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Journal ArticleDOI

Experimental and empirical investigations of traffic flow instability

TLDR
In this paper, the authors have carried out a large scale experiment to study the car-following behavior in a 51-car platoon and found that there exists a critical speed between 30 and 40 km/h, above which the standard deviation of car velocity is almost saturated (flat) along the platoon.
Abstract
Traffic instability is an important but undesirable feature of traffic flow. This paper reports our experimental and empirical studies on traffic flow instability. We have carried out a large scale experiment to study the car-following behavior in a 51-car-platoon. The experiment has reproduced the phenomena and confirmed the findings in our previous 25-car-platoon experiment, i.e., standard deviation of vehicle speeds increases in a concave way along the platoon. Based on our experimental results, we argue that traffic speed rather than vehicle spacing (or density) might be a better indicator of traffic instability, because vehicles can have different spacing under the same speed. For these drivers, there exists a critical speed between 30 km/h and 40 km/h, above which the standard deviation of car velocity is almost saturated (flat) along the 51-car-platoon, indicating that the traffic flow is likely to be stable. In contrast, below this critical speed, traffic flow is unstable and can lead to the formation of traffic jams. Traffic data from the Nanjing Airport Highway support the experimental observation of existence of a critical speed. Based on these findings, we propose an alternative mechanism of traffic instability: the competition between stochastic factors and the so-called speed adaptation effect, which can better explain the concave growth of speed standard deviation in traffic flow.

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Citations
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Journal ArticleDOI

Trajectory data-based traffic flow studies: A revisit

TL;DR: The critical role of trajectory data (especially the next generation simulation (NGSIM) trajectory dataset) in the recent history of traffic flow studies is highlighted and the critical role at the microscopic/mesoscopic/macroscopic levels is highlighted.
Journal ArticleDOI

Analyzing the impact of automated vehicles on uncertainty and stability of the mixed traffic flow

TL;DR: The proposed stochastic model allows us to explicitly investigate the interaction between AVs and HVs considering the uncertainty of human driving behavior, and results show that AVs have significant impact on the uncertainty and stability of the mixed traffic flow system.
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Langevin method for a continuous stochastic car-following model and its stability conditions

TL;DR: Stochastic linear stability conditions are derived which, for the first time, theoretically capture the effect of the random parameter on traffic instabilities.
Journal ArticleDOI

Model-Based String Stability of Adaptive Cruise Control Systems Using Field Data

TL;DR: In this article, a set of car following experiments are conducted to collect data from a 2015 luxury electric vehicle equipped with a commercial adaptive cruise control (ACC) system, which is used to calibrate an optimal velocity relative velocity car following model for both the minimum and maximum following settings.
References
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Journal ArticleDOI

Congested traffic states in empirical observations and microscopic simulations

TL;DR: It is shown that the results of the microscopic model can be understood by formulating the theoretical phase diagram for bottlenecks in a more general way, and a local drop of the road capacity induced by parameter variations has essentially the same effect as an on-ramp.
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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.
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Dynamical model of traffic congestion and numerical simulation

TL;DR: In this model, the legal velocity function is introduced, which is a function of the headway of the preceding vehicle, and the evolution of traffic congestion is observed with the development of time.
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Statistical physics of vehicular traffic and some related systems

TL;DR: In this paper, a critical review of particle-hopping models of vehicular traffic is presented, focusing on the results obtained mainly from the so-called "particle hopping" models, particularly emphasizing those formulated in recent years using the language of cellular automata.
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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.
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