Implementation and Evaluation of Mobility Models with OPNET04… · Implementation and Evaluation...
Transcript of Implementation and Evaluation of Mobility Models with OPNET04… · Implementation and Evaluation...
Implementation and Evaluation of Mobility Models with OPNET 1
Lehrstuhl Netzarchitekturen und NetzdiensteInstitut für InformatikTechnische Universität München
Implementation and Evaluation ofMobility Models with OPNET
Abschlussvortrag zur Masterarbeit
von
Thomas Oberwallner
09.04.2013
Betreuer: Alexander von Bodisco
Implementation and Evaluation of Mobility Models with OPNET 2
Implementation and Evaluation of Mobility Models with OPNET 3
Outline
I. Motivation
II. Modules Import of OpenStreetMap (OSM) and routing Mobility model Statistics
III. Evaluation Introduction of scenarios Simulation results
Implementation and Evaluation of Mobility Models with OPNET 4
Motivation
Existing mobility framework in OPNET Mobility models: Random Waypoint/Direction/Walk, Group Mobility Statistics: Spatial node distribution, node speed distribution, link
duration, transient phase
Existing VANET simulators Complex movement models (SUMO/VanetMobiSim) Complex configuration (SUMO) Import of OSM files incomplete (VanetMobiSim) Few statistics about movement (SUMO/VanetMobiSim)
Goal Simulation of traffic on real maps Fast movement model of VANETs with focus on the main aspects of
vehicular movement Simulate accurately enough to evaluate routing protocols Import/Export Traces
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OSM file consists of: Nodes: Points in map with a defined position Ways: Contain references to points, form roads
Creation of routing graph by minimizing road graph Vertex in routing graph: intersection Edge: Connects two intersections
Modules: Import of OSM and Routing
Implementation and Evaluation of Mobility Models with OPNET 6
Creation of routing graph by minimizing road graph Vertex in routing graph: intersection Edge: Connects two intersections
Routing with Dijkstra algorithm
Weight of edges Distance for shortest path Time for quickest path
Pending nodes stored in a Min-Heap
Modules: Import of OSM and Routing
Implementation and Evaluation of Mobility Models with OPNET 7
OSM file consists of: Nodes: Points in map with a defined position Ways: Contain references to points, form roads
Creation of routing graph by minimizing road graph Vertex in routing graph: intersection Edge: Connects two intersections
Routing with A* algorithm Weight of edges
• Distance for shortest path• Time for fastest path
Pending nodes stored in a Min-Heap
Modules: Import of OSM and Routing
Implementation and Evaluation of Mobility Models with OPNET 8
Modules: Mobility model – Trip generation
Routed-Geo-Waypoint Similar to Random Waypoint Random destination Fastest route to destination based on speed limits
Adaptive Destination like in Routed-Geo-Waypoint Fastest route to destination according to average speed of all cars
which drove on sections
“Lévy-Flight” Distance to destination exponentially distributed Drive shortest path to destination
Implementation and Evaluation of Mobility Models with OPNET 9
Modules: Mobility model – Speed
Every car has its desired speed
Speed limits: Drivers obey speed limits depending on desired speed
Behaviour: If no car in front: speed = (desired speed / 100) * speed limit If slower car in front:
• If distance > safety-distance: speed = (desired speed / 100) * speed limit• If distance = safety-distance: speed = speed of car in front• If distance < safety-distance: speed = 0.95 * speed of car in front
Implementation and Evaluation of Mobility Models with OPNET 10
Modules: Mobility model – Traffic signals
Position of traffic signal (TS) extracted from map
Timing: Every TS has a uniform distributed offset [0; 20]s Every TS has a uniform distributed duration [5; 15]s No yellow-phase
Two roads with an angle closest to 180°
have a green signal at the same time
Implementation and Evaluation of Mobility Models with OPNET 11
Modules: Mobility model – Intersections
First in, first out principle
Departure and destination of all cars which crossed the intersection in the previous 2 seconds is stored
Arriving car comes from direction A and drives in direction B
Waiting decision depends on the direction of previous cars: If no car crossed the intersection: ok If cars came from A: ok If cars went from B to A: ok Else: Wait 2 seconds
Implementation and Evaluation of Mobility Models with OPNET 12
Modules: Statistics
Map metrics Size of map
Type of roads
Number of nodes/intersections
Distance between nodes/intersections
Speed limits
Number of traffic signals
Mobility metrics Car speed
Distance of routes
Travel time of routes
Number of cars per section
Relative speed of neighbours
Speed ratio between neighbours
Spatial dependence betweenneighbours
Network metrics Number of neighbours
Neighbour distance
Number of network partitions
Implementation and Evaluation of Mobility Models with OPNET 13
Evaluation: Introduction of scenarios
Characteristic scenarios Lower Manhattan: Parallel roads from north to south and east to west,
traffic signals on most intersections Soest: Radial, concentric ring roads Regensburg: “Normal“ city
Implementation and Evaluation of Mobility Models with OPNET 14
Evaluation: Simulation results – basic features
Number of cars set according to length of road network
The higher the number of cars … the lower the average speed the higher the time until the destination is reached the lower the driven distance the lower the number of crossed intersections the lower the relative speed the higher the number of neighbors the lower the number of network partitions
Adaptive routes produce the fastest routes followed by Lévy-Flight and Geo-Routed-Waypoint routes
Number of cars
Lower Manhattan
Soest Regensburg
500 / 441 / 807 60.50 km/h 48.87 km/h
48.87 km/h
1000 / 883 / 1614
56.68 km/h 23.86 km/h
31.02 km/h
1500 / 1324 / 2421
52.13 km/h 15.88 km/h
21.17 km/h
Implementation and Evaluation of Mobility Models with OPNET 15
Evaluation – Speed on sections in Soest
Implementation and Evaluation of Mobility Models with OPNET 16
Video
Click to edit Master text styles Second level
• Third level– Fourth level
» Fifth level
Implementation and Evaluation of Mobility Models with OPNET 17
Comparison of VANET simulators
Master-Thesis VanetMobiSim SUMO
Import OSM-Files Yes Yes (since current version), but incomplete
Yes (NETCONVERT)
Mobility model Car following, traffic lights, overtaking, individual driver-models
Car following, overtaking or traffic lights
Car following, multilane roads, traffic lights
Trip generation Random, adaptive,distance-based
Random, activity-based, sightseeing
Flow definitions, OD matrices, random, population statistics
Routing A*, fast Dijkstra, slow A*, fast
Statistics Map metrics, mobility metrics, network metrics, simulation performance metrics
Node density Position dump, edgelane traffic, trip/route informationNot aggregated
Import/Export Traces Yes/YesGPX-Format
No/Yes (NS2, GloMoSim, QualNet, NET)
No/Yes(unknown format)
Network Simulation Yes (no hybrid simulation)
No No
Implementation and Evaluation of Mobility Models with OPNET 18
Questions
Thank you for your time and attention.
Questions?
Implementation and Evaluation of Mobility Models with OPNET 19
Classification of synthetic mobility models
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• Third level– Fourth level
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Implementation and Evaluation of Mobility Models with OPNET 20
Modules: Import of OpenStreetMap road maps
File-Format: OSM XML-File contains 3 element types
Node Point in map Contains latitude, longitude, id, (version, timestamp, userid, changeset)
Way Contains references to nodes + additional data like highway type,
speed limit, name, surface, one way
Relation Forms restrictions or areas Contains references to nodes and ways
Important: Guessing of unknown data
Implementation and Evaluation of Mobility Models with OPNET 21
Modules: Import/Export of GPS-Traces
File Format: GPX
Wpt: Waypoint Attributes: Latitude, longitude Elements (optional): Elevation, timestamp
Rte: Route Elements: Name, description, list of route points (wpt)
Trk: Track Elements: Name, description, list of track segments
Trkseg: Track segment Elements: List of waypoints
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Modules: Mobility Model – Overtaking
Overtaking decision depends on: Overtaking enabled by configuration? Driving out of town? Car in front driving its desired speed? Desired speed >> Desired speed of car in front? Car in front not overtaking at the moment? No opposing traffic? Overtake will be completed before arriving at the next intersection?
Following car overtakes by keeping to drive its desired speed
When position of overtaking car has reached its predecessor: Positions in lists are switched
Implementation and Evaluation of Mobility Models with OPNET 23
Evaluation: Simulation results – advanced features
Pause: Average speed of currently moving cars increases Time from start to destination decreases
Driver changes: Variance of driven distance and number of crossed intersections decreases
Individual driver models (Sunday driver vs. Speeder): Low amount of cars: Speeder faster than Sunday drivers High amount of cars: Almost no difference
Overtaking: No differences, because urban scenario has been simulated Low amount of overtaking maneuvers
Implementation and Evaluation of Mobility Models with OPNET 24
Evaluation: Performance of simulation
Time of import of map is <10 seconds in evaluated maps
Simulation duration depends quadratically on number of cars
Disabling periodical statistics speeds up simulation by a factory of 3.5 to 16
Simulations (without statistics) on average 38.5% faster than VanetMobiSim
Memory usage depends quadratically on number of cars
Enabling statistics consumes about 12 MB memory