SUMO2018: Author Index| Author | Papers |
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| A | | Acosta, Andrés | A new strategy for synchronizing traffic flow on a distributed simulation using SUMO | | Alazzawi, Sabina | Simulating the Impact of Shared, Autonomous Vehicles on Urban Mobility – a Case Study of Milan | | Arroyo, Nicolas | A new strategy for synchronizing traffic flow on a distributed simulation using SUMO | | Aswakul, Chaodit | Chula-SSS: Developmental Framework for Signal Actuated Logics on SUMO Platform in Over-saturated Sathorn Road Network Scenario | | B | | Baksa, Zoltan | Simulation of Autonomous RoboShuttles in Shared Space | | Barthauer, Mirko | Coupling traffic and driving simulation: Taking advantage of SUMO and SILAB together | | Bayen, Alexandre | Flow: Deep Reinforcement Learning for Control in SUMO | | Behrisch, Michael | Analysis of the traffic behavior of emergency vehicles in a microscopic traffic simulation Improving SUMO's Signal Control Programs by Introducing Route Information Route estimation based on network flow maximization | | Beutelschieß, Stephan | Simulation of Autonomous RoboShuttles in Shared Space | | Bieker-Walz, Laura | Analysis of the traffic behavior of emergency vehicles in a microscopic traffic simulation | | Bósa, Károly | Calibrating Traffic Simulation Models in SUMO Based upon Diverse Historical Real-Time Traffic Data – Lessons Learned in ITS Upper Austria | | C | | Codeca, Lara | Monaco SUMO Traffic (MoST) Scenario: A 3D Mobility Scenario for Cooperative ITS | | D | | Dingil, Ali Enes | Road network extraction with OSMNx and SUMOPy | | E | | Erdmann, Jakob | Route estimation based on network flow maximization Multi-Level-Validation of Chinese traffic in the ChAoS framework | | Espinosa, Jairo | A new strategy for synchronizing traffic flow on a distributed simulation using SUMO | | Espinosa, Jorge | A new strategy for synchronizing traffic flow on a distributed simulation using SUMO | | F | | Filippi, Francesco | Generating activity based, multi-modal travel demand for SUMO | | Flitsch, Christina | Calibrating Traffic Simulation Models in SUMO Based upon Diverse Historical Real-Time Traffic Data – Lessons Learned in ITS Upper Austria | | Flötteröd, Yun-Pang | Improving SUMO's Signal Control Programs by Introducing Route Information | | Friedrich, Bernhard | Multi-Level-Validation of Chinese traffic in the ChAoS framework | | G | | Gasper, Rainer | Simulation of Autonomous RoboShuttles in Shared Space | | H | | Hafner, Alexander | Coupling traffic and driving simulation: Taking advantage of SUMO and SILAB together | | Hummel, Mathias | Simulating the Impact of Shared, Autonomous Vehicles on Urban Mobility – a Case Study of Milan | | Härri, Jérôme | Monaco SUMO Traffic (MoST) Scenario: A 3D Mobility Scenario for Cooperative ITS | | J | | Jung, Martin | Simulating a multi-airport region on different abstraction levels by coupling several simulations | | Junghans, Marek | Analysis of the traffic behavior of emergency vehicles in a microscopic traffic simulation | | K | | Kastner, Karl-Heinz | Calibrating Traffic Simulation Models in SUMO Based upon Diverse Historical Real-Time Traffic Data – Lessons Learned in ITS Upper Austria | | Kheterpal, Nishant | Flow: Deep Reinforcement Learning for Control in SUMO | | Komolkiti, Patrachart | Chula-SSS: Developmental Framework for Signal Actuated Logics on SUMO Platform in Over-saturated Sathorn Road Network Scenario | | Kordt, Pascal | Simulating the Impact of Shared, Autonomous Vehicles on Urban Mobility – a Case Study of Milan | | Kreidieh, Aboudy | Flow: Deep Reinforcement Learning for Control in SUMO | | Krisanachantara, Chonti | Chula-SSS: Developmental Framework for Signal Actuated Logics on SUMO Platform in Over-saturated Sathorn Road Network Scenario | | Krumnow, Mario | Simulation of Autonomous RoboShuttles in Shared Space | | M | | Mintsis, Evangelos | Assessment of ACC and CACC systems using SUMO | | Mitsakis, Evangelos | Assessment of ACC and CACC systems using SUMO | | N | | Neubauer, Matthias | Calibrating Traffic Simulation Models in SUMO Based upon Diverse Historical Real-Time Traffic Data – Lessons Learned in ITS Upper Austria | | Noyer, Ulf | Simulating a multi-airport region on different abstraction levels by coupling several simulations | | P | | Parvate, Kanaad | Flow: Deep Reinforcement Learning for Control in SUMO | | Poliziani, Cristian | Generating activity based, multi-modal travel demand for SUMO | | Porfyri, Kallirroi N. | Assessment of ACC and CACC systems using SUMO | | R | | Rudolph, Florian | Simulating a multi-airport region on different abstraction levels by coupling several simulations | | Rupi, Federico | Road network extraction with OSMNx and SUMOPy Generating activity based, multi-modal travel demand for SUMO | | S | | Schwarzer, Jochen | Simulation of Autonomous RoboShuttles in Shared Space | | Schweizer, Joerg | Road network extraction with OSMNx and SUMOPy Generating activity based, multi-modal travel demand for SUMO | | Semrau, Marc | Multi-Level-Validation of Chinese traffic in the ChAoS framework | | Shafiq, Muhammad | Dynamic Route Optimization for Heterogeneous Agent Envisaging Topographic of Maps | | Sickenberger, Thorsten | Simulating the Impact of Shared, Autonomous Vehicles on Urban Mobility – a Case Study of Milan | | Simon, Levente | Simulation of Autonomous RoboShuttles in Shared Space | | Stasiskiene, Zaneta | Road network extraction with OSMNx and SUMOPy | | T | | Techakittiroj, Kittiphan | Chula-SSS: Developmental Framework for Signal Actuated Logics on SUMO Platform in Over-saturated Sathorn Road Network Scenario | | V | | Vinitsky, Eugene | Flow: Deep Reinforcement Learning for Control in SUMO | | W | | Watarakitpaisarn, Sorawee | Chula-SSS: Developmental Framework for Signal Actuated Logics on SUMO Platform in Over-saturated Sathorn Road Network Scenario | | Wieseotte, Christian | Simulating the Impact of Shared, Autonomous Vehicles on Urban Mobility – a Case Study of Milan | | Wohak, Oliver | Simulating the Impact of Shared, Autonomous Vehicles on Urban Mobility – a Case Study of Milan | | Wu, Cathy | Flow: Deep Reinforcement Learning for Control in SUMO |
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