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1
Intermodal Travel Informationwith Distributed Routing
mdvmentzdatenverarbeitung
VIKING Domain 4seminar
CopenhagenMay 31, 2001
www.mentzdv.de
2
mdvTopicsmentz
datenverarbeitung
- Introduction
- Broker
- basics
- place identification
- supported passive servers
- supported routing techniques
-architecture
- Examples
3
mdvIntroductionmentz
datenverarbeitung
Distributed
multiple planning systems co-operate under the control of a so-called „Broker“ (search controller)
Intermodal
all means of transport are considered
• public transport : regional (bus, metro, commuter train, tram, ...)
• long-distance (high-speed train, plane, ferry, ...)
• individual transport (footpath, taxi, car, bicycle, ...)
4
mdvDistributed vs. Integrated Trip Planningmentz
datenverarbeitung
today
user wants to plan long-distance trips
many regional limited trip planning systems
few integrated national trip planning systems (with up to 70 data sources)
integrated networks are huge
requires large memory / disk space
real-time information cannot be integrated
large integration effort
each regional change in timetable leads to new data integration
therefore
Distributed Trip Planning
5
mdvWork-split in Distributed Trip Planningmentz
datenverarbeitung
Work-split into
passive servers
- regional systems for regional transport(bus, metro, commuter train, tram, ... + individual traffic)
- national /international systems for long-distance transport(long-distance trains, ... + flight traffic + ferry boats + ...)
active broker (search controller)
- interface to the user
- distributed routing
Each system does what it can the best
6
mdvDistributed Routingmentz
datenverarbeitung
Idea of distributed routing
1) Divide total network into overlapping subnetworkswith common points (transition points) in overlap
2) Divide user request into partial requests on subnetworks
e.g. request „from A to B“ is divided into
1) req. „from A to transitions“ in network X
2) req. „from transitions to transitions“ in network Y
3) req. „from transitions to B“ in network Z
Sometimes a division into more than 3 subnetworks is needed.
7
mdvBrokermentz
datenverarbeitung
Broker as search controller and integrator
is interface to user
knows the passive servers
has meta knowledge
implements distributed routing
can access the passive servers
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mdvMeta Knowledgementz
datenverarbeitung
Broker has mappings
„place to subnetwork“ e.g. „Hannover“ is in the subnetwork of the Hannover Region Transport Company „GVH“
„from subnetwork to subnetwork“ e.g. from subnet „GVH“
via subnet „DB“ (Deutsche Bahn) or via subnet „Flight“ (START/Amadeus) to subnet „Copenhagen“ Region
„subnetwork to passive server“
e.g. subnet „GVH“ by server „IOR_209328FD23DB88A6352C...“
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mdvMeta Knowledgementz
datenverarbeitung
Broker gets from passive server
transition points (common points of different networks)
e.g. transition points for „Hannover Town Hall“ are„Hannover Main Station“ and „Hannover Airport“
partial trips
- from origin to transition points
- from transition points to transition points
- from transition points to destination
e.g. from „Hannover Town Hall“ to „Hannover Airport“,
from „Hannover Airport“ to „Copenhagen Airport“,
from „Copenhagen Airport“ to „Copenhagen Rådhuspladsen“
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mdvPlace Identification
user-driven (e.g. EUSpirit)
User input for origin / destination:
1) region
2) place (town, village)
3) point (stop, address, point of interest)
By choosing the region from a list, the passive server
for place and point identification is selected.
+ easy to implement
- additional input step (region + town + point)
- choose of region difficult when many regions
mentzdatenverarbeitung
11
mdvPlace Identification
knowledge-based (e.g. EFA/IMTP)
User input for origin / destinition:
1) place (town, village)2) point (stop, address, point of interest)
One „place server“ knows all places of the total network.He identifies the place.
Point verification is done by the passive server for this place (this subnetwork)
+ user-friendly- effort to integrate place data
mentzdatenverarbeitung
12
mdvPassive Servers
The following passive servers are supported
PT EUSpirit server DELFI server EFA server START/Amadeus (flight server)
IT EFA router PTV router (soon)
mentzdatenverarbeitung
13
mdvDistributed routing
The following techniques for distributed routing are implemented
EUSpirit DELFI Multimodal
Alternative trips can be calculated by different network sequences techniques
mentzdatenverarbeitung
14
mdvDistributed Routing
A) EUSpirit-Technique
„Extending the long-distance trips into the regional networks“
Used in EU project EUSpirit(Denmark, Scania, Austria, Vienna, Emilia Romangna, Berlin)
Assumptions: • origin and destination region are not close• few transition points
+ fast if assumptions true+ extension into regional networks parallel- needs estimation- slow if assumptions false
mentzdatenverarbeitung
15
Origin Destination
Departure at 10:00
Regional Transport Regional Transport
Long-distance Transport
mdvmentzdatenverarbeitungEUSpirit-Technique : Request
16
Origin Destination
Estimated Departures
Regional Transport Regional Transport
Long-distance Transport
10:20
10:50
mdvmentzdatenverarbeitungEUSpirit-Technique : Transition Points
17
Origin Destination
Regional Transport Regional Transport
Long-distance Transport
14:00
15:00
14:30
14:50
10:20
10:50
m:n search
mdvmentzdatenverarbeitungEUSpirit-Technique : Long-distance trip search
18
Origin Destination
Regional Transport Regional Transport
Long-distance Transport
14:00
14:30
10:20
10:50
9:50
10:10 15:20
14:50
1:m search (backward) n:1 search (forward)
mdvmentzdatenverarbeitungEUSpirit-Technique : Extension into regional networks
19
OriginDestination
Regional Transport Regional Transport
Long-distance Transport
14:00
10:50
10:10
14:50
Merging of partial trips
mdvmentzdatenverarbeitungEUSpirit-Technique : Result
10:2514:20
20
mdvDistributed Routing
B) DELFI-Technique
„Distributed Dijkstra-Algorithm“
Used in German project DELFI (in cooperation with HaCon, HBT, IVU, TLC, et al)
+ no estimation needed
+ works not only for 3 subnetworks- no parallelism
mentzdatenverarbeitung
21
Origin Destination
Departure at 10:00
Regional Transport Regional Transport
Long-distance Transport
mdvmentzdatenverarbeitungDELFI-Technique : Request
22
Origin Destination
Regional Transport Regional Transport
Long-distance Transport
mdvmentzdatenverarbeitungDELFI-Technique : Transition Points
23
Origin Destination
Regional Transport Regional Transport
Long-distance Transport
14:00
14:30
10:20
10:30
mdvmentzdatenverarbeitungDELFI-Technique : Connection search forward
14:5010:00
24
Origin Destination
Regional Transport Regional Transport
Long-distance Transport
14:20
14:40
mdvmentzdatenverarbeitungDELFI-Technique : Connection search backward
14:50
10:50
10:35
10:10
14:0010:20
14:5010:00
14:3010:30
25
Origin Destination
Regional Transport Regional Transport
Long-distance Transport
14:00
10:10
14:50
1:1 search (forward) 1:1 search (forward)
mdvmentzdatenverarbeitungDELFI-Technique : Trip search
1:1 search (forward)
10:50
14:2010:30
26
OriginDestination
Regional Transport Regional Transport
Long-distance Transport
14:00
10:50
10:10
14:50
Merging of partial trips
mdvmentzdatenverarbeitungDELFI-Technique : Result
10:3014:20
27
mdvDistributed Routing
C) Multimodal Technique
„Extended DELFI-Technique for intermodal trip planning“
combines PT/IT for door-to-door trips needs passive servers for IT routing uses GIS data for IT routing produces graphical maps and textual descriptions restricted to EFA systems.
mentzdatenverarbeitung
28
mdvMultimodal Technique
O = regional system of origin
D = regional system of destination
V = national system for long-distance transport
1. Search stops near origin/destination address
2. Search transition points in O and D
3. Search connections forward in O + V + D
4. Search connections backward in D + V + O
5. Search trips in O
6. Search trips in V
7. Search trips in D
8. Search IT path from origin address to origin stop
9. Search IT path from destination stop to destination address
mentzdatenverarbeitung
DELFI
29
mdvArchitecturementz
datenverarbeitung
CORBA-Client
Broker
IMTP IDL
DELFI IDL
EUSpirit IDL
DELFI Technique
EUSpirit Technique
IMTP Server
DELFI Server
EUSpirit Server
Distributed Routing
Standard Routing
Passive Servers
HTTP-Client WAP-Client SMS-ClientRequests
Results
START AMADEUS
IT Server
IT IDL
Multimodal Technique
Flight IDL
CORBA
30
Work-split Examplementz
datenverarbeitung
Stuttgart Town Hall
Stockholm
Gamla Stan
Broker
Town Hall VVS
Gamla Stan TPG
VVS Flight TPG
VVS Train TPG
VVS Flight TPG
VVS Train TPG
VVS
TågPlus Guiden
TravelLink
START Amadeus
VVS Ferry TPG
Trip 1
Trip 2
Trip 3
Dep 06:34
Arr 12:09
VVS Ferry TPG
Alternative 1
Alternative 2
Alternative 3
Meta Knowledge
International Trains
mdv
VVS = Stuttgart Region Transport TPG = Stockholm Region Transport
31
mdvExample of an intermodal local trip
Example Local trip
from : Mannheim (Germany) Stresemannstrasse / Friedrichsplatz
to : Ludwigshafen (Germany)Roonstrasse / Halbergstrasse
using : one PT server with regional timetable dataone IT server with regional GIS data
mentzdatenverarbeitung
32
mdvOutput of an intermodal local trip
Trip Overview
mentzdatenverarbeitung
33
mdvOutput of an intermodal local trip
Trip Detail
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34
mdvOutput of an intermodal local tripmentz
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Origin Detail
35
mdvOutput of an intermodal local tripmentz
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Destination Detail
36
mdvOutput of an intermodal local tripmentz
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Overview Map
37
mdvExample of an intermodal regional trip
Example Intermodal regional trip
from : Ludwigshafen (Germany) Limesstrasse / Im Kappes
to : Heidelberg (Germany)Marktplatz
using : PT server with regional timetable dataIT server with regional GIS data
mentzdatenverarbeitung
38
mdvOutput of an intermodal regional trip
Trip Overview
mentzdatenverarbeitung
39
mdvOutput of an intermodal regional trip
Trip Detail
mentzdatenverarbeitung
40
mdvOutput of an intermodal regional tripmentz
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Origin Detail
41
mdvOutput of an intermodal regional tripmentz
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Destination Detail
42
mdvOutput of an intermodal regional tripmentz
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Overview Map
43
mdvExample of an intermodal long-distance trip
Example Intermodal long-distance trip
from : Mulhouse (France) Rue du Beau Regard
to : Bremen (Germany)Im Leher Felde / Lilienthaler Heerstrasse
using : PT server with Alsace timetable dataPT server with German timetable data (trains)PT server with Bremen timetable data
IT server with Alsace GIS dataIT server with Bremen GIS data
mentzdatenverarbeitung
44
mdvOutput of an intermodal long-distance trip
Trip Overview
mentzdatenverarbeitung
45
mdvOutput of an intermodal long-distance trip
Trip Detail
mentzdatenverarbeitung
46
mdvOutput of an intermodal long-distance tripmentz
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Origin Detail
47
mdvOutput of an intermodal long-distance tripmentz
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Destination Detail
48
mdvConclusionmentz
datenverarbeitung
With EFABroker you can build a
distributed
intermodal
travel information system.
Passive servers with EUSpirit, DELFI or EFA interfaces can be integrated.
The EUSpirit and DELFI interface should be enlarged to allow real intermodal door-to-door trip planning.
Open points:
standardized access to Broker
language problems (e.g. operational notices)