An Open-Source Microscopic Traffic Simulator

We present the interactive Java-based open-source traffic simulator available at www.traffic-simulation.de. In contrast to most closed-source commercial simulators, the focus is on investigating fundamental issues of traffic dynamics rather than simulating specific road networks. This includes testing theories for the spatiotemporal evolution of traffic jams, comparing and testing different microscopic traffic models, modeling the effects of driving styles and traffic rules on the efficiency and stability of traffic flow, and investigating novel ITS technologies such as adaptive cruise control, inter-vehicle and vehicle-infrastructure communication

An hybrid simulation tool for autonomous cars in very high traffic scenarios

International audienceThis article introduces an open source tool for simulating autonomous vehicles in complex, high traffic, scenarios. The proposed approach consists on creating an hybrid simulation, which fully integrates and synchronizes two well known simulators: a microscopic, multi-modal traffic simulator and a complex 3D simulator. The presented software tool allows to simulate an autonomous vehicle, including all its dynamics, sensors and control layers, in a scenario with a very high volume of traffic. The hybrid simulation creates a bi-directional integration, meaning that, in the 3D simulator, the ego-vehicle sees and interacts with the rest of the vehicles, and at the same time, in the traffic simulator, all additional vehicles detect and react to the actions of the ego-vehicle. Two interfaces, one for each simulator, where created to achieve the integration, they ensure the synchronization of the scenario, the state of all vehicles including the ego-vehicle, and the time. The capabilities of the hybrid simulation was tested with different models for the ego-vehicle and almost 300 additional vehicles in a complex merge scenario

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

Traffic signal control is an emerging application scenario for reinforcement learning. Besides being as an important problem that affects people's daily life in commuting, traffic signal control poses its unique challenges for reinforcement learning in terms of adapting to dynamic traffic environment and coordinating thousands of agents including vehicles and pedestrians. A key factor in the success of modern reinforcement learning relies on a good simulator to generate a large number of data samples for learning. The most commonly used open-source traffic simulator SUMO is, however, not scalable to large road network and large traffic flow, which hinders the study of reinforcement learning on traffic scenarios. This motivates us to create a new traffic simulator CityFlow with fundamentally optimized data structures and efficient algorithms. CityFlow can support flexible definitions for road network and traffic flow based on synthetic and real-world data. It also provides user-friendly interface for reinforcement learning. Most importantly, CityFlow is more than twenty times faster than SUMO and is capable of supporting city-wide traffic simulation with an interactive render for monitoring. Besides traffic signal control, CityFlow could serve as the base for other transportation studies and can create new possibilities to test machine learning methods in the intelligent transportation domain.Comment: WWW 2019 Demo Pape

From Drivers to Athletes -- Modeling and Simulating Cross-Country Sking Marathons

Traffic flow of athletes in classic-style cross-country ski marathons, with the Swedish Vasaloppet as prominent example, represents a non-vehicular system of driven particles with many properties of vehicular traffic flow such as unidirectional movement, the existence of lanes, and, moreover, severe traffic jams. We propose a microscopic acceleration and track-changing model taking into account different fitness levels, gradients, and interactions between the athletes in all traffic situations. The model is calibrated on microscopic data of the $\textit{Vasaloppet 2012}$ Using the multi-model open-source simulator MovSim.org, we simulate all 15 000 participants of the Vasaloppet during the first ten kilometers.Comment: 8 pages, contribution to the conference Traffic and Granular Flow '13 in Juelich. Will be included in the Conference proceedings (Springer

SimMobility Short-Term: An Integrated Microscopic Mobility Simulator

This paper presents the development of an integrated microscopic mobility simulator, SimMobility Short-Term (ST). The simulator is integrated because its models, inputs and outputs, simulated components, and code base are integrated within a multiscale agent- and activity-based simu- lation platform capable of simulating different spatiotemporal resolutions and accounting for different levels of travelers’ decision making. The simulator is microscopic because both the demand (agents and its trips) and the supply (trip realization and movements on the network) are microscopic (i.e., modeled individually). Finally, the simulator has mobility because it copes with the multimodal nature of urban networks and the need for the flexible simulation of innovative transportation ser - vices, such as on-demand and smart mobility solutions. This paper follows previous publications that describe SimMobility’s overall framework and models. SimMobility is an open-source, multiscale platform that considers land use, transportation, and mobility-sensitive behavioral models. SimMobility ST aims at simulating the high-resolution movement of agents (traffic, transit, pedestrians, and goods) and the operation of different mobility services and control and information systems. This paper presents the SimMobility ST modeling framework and system architecture and reports on its successful calibration for Singapore and its use in several scenarios of innovative mobility applications. The paper also shows how detailed performance measures from SimMobility ST can be integrated with a daily activity and mobility patterns simulator. Such integration is crucial to model accurately the effect of different technologies and service operations at the urban level, as the identity and preferences of simulated agents are maintained across temporal decision scales, ensuring the consistency and accuracy of simulated accessibility and performance measures of each scenario.Singapore. National Research Foundation (CREATE program)Singapore-MIT Alliance. Center. Future Urban Mobility Interdisciplinary Research Grou