SUMO 2018- Simulating Autonomous and Intermodal Transport Systems17 articles•217 pages•Published: June 25, 2018 PapersPages 1-13 | Pages 14-24 | Pages 25-42 | Pages 43-55 | Pages 56-66 | Pages 67-81 | Pages 82-93 | Pages 94-110 | Pages 111-117 | Pages 118-133 | Pages 134-151 | Pages 152-161 | Pages 162-172 | Pages 173-182 | Pages 183-193 | Pages 194-205 | Pages 206-217 |
Keyphrases3D Traffic Scenario, Activity based demand, Activity-based model, Adaptive Cruise Control (ACC), Advanced Driving Assistance Systems, autonomous driving2, autonomous vehicles, communication, Connected and Automated Vehicle, Cooperative Adaptive Cruise Control (CACC), Cooperative Intelligent Transportation Systems, coupled simulation, data-fusion in ITS, Deep Reinforcement Learning, Dijikstra SUMO topographic Road Netwoks OSM, distributed traffic simulation, driver model, Driving Simulation, Dyanic Route Optimization, Emergency Vehicles, heterogeneous agent, Heterogeneous traffic, Intermodal Mobility, Learning and Adaptive Systems, Mesoscopic Traffic Simulation, micro-simulation, microscopic modelling, microscopic simulation, microscopic traffic simulation, microsimulation, multi-airport region, network flow, network performance, NetworkX, operation strategy, Optimode.net, OSM, OSMnx, Rescue lanes, ride-sharing, road network, Route estimation, Routing, shared space, Signal Adaptation, SUMO3, synchronization, traffic data, traffic microsimulation, traffic signal control, traffic simulation4, traffic valiadtion, urban mobility, vehicle dynamics, Webster |
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