GI2013 ppt löwner_20130429_geodata_forprivatetransportation_final_print

Platzhalter für Bild, Bild auf Titelfolie hinter das Logo einsetzen
Prof. Dr.-Ing. Marc-O. Löwner, 29. April 2013
Grenzüberschreitendes 13. Sächsische GI/GIS/GDI-Forum am 29.-30. April in Dresden
Geo data for private transportation questions

Our daily hazard on the streets
 2.361.457 accidents on German
streets in 2011
 306.266 accidents causing
personal injury
 4.722 fatal accidents
Damages to persons in 2011 [%]
killed badly injured
slightly
injured
build up areas out-of-town highway
Statistisches Bundesamt 2012
29.04.2013 | Marc-O. Löwner | Geo data for private transportation questions | Seite 2

Accidents caused by influence of weather (in total)
bad weather
crosswind
dazzling sun
hail or snow storm
fog
[No.ofpersons]
1.54% of all accidents

Accidents by influence of weather (killed persons)
bad Weather
crosswind
dazzling sun
hail or snow storm
fog
[No.ofpersons]
2.16% of all accidents

 dazzling by low sun conditions is a danger
to private transportation
 today, no warning service is available,
either by public authorities or private
navigation system providers
 Risk assessment of dazzling is
possible for transport infrastructure
networks !
 Small application project supported by the
Verein zur Förderung der Geoinformatik in
Norddeutschlang GiN e.V.
„Massenkarambolage von 259 Autos auf
der A2
Bei einer Massenkarambolage auf der
Autobahn A2 in Niedersachsen wurden
mehr als 60 Menschen verletzt, zehn davon
erlitten schwere Verletzungen. Nach
heftigen Regenfällen verloren im Bereich
Peine mehrere Fahrer die Kontrolle über
ihre Autos. Der Sachschaden soll in die
Millionenhöhe gehen. […]
Ein Grund für die Vielzahl der Beteiligten
war nach erster Einschätzung der Polizei
auch, dass viele Fahrer bei dem schlechten
Wetter zu schnell unterwegs waren und zu
wenig Abstand zum Vordermann hielten.
Die tiefstehende Sonne behinderte die Sicht
erheblich, sagte ein Sprecher der
Braunschweiger Autobahnpolizei. […]“
20.7.2009
www.welt.de
Risik assesment of dazzling by low sun conditions

Risik assesment of dazzling by low sun conditions
 main target:
 Modelling of dazzling effects on the highways of Lower Saxony for one year with high
temporal resolution
 model components
 street data
 position of the sun in a high temporal resolution
 vehicle model
 result
 Movie of street segments under risk
 not considered
 digital terrain model
 surrounding infrastructure
 weather effects (reflection from the lane)

Street information from OpenStreetMap
 started 2004
 Volunteered Geographic Information
 user-generated Content
 non-professionals may add coordinates,
objects and attributes. They also may
change existing ones.
 pPublished under ShareAlike 2.0 Generic
(CC BY-SA 2.0)
 users are allowed to use and share data,
even for commercial purposes
Zimmermann & Löwner (2012)

position of the sun
 angle and azimuth of the sun (AstAlm 2006;
Meeus 2000) for every 15 minutes
 26.200 pairs of angles for one geometry
h
N
Vertikalwinkel
Horizontalwinkel
0103 9:45 143.871086524855 7.5960694032043
0103 10:00 147.105451090724 8.88208963931512
0103 10:15 150.393674576367 10.0626732182494
0103 10:30 153.734117939271 11.1306801587273
0103 10:45 157.124065211231 12.0798261642064
0103 11:00 160.559715910859 12.9045201956266
0103 11:15 164.036211005061 13.5998340957865

vehicle model
 three main danger classes
 dazzling from forward view
 dazzling from forward view in spite of put
on solar screen
 dazzling from behind

data infrastructure
OSM Data PostgreSQL
osm2pgsql
Java
angle of
the sun
Risk assesment
Java
visualization
ArcObjects
result
pgsql2shape
SQL
split
polylines
orientation of
street segments
SQL

results
 733.600.000 evaluations of single
geometries
 403 km (43 %) of highways are
affected in Lower Saxony
 Highway interchange Osnabrück
 forward view: 171 h/a (75 h/a)
 forward view in spite of put on solar
screen: 133 h/a (28 h/a)
 from behind: 63 h/a (44 h)

can we go any further?
 Advises from ACE Auto Club Europa e.V.
 put on solar sreen
 approach crossings slowly
 use trafic lights not expossed to direct sun
 use sun glasses
 clean front window
 keep savety distance

Architecture of a solar risk service
start
end
PSnPZn
tn
t1
PS1PZ1
route (http)
Solar Risk
Service
split geometry
time stamp City-DB
position of the sun
evaluate geometry
deliver evaluated route
synchronize
CityGML
X3D
KML

Automotive risk service
Start
Ziel
PSnPZn
tn
t1
PS1PZ1
route (http)
Solar Risk
Service
split geometry
time stamp City-DB
position of the sun
evaluate geometry
deliver evaluated route
synchronize
CityGML
X3D
KML
field of vision field of vision
building
Automotive risk
service

Further requirements
 semantical enriched 3D-city models: CityGML
 geometries for line of sight analysis (CityGML’s LoD 2 Building model would be best)
 semantical information on function and usage of buildings (attributes are partly available
in the Building class)
 fusion of infrastructure information (geo data) and vehicle sensors used in Advanced
Driver Assistant Systems (ADAS)
 precise position
 interaction with driver
 communication infrastructure

Thank you for your attention !

GI2013 ppt löwner_20130429_geodata_forprivatetransportation_final_print

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GI2013 ppt löwner_20130429_geodata_forprivatetransportation_final_print