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Fundamentals of Transportation and Traffic Operations

TLDR
This book contains chapters on "tools", covering topics such as graphical methods, optimization, probability, stochastic processes, statistics and simulation, which are complemented by application chapters on traffic dynamics, control, observation, and scheduled modes.
Abstract
Presents the basic concepts in the transportation and traffic operations field. This book contains chapters on "tools", covering topics such as graphical methods, optimization, probability, stochastic processes, statistics and simulation, which are complemented by application chapters on traffic dynamics, control, observation, and scheduled modes.

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Journal ArticleDOI

Traffic and related self-driven many-particle systems

TL;DR: This article considers the empirical data and then reviews the main approaches to modeling pedestrian and vehicle traffic, including microscopic (particle-based), mesoscopic (gas-kinetic), and macroscopic (fluid-dynamic) models.
Journal ArticleDOI

The physics of traffic jams

TL;DR: In this paper, a car-following model is proposed to investigate the bunching transition and bus delay in traffic flow and pedestrian flow, and detailed results obtained mainly from the microscopic car following models are presented.
Journal ArticleDOI

Some traffic features at freeway bottlenecks

TL;DR: In this paper, the average discharge rate of vehicles in a queue can be 10% lower than the flow measured prior to the queue's formation and the discharge flows exhibited nearly stationary patterns that alternated between higher and lower rates.
Journal ArticleDOI

On the Modeling of Traffic and Crowds: A Survey of Models, Speculations, and Perspectives

TL;DR: A review and critical analysis of the mathematical literature concerning the modeling of vehicular traffic and crowd phenomena and a critical analysis focused on research perspectives that consider the development of a unified modeling strategy are presented.
Journal ArticleDOI

Optimizing urban rail timetable under time-dependent demand and oversaturated conditions

TL;DR: In this article, a genetic algorithm is developed to solve the multi-station problem through a special binary coding method that indicates a train departure or cancellation at every possible time point, and a local improvement algorithm is presented to find optimal timetables for individual station cases.