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Open AccessProceedings ArticleDOI

Microscopic Traffic Simulation using SUMO

TLDR
The latest developments concerning intermodal traffic solutions, simulator coupling and model development and validation on the example of the open source traffic simulator SUMO are presented.
Abstract
Microscopic traffic simulation is an invaluable tool for traffic research. In recent years, both the scope of research and the capabilities of the tools have been extended considerably. This article presents the latest developments concerning intermodal traffic solutions, simulator coupling and model development and validation on the example of the open source traffic simulator SUMO.

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Journal ArticleDOI

Deep Reinforcement Learning for Autonomous Driving: A Survey

TL;DR: This review summarises deep reinforcement learning algorithms, provides a taxonomy of automated driving tasks where (D)RL methods have been employed, highlights the key challenges algorithmically as well as in terms of deployment of real world autonomous driving agents, the role of simulators in training agents, and finally methods to evaluate, test and robustifying existing solutions in RL and imitation learning.
Journal ArticleDOI

Deep Reinforcement Learning for Autonomous Driving: A Survey

TL;DR: The authors provides a taxonomy of automated driving tasks where deep reinforcement learning (DRL) methods have been employed, while addressing key computational challenges in real world deployment of autonomous driving agents and delineates adjacent domains such as behavior cloning, imitation learning, inverse reinforcement learning that are related but are not classical RL algorithms.
Journal ArticleDOI

A digital twin smart city for citizen feedback

TL;DR: A public and open digital twin of the Docklands area in Dublin, Ireland is demonstrated and it is shown how this model can be used for urban planning of skylines and green space allowing users to interact and report feedback on planned changes.
Proceedings ArticleDOI

CityFlow: A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenario

TL;DR: A new traffic simulator CityFlow with fundamentally optimized data structures and efficient algorithms that can support flexible definitions for road network and traffic flow based on synthetic and real-world data and provides user-friendly interface for reinforcement learning.
Proceedings ArticleDOI

TrafficSim: Learning to Simulate Realistic Multi-Agent Behaviors

TL;DR: In this paper, the authors propose TrafficSim, a multi-agent behavior model for realistic traffic simulation, in which the policy is parameterized with an implicit la-tent variable model that generates socially consistent plans for all actors in the scene jointly.
References
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Recent Development and Applications of SUMO - Simulation of Urban MObility

TL;DR: The current state of the SUMO package, its major applications, both by research topic and by example, as well as future developments and extensions are described.
Journal ArticleDOI

Bidirectionally Coupled Network and Road Traffic Simulation for Improved IVC Analysis

TL;DR: The hybrid simulation framework Veins (Vehicles in Network Simulation), composed of the network simulator OMNeT++ and the road traffic simulator SUMO, is developed and can advance the state-of-the-art in performance evaluation of IVC and provide means to evaluate developed protocols more accurately.

Microscopic modeling of traffic flow: investigation of collision free vehicle dynamics.

Stefan Krauss
TL;DR: A microsopic model of traffic flow is proposed, adding to the understanding of the different types of congestion found in traffic flow, to find out how to optimize traffic with respect to a reduction of environmental impacts and economical loss due to congestion.
Proceedings ArticleDOI

TraCI: an interface for coupling road traffic and network simulators

TL;DR: This article presents TraCI a technique for interlinking road traffic and network simulators that permits us to control the behavior of vehicles during simulation runtime, and consequently to better understand the influence of VANET applications on traffic patterns.
Proceedings ArticleDOI

Plexe: A platooning extension for Veins

TL;DR: P Plexe as discussed by the authors is an Open Source extension to Veins that offers researchers a simulation environment able to run experiments in realistic scenarios, taking into account physics and mechanics of the vehicles, communications and networking impairments, and Inter-Vehicle Communication (IVC) protocol stacks.
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