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dortmund university OMNeT++ Community Summit 2017 LIMoSim: A Lightweight and Integrated Approach for Simulating Vehicular Mobility with OMNeT++ Benjamin Sliwa, Johannes Pillmann, Fabian Eckermann and Christian Wietfeld Bremen, September 07, 2017 Faculty of Electrical Engineering & Information Technology Communication Networks Institute Prof. Dr.-Ing. Christian Wietfeld

dortmund Communication Networks Institute Prof. Dr.-Ing. C. Wietfeld university Outline  Motivation: Convergence of Vehicular Mobility and Communication  State-of-the-art: Coupling based on Interprocess Communication  Proposal: Lightweight ICT-centric Mobility Simulation (LIMoSim)  Integration of LIMoSim into OMNeT++  Proof-of-concept Evaluation in an LTE Context  Conclusion and Future Work Slide 2 Benjamin Sliwa | LIMoSim: A Lightweight and Integrated Approach for Simulating Vehicular Mobility with OMNeT++

dortmund Communication Networks Institute Prof. Dr.-Ing. C. Wietfeld university Convergence of Vehicular Mobility and Communication Communication as a Key Factor for Coordination in Intelligent Transportation Systems (ITS) Mobility-aware Predictive Routing and Cellular Handover Gateway Selection Context-aware Anticipatory Alignment Interface Selection of Pencil Beams Combined Simulation of Vehicular Mobility and Communication Source: Yunfei Hou, Autonomous Intersection in Action, https://youtu.be/4SmJP8TdWTU Slide 3 Benjamin Sliwa | LIMoSim: A Lightweight and Integrated Approach for Simulating Vehicular Mobility with OMNeT++

dortmund Communication Networks Institute Prof. Dr.-Ing. C. Wietfeld university Coupling based on Interprocess Communication Network Simulator Coupling Framework Traffic Simulator Protocol Stack Mobility Mobility Vehicle & Infrastructure control Interface Interface Vehicular Mobility Vehicular Mobility Position & State updates Simulation Control Simulation Control Synchronization Event handling Event handling  Coupling as a side feature of a framework for a specific communication technology (e.g. IEEE 802.11p)  Violation of the modular paradigm  Portability effort: LTE, MANET, IEEE 802.15.4  Limited interaction possibilities – bound to protocol specification  Complex setup – simultaneous execution of multiple processes  Risk of compatibility drifts Demand for IPC-free alternatives for mobility simulation with network simulators IPC – Interprocess Communication Slide 4 Benjamin Sliwa | LIMoSim: A Lightweight and Integrated Approach for Simulating Vehicular Mobility with OMNeT++

dortmund Communication Networks Institute Prof. Dr.-Ing. C. Wietfeld university Simulation of Vehicular Traffic with SUMO High Level of Complexity  Rather a package of different tools than a standalone simulator  Map data import: “Congratulations ! When you performed all the steps so far, you have a map suitable for traffic simulation with SUMO” (Source: http://sumo.dlr.de/wiki/Tutorials/Import_from_OpenStreetMap)  Wide range of different mobility models  External control through TCP-based TraCI Static Approach  Routes are usually precomputed using external tools  Dynamic routing is possible with TraCI, but complicated Demand for lightweight alternatives to SUMO with focus on communication SUMO – Simulation of Urban Mobility TraCI – Traffic Control Interface Slide 5 Benjamin Sliwa | LIMoSim: A Lightweight and Integrated Approach for Simulating Vehicular Mobility with OMNeT++

dortmund Communication Networks Institute Prof. Dr.-Ing. C. Wietfeld university Lightweight ICT-centric Mobility Simulation – LIMoSim SimuLTE Veins INET Applications LTE User Plane Simulation IEEE 802.11p INET / INETMANET Protocol Stack Mobility LIMoSim Kernel Standalone Mode LIMoSim UI Vehicular Mobility Visualization, Editor OMNeT++ Event handling Focus: Seamless Integration Focus: Lightweight Approach   Interaction-level: Shared codebase Relies on selected well-known mobility models  Exploiting synergies  Native support for OSM map data  Independence from the  communication technology Dynamic decision processes Slide 6 Benjamin Sliwa | LIMoSim: A Lightweight and Integrated Approach for Simulating Vehicular Mobility with OMNeT++

dortmund Communication Networks Institute Prof. Dr.-Ing. C. Wietfeld university Hierarchical Mobility Model LIMoSim OMNeT++ / INET Destination StrategicMobility Strategic Mobility Determination Model.ned Trip, Random Destination Destination Path Planning Routing Path Movement on Lane Mobility Model Next Node Following Model Adaptive Cruise Control FollowingModel.ned Intelligent Driver Model Acceleration Position Update LIMoSimCar.ned Slide 7 Benjamin Sliwa | LIMoSim: A Lightweight and Integrated Approach for Simulating Vehicular Mobility with OMNeT++

ሶ dortmund Communication Networks Institute Prof. Dr.-Ing. C. Wietfeld university Car Following Behavior with the Intelligent Driver Model Velocity 𝑤 Distance 𝑡 𝜀 − 𝑡 ∗ 𝑤, ∆𝑤 2 𝑤  𝑤 = 𝑏 1 − Goal : determine the acceleration 𝑤 0 𝑡 with respect to other traffic participants Free Flow Following Behavior 𝑤∆𝑤 𝑡 ∗ 𝑤, ∆𝑤 = 𝑡 0 + 𝑛𝑏𝑦 0, 𝑤𝑈 +  LIMoSim: Traffic Signals are 2 𝑏𝑐 treated as “static vehicles” if the Desired Safety Intelligent Braking Distance state is yellow or red Distance Strategy 𝑤 0 Desired speed 𝑏 Maximum acceleration 𝑈 Time gap 𝑐 Comfortable deceleration 𝑡 0 Minimum distance 𝜀 Acceleration exponent Treiber, M. & Kesting, A., Traffic Flow Dynamics: Data, Models and Simulation , Springer-Verlag Berlin Heidelberg, 2013 Slide 8 Benjamin Sliwa | LIMoSim: A Lightweight and Integrated Approach for Simulating Vehicular Mobility with OMNeT++

dortmund Communication Networks Institute Prof. Dr.-Ing. C. Wietfeld university Representation of Map Data with the OpenSteetMap Data Model 𝑂 3 𝑋 1 = {𝑂 3 , 𝑂 1 , 𝑂 4 } 𝑋 0 = {𝑂 0 , 𝑂 1 , 𝑂 2 } 𝑂 0 𝑂 1 𝑂 2 Intersection 𝑂 4  Nodes as basic entities with identifier and location information  Ways describe street segments with the same properties  Lanes provide alignment references for vehicles  Automatic detection of intersection nodes Slide 9 Benjamin Sliwa | LIMoSim: A Lightweight and Integrated Approach for Simulating Vehicular Mobility with OMNeT++

dortmund Communication Networks Institute Prof. Dr.-Ing. C. Wietfeld university Integration of LIMoSim Events into OMNeT++  LIMoSim objects are not aware of their OMNeT++ Environment  Cannot be derived from cModule / cSimpleModule  How to integrate event-based behavior? Virtual LIMoSim EventQueue schedule(Event*) handle(Event*) EventMapping<Event*,cMessage*> scheduleAt(cMessage*) handleMessage(cMessage*) OMNeT++ 0 0 1.2 1.4 2.3 2.4 2.7 3.1 3.3 3.5 EventQueue Transparent embedding of events without requiring actual OMNeT++ modules Slide 10 Benjamin Sliwa | LIMoSim: A Lightweight and Integrated Approach for Simulating Vehicular Mobility with OMNeT++

dortmund Communication Networks Institute Prof. Dr.-Ing. C. Wietfeld university Setup of a Vehicular LTE Scenario with LIMoSim and SimuLTE <node id="677230875" x="272.392" y="368.178"/> *.ue.mobilityType = "LIMoSimCar" <node id="275672221" x="1141.36" y="499.156"/> *.ue.mobility.map = "map.osm" <node id="3569208993" x="1060.36" y="897.189"/> *.ue.mobility.strategicModel = "Trip" <node id="477807" x="254.202" y="767.967"/> *.ue.mobility.strategicModel.trip = "677230875, <way id=" 337055293 "> 275672221,3569208993,477807" <nd ref="677231620"/> *.ue.mobility.way = " 337055293 " Random position <nd ref="677231627"/> *.ue.mobility.segment = 4 if undefined <nd ref="627846556"/> *.ue.mobility.lane = 0 <nd ref="677231621"/> *.ue.mobility.offset = 1m <nd ref="52919181"/> <nd ref="477807"/> # interference traffic <nd ref="3441521491"/> *.car[].mobilityType = "LIMoSimCar" <tag k="lanes" v="2"/> *.car[].mobility.map = "map.osm" </way> *.car[].mobility.strategicModel = "RandomDestination" map.osm.limo omnetpp.ini  Optimized map file *.limo is generated automatically  Node IDs can be obtained from the LIMoSim UI  Optional configuration via XML XML – Signal-to-noise ratio Slide 11 Benjamin Sliwa | LIMoSim: A Lightweight and Integrated Approach for Simulating Vehicular Mobility with OMNeT++

dortmund Communication Networks Institute Prof. Dr.-Ing. C. Wietfeld university Reference Scenario: University Campus of the TU Dortmund Simulation Value Parameter Strategic mobility Trip model (UE) Strategic mobility model (interference Random Direction traffic) Number of 100 interference cars Following model IDM Speed factor (driver 1 ± [ 0…0.2 ] behavior) Carrier frequency 1800 [MHz] eNode B 46 [dBm] transmission power eNode B antenna Omnidirectional  Sensing of the LTE signal strength using an LTE-enabled car Slide 12 Benjamin Sliwa | LIMoSim: A Lightweight and Integrated Approach for Simulating Vehicular Mobility with OMNeT++