Team: Alberto Debiasi , Stefano Piffer, Daniele Magliocchetti and Raffaele De

Amicis

WorldWind Challenge

Nowadays is extremely important to monitor and analyze the urban environment and in particular the urban viability.

In recent years, microscopic traffic simulations have become an increasingly active field of research in transport engineering.

However, often these tools lack in usability and visualization makes it difficult to extract useful information.

Simplifying the interface and improving the usability of these tools can reduce the learning curve substantially.

The added value of our work is the capability to simplify the complex interactions related to traffic analysis, using visualization tools which are able to translate into drawing action the complex input of the traffic simulation.

Develop an interactive system

For the analysis of urban scenario

The test study is the city of Trento

The setup phase is made through drawing actions

The results are generated through graphical components

The generated model is based on the following assumption:

• We suppose that vehicles that start in the same geographical area share the same destinations

Each vehicle is managed as an individual entity by the system.

Each vehicle chooses the route accordingly to the length and the level of congestion of each road.

The user can redirect groups of vehicles located from the same macro area to one or more macro areas.

Visual Analytics tool

Visualization layer

Simulation layer

Jgraph library

WorldWind SDK

Local Data layer

Remote Data layer

WFS request Example of wfs url ...

3D model of the buildings

model of the roads

Road network Cadastral Information

WorldWind Server

DSM & DTM

Vehicle Manager

Render Module

Emitter Manager Parking Area Manager

Not only used as virtual globe

Not only used as visual tool for geographical data

But extended as interactive system performing analysis of urban traffic

http://worldwind.arc.nasa.gov/java/

JGraph is a graph drawing open source software component written in Java.

It contains different algorithms for the shortest path problem.

It is used for the routing of the generated vehicles.

http://www.jgraph.com/

• The digital surface model (DSM) is used to visualize the map of the city.

• It’s a feature already implemented in worldwind.

http://localhost:8080/wms? service=WMS &request=GetMap&version=1.3.0 &crs=CRS:84 &layers=layername &width=512&height=512 &format=image/jpeg &bbox=162.0,-18.0,180.0,0.0&

Example Request Example Response

• The Road Network is loaded in KML format.

• It’s exported from http://www.openstreetmap.org/

<Placemark> <name>Via Vittorio Veneto</name> <Style><LineStyle><color>ff0000ff</color></LineStyle> <PolyStyle><fill>0</fill></PolyStyle></Style> <ExtendedData><SchemaData schemaUrl="#Roads_Geo_WGS84"> <SimpleData name="Name">Via Vittorio Veneto</SimpleData> <SimpleData name="GM_LAYER">highway - residential</SimpleData> <SimpleData name="GM_TYPE">Residential Road</SimpleData> <SimpleData name="id">37133037</SimpleData> <SimpleData name="highway">residential</SimpleData> <SimpleData name="oneway">yes</SimpleData> </SchemaData></ExtendedData> <LineString> <coordinates> 11.125013399999998,46.058851999999987 11.124864099999998,46.05905139999999 4</coordinates> </LineString> </Placemark>

Example KML Example Result in WorldWind

• 3d Model of the buildings in .shp format

• Model of the roads in .shp format

Example Result in WorldWind

• The cadastral information is exposed as WFS • It contains information about the estimated number of persons for each building • Provided by Protezione Civile • We use this information to estimate the number of vehicles for each building

<?xml version="1.0" encoding="UTF-8"?> <wfs:FeatureCollection > <gml:featureMember> <cite:Home_emitter fid="Home_emitter.1741"> <cite:the_geom> <gml:Point srsName="http://www.opengis.net/gml/srs/epsg.xml#4326"> <gml:coordinates>11.12988077,46.06052735</gml:coordinates> </gml:Point> </cite:the_geom> <cite:GINO_ID>52057</cite:GINO_ID> <cite:TIPO>Civile</cite:TIPO> <cite:POPRES>221.0</cite:POPRES> <cite:MAX_AREA>250.486199982</cite:MAX_AREA> <cite:SUM_AREA>4548.05984997</cite:SUM_AREA> <cite:AREAP>0.0550753965966</cite:AREAP> <cite:POP_P2>12.17</cite:POP_P2> <cite:POP_P>12</cite:POP_P> <cite:NEAR_X>11.1298807704</cite:NEAR_X> <cite:NEAR_Y>46.0605273517</cite:NEAR_Y> </cite:Home_emitter> </gml:featureMember> </wfs:FeatureCollection>

http://serviceUrl/geoserver/wfs?request=GetFeature

<wfs:GetFeature service="WFS" version="1.0.0" outputFormat="GML2"> <wfs:Query typeName="cite:Home_emitter"> <ogc:Filter> <Intersects> <PropertyName>the_geom</PropertyName> <gml:Polygon> <gml:outerBoundaryIs><gml:LinearRing><gml:coordinates> 11.1295,46.061 11.13,46.061 11.13,46.0605 11.1295,46.0605 11.1295,46.061 </gml:coordinates></gml:LinearRing></gml:outerBoundaryIs> </gml:Polygon> </Intersects> </ogc:Filter> </wfs:Query> </wfs:GetFeature>

Example Request Example Response

Drawing actions for the creation of geographical features

Panel of graphical layers

Panel of operations

The departure area is where the vehicles are generated

The departure area is colored white

The departure area contains the Emitters:

•One for each building

•Generates vehicles accordingly with the estimated number of people living in the associated building

The destination area is where the vehicles will arrive

The destination area contains the Parking lots:

• Randomly generated inside the area

• Fixed capacity of vehicles

• Remove vehicles from the system

The dangerous area is where vehicles cannot transit

It can be generated by the user or imported as KML file

• For example can be an output of a system for modeling gas dispersion

Matlab tool

KML

Vehicle is reaching the destination area

Vehicle is searching for an empty parking lot

speed:=Random(minSpeed, maxSpeed)

if (currNextCarDistance < MAX_CAR_DISTANCE &NCarsInFront > N_CARS_TO_SURPASS){ speed:=nextCarSpeed }else{ speed:=regularSpeed }

weight = road.getLength()+ CAR_PENALTY * road.getNumCars()

When a car is generated the speed is a random value:

The speed changes accordingly with the other cars in the same road: If the car is near another vehicle and the number of cars in front of it is more than 3 then the speed is decreased.

The routing path is based on the Dijkstra algorithm: The weight depends on the length of the road and on the number of vehicles

The routing path is updated every N_STEPS in order to improve the performance.

The color of the vehicle defines its target destination.

for (Emitter emitter : emitters) {

if(emitter.isActive()){

long newTime = System.currentTimeMillis();

long timeRange = newTime - lastTime;

if(NumTotalCars()<NUM_MAX_CARS){

if((indexGeneratedCars>BLOCK_SIZE_GENERATED_CARS)&&(timeRange < CAR_FREQUENCY)){

wait=true;

indexGeneratedCars=0;

}

if(!wait){

Car car = emitter.emitCar();

lastTime=0;

indexGeneratedCars++;

}

}

else if (timeDelta > CAR_FREQUENCY){

wait=false;

}

}}}

The number and the frequency of generated vehicles affect on the performance of the system.

In order to reduce this issue:

• Only a specific number of vehicles can be managed by the system.

• Only a specific number of vehicles can be generated in a range of time.

• example: at most 25 cars can be generated every 3 seconds

No congested

road

High congested

road

Each road has an extruded line

The color represents the level of congestion of the road

The elevation represents the number of vehicles are passed on the road over the entire simulation

Full Parking

Lot

Empty Parking

Lot

The color represents the availability of the parking area.

• Add traffic lights

• Real parking area Improve the

simulation model

• Show summary information for each area

• N° available parking lots

• avg speed of vehicles

Improve the visual analysis

https://interactivesystem.collaborate.org/dashboard