use cases see UC:Use cases


Use case / Anwendungsfall / Scénario d’utilisation

Driver Advisory System (DAS); Fahrerassistentsystem; nom descriptif en Francais

Description / Beschreibung / 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.

DAS use case.png

Data Flows and Interfaces / Datenflüsse und Schnittstellen / Flux de données et interfaces

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 / Interaction avec autres schemas railML®

  • rolling stock
  • timetable

Characterizing Data / Charakterisierung der Daten / Caractérisation des données

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)