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Journal ArticleDOI

A microscopic traffic simulator for evaluation of dynamic traffic management systems

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TLDR
The simulator is a component of a larger system for evaluating traffic management systems and interacts with a surveillance module that can represent a wide variety of sensors and a traffic management module which sets traffic signals and signs, routing recommendations, etc.
Abstract
A MIcroscopic Traffic SIMulator (MITSIM) has been developed for modeling traffic networks with advanced traffic control, route guidance and surveillance systems. MITSIM represents networks in detail and simulates individual vehicle movements using car following, lane changing, and traffic signal responding logic. A probabilistic route choice model is used to capture drivers' route choice decisions in the presence of real time traffic information provided by route guidance systems. The simulator is a component of a larger system for evaluating traffic management systems and interacts with a surveillance module that can represent a wide variety of sensors (e.g. loop detectors, area sensors, probe vehicles, etc.) and a traffic management module which sets traffic signals and signs, routing recommendations, etc. MITSIM is coded in C+ + using object-oriented design and supports distributed implementation. It includes a graphical user interface for animating vehicle movements in the network and displaying aggregate traffic information such as speed and density.

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Citations
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Proceedings Article

A framework of real-time traffic information system

TL;DR: A framework of implementing real-time traffic simulation on urban network, which consists of Path generation, Dynamic Origin-Destination Estimation and Link Dynamics, and the LWR model is used to describe the macroscopic traffic flow in Link Dynamics.
Proceedings ArticleDOI

Towards Smart Traffic Lights based on Deep Learning and Traffic Flow Information

TL;DR: In this paper , a deep learning model based on the bidirectional LSTM architecture is proposed to estimate the appropriate duration of traffic lights by learning traffic flow information, which achieves high accuracy and is lightweight enough to deploy resource-constrained IoT devices.
Proceedings ArticleDOI

Controlled Networks to Solve Traffic Flows Problem

TL;DR: In this article , the optimal control problem of traffic flows in the city road network is considered, where the control is performed by means of traffic lights at regulated intersections, and evolutionary algorithms are used to solve this problem in particular to determine the duration of the traffic light phases in accordance with the control quality criteria.
Journal ArticleDOI

A Survey on Mixed Traffic Flow Characteristics in Connected Vehicle Environments

TL;DR: The current research status of traffic flow characteristics under connected vehicle environments to some extent is summarized to provide references for future traffic flow characteristic research in terms of framework, methods and technologies, etc.
Proceedings ArticleDOI

Towards a Review on Simulated ADAS/AD Testing

TL;DR: In this paper , the authors investigate previous surveys that cover multiple scenarios and initiate a systematic review targeting simulators for testing ADAS/AD, finding that the most popular simulators are CARLA, Airsim, and SUMO.
References
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Book

Network Flows: Theory, Algorithms, and Applications

TL;DR: In-depth, self-contained treatments of shortest path, maximum flow, and minimum cost flow problems, including descriptions of polynomial-time algorithms for these core models are presented.
Journal ArticleDOI

PVM: Parallel virtual machine: a users' guide and tutorial for networked parallel computing

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Journal ArticleDOI

A model for the structure of lane-changing decisions

TL;DR: A structure is proposed to connect the decisions which a driver has to make before changing lanes to ensure that the vehicles in traffic simulations behave logically when confronted with situations commonly encountered in real traffic.
Journal ArticleDOI

A probabilistic multipath traffic assignment model which obviates path enumeration

TL;DR: A probabilistic assignment model that attempts to circumvent path enumeration, in such a way that the resulting effect is identical to what would have been obtained if each path had been assigned trips separately under certain choice probability assumptions.
Journal ArticleDOI

Traffic Dynamics: Analysis of Stability in Car Following

TL;DR: “Acceleration noise” is proposed as a parameter that might be employed to characterize the driver-car-road complex under various conditions and some preliminary experimental measurements of acceleration noise are discussed.
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