Journal ArticleDOI
Nonlinear Follow-the-Leader Models of Traffic Flow
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A variety of nonlinear follow-the-leader models of traffic flow are discussed in this article in the light of available observational and experimental data, with emphasis placed on steady-state flow equations.Abstract:
A variety of nonlinear follow-the-leader models of traffic flow are discussed in the light of available observational and experimental data. Emphasis is placed on steady-state flow equations. Some trends regarding the advantages of certain follow-the-leader functionals over others are established. However, it is found from extensive correlation studies that more data are needed before one can establish the unequivocal superiority of one particular model. A discussion is given of some ideas concerning the possible reasons for the existence of a bimodal flow versus concentration curve especially for multilane highways.read more
Citations
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Traffic and related self-driven many-particle systems
Dirk Helbing,Dirk Helbing +1 more
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
A behavioural car-following model for computer simulation
TL;DR: A new model is constructed for the response of the following vehicle based on the assumption that each driver sets limits to his desired braking and acceleration rates and it is shown that when realistic values are assigned to the parameters in a simulation, the model reproduces the characteristics of real traffic flow.
Journal ArticleDOI
Car-following: a historical review
Mark Brackstone,Mike McDonald +1 more
TL;DR: In this article, the authors assess the range of options available in the choice of car-following model, and assess just how far work has proceeded in our understanding of what, at times, would appear to be a simple process.
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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 simplified car-following theory: a lower order model
TL;DR: A very simple “car-following” rule is proposed wherein, if an nth vehicle is following an (n−1)th vehicle on a homogeneous highway, the time-space trajectory of the nth vehicles is essentially the same as the (n −1) fourth vehicle except for a translation in space and in time.
References
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Journal ArticleDOI
Traffic Dynamics: Studies in Car Following
TL;DR: In this paper, the acceleration at time t of a car attempting to follow a leader is proportional to the difference in velocity of the two cars at a time t-Δ, Δ being about 1.5 sec and the proportionality constant being about 0.37 sec-1.
A study of traffic capacity
TL;DR: The Recordograph traffic analysis was found to be an accurate method of determining the traffic capacity of highways and valuable aid in determining traffic conditions.
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An Operational Analysis of Traffic Dynamics
TL;DR: In this paper, the authors studied the dynamics of a line of traffic composed of n vehicles, where the movements of the vehicles are controlled by an idealized ''law of separation'' which specifies that each vehicle must maintain a certain prescribed following distance from the preceding vehicle.
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Nonlinear Effects in the Dynamics of Car Following
TL;DR: In this paper, it was shown that a small amplitude disturbance propagates through a series of cars in the manner described by linear theories, except that the dependence of the wave velocity on the car velocity causes an accleration wave to spread as it propagates and a deceleration wave forming a stable shock.
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An Analysis of Traffic Flow
TL;DR: A model for traffic flow is developed by treating the traffic stream as a continuous fluid and fluid dynamic principles are used to derive relations between speed, density, and flow.