Search Results - "Codeca, Lara"

SAGA: An Activity-based Multi-modal Mobility ScenarioGenerator for SUMO by Codeca, Lara, Jakob ERDMANN, Vinny CAHILL, Jerome Haerri

“…In this paper, we define a workflow and a toolchain to support fast mobility scenario prototyping based on open data and open-source software. SAGA is an…”
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Using Deep Reinforcement Learning to Coordinate Multi-Modal Journey Planning with Limited Transportation Capacity by Codeca, Lara, Cahill, Vinny

“…Multi-modal journey planning for large numbers of simultaneous travellers is a challenging problem, particularly in the presence of limited transportation…”
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A digital twin smart city for citizen feedback by White, Gary, Zink, Anna, Codecá, Lara, Clarke, Siobhán

“…A digital twin is a digital representation of a physical process, person, place, system or device. Digital twins were originally designed to improve…”
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Multi-Agent Deep Reinforcement Learning for Large-Scale Traffic Signal Control by Chu, Tianshu, Wang, Jie, Codeca, Lara, Li, Zhaojian

“…Reinforcement learning (RL) is a promising data-driven approach for adaptive traffic signal control (ATSC) in complex urban traffic networks, and deep neural…”
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Improving traffic in urban environments applying the Wardrop equilibrium by Codeca, Lara, Frank, Raphael, Engel, Thomas

“…Over the last few years vehicular traffic density has continuously increased and it is likely that the traffic demand will further increase in the future. In…”
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Luxembourg SUMO Traffic (LuST) Scenario: 24 hours of mobility for vehicular networking research by Codeca, Lara, Frank, Raphael, Engel, Thomas

“…Different research communities varying from telecommunication to traffic engineering are working on problems related to vehicular traffic congestion,…”
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Luxembourg SUMO Traffic (LuST) Scenario: Traffic Demand Evaluation by Codeca, Lara, Frank, Raphael, Faye, Sebastien, Engel, Thomas

“…Both the industrial and the scientific communities are working on problems related to vehicular traffic congestion, intelligent transportation systems, and…”
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Towards multimodal mobility simulation of C-ITS: The Monaco SUMO traffic scenario by Codeca, Lara, Harri, Jerome

“…The information that we are collecting in the cities is enhancing our understanding of their dynamics. Cooperative Intelligent Transportation Systems (C-ITS)…”
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A SUMO-Based Parking Management Framework for Large-Scale Smart Cities Simulations by CODECA, Lara, ERDMANN, Jakob, HARRI, Jerome

“…We collectively decided that investing in smart cities, and consequently smart mobility, is the appropriate direction to solve traffic congestion and…”
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Comparing Multi-Modal Traffic Assignments in Large-Scale Simulations using the Macroscopic Fundamental Diagram: Mode Shift from Cars to Powered Two Wheelers by Codeca, Lara, VITI, Francesco, Cahill, Vinny, Harri, Jerome

“…The Macroscopic Fundamental Diagram (MFD) relates traffic flow (vehicles/hour) and density (vehicles/km), and can be used to support decisions on how to…”
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IoT and Microservices Based Testbed for Connected Car Services by Kanti Datta, Soumya, Irfan Khan, Mohammad, Codeca, Lara, Denis, B., Harri, Jerome, Bonnet, Christian

“…The Internet of Things (IoT) has accelerated the innovations in the connected car domain. Together with Intelligent Transportation Systems (ITS), the IoT…”
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Traffic routing in urban environments: The impact of partial information by Codeca, Lara, Frank, Raphael, Engel, Thomas

“…There are many studies concerning the problem of traffic congestion in cities. One of the best accepted solutions to relieving congestion involves optimization…”
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A Car Hacking Experiment: When Connectivity Meets Vulnerability by Jafarnejad, Sasan, Codeca, Lara, Bronzi, Walter, Frank, Raphael, Engel, Thomas

“…Interconnected vehicles are a growing commodity providing remote access to onboard systems for monitoring and controlling the state of the vehicle. Such…”
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On the evaluation of make-before-break handovers in urban WiFi networks for moving vehicles by Mouton, Maximilien, Castignani, German, Frank, Raphael, Codeca, Lara, Engel, Thomas

“…Due to the increasing deployment of city-wide IEEE 802.11 networks for nomadic Internet access, there is a great potential for users wanting to access the…”
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Multi-Agent Deep Reinforcement Learning for Large-scale Traffic Signal Control by Chu, Tianshu, Wang, Jie, Codecà, Lara, Li, Zhaojian

“…Reinforcement learning (RL) is a promising data-driven approach for adaptive traffic signal control (ATSC) in complex urban traffic networks, and deep neural…”
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