A behavioral car-following model that captures traffic oscillations

Chen, Danjue; Laval, Jorge A.; Zheng, Zuduo; Ahn, Soyoung

doi:10.1016/j.trb.2012.01.009

Cited by 193 publications

(113 citation statements)

References 22 publications

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“…At a microscopic level, Chen et al proposed a behavioral car-following model based on empirical data that captures phantom jams [27]. Therein, the authors showed statistical correlation in drivers' behavior before and during traffic oscillations.…”

Section: A Related Work On Car-following Modelsmentioning

confidence: 99%

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The modified optimal velocity model: stability analyses and design guidelines

Kamath

Jagannathan

Raina

2017

IFAC Journal of Systems and Control

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Reaction delays are important in determining the qualitative dynamical properties of a platoon of vehicles traveling on a straight road. In this paper, we investigate the impact of delayed feedback on the dynamics of the Modified Optimal Velocity Model (MOVM). Specifically, we analyze the MOVM in three regimes -no delay, small delay and arbitrary delay. In the absence of reaction delays, we show that the MOVM is locally stable. For small delays, we then derive a sufficient condition for the MOVM to be locally stable. Next, for an arbitrary delay, we derive the necessary and sufficient condition for the local stability of the MOVM. We show that the traffic flow transits from the locally stable to the locally unstable regime via a Hopf bifurcation. We also derive the necessary and sufficient condition for non-oscillatory convergence and characterize the rate of convergence of the MOVM. These conditions help ensure smooth traffic flow, good ride quality and quick equilibration to the uniform flow. Further, since a Hopf bifurcation results in the emergence of limit cycles, we provide an analytical framework to characterize the type of the Hopf bifurcation and the asymptotic orbital stability of the resulting non-linear oscillations. Finally, we corroborate our analyses using stability charts, bifurcation diagrams, numerical computations and simulations conducted using MATLAB.

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Section: A Related Work On Car-following Modelsmentioning

confidence: 99%

“…Thus, for ω = 0 to be the unique solution of (26), we require a 2 = 2σ 2 e 2στ in addition to the condition mentioned in (27). That is, (23) has real eigenvalues if and only if…”

Section: Non-oscillatory Convergencementioning

confidence: 99%

The modified optimal velocity model: stability analyses and design guidelines

Kamath

Jagannathan

Raina

2017

IFAC Journal of Systems and Control

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“…In that regards, other oscillation generating models could have been linearized such as [44]. Behavioral models such as in [22,45], and more recently [46,47], depict the effects of car-following and lanechanging on freeway dynamics, effects often cited as the cause of oscillations [48][49][50]. However, second-order macroscopic models are most suited for our method.…”

Section: Models Appropriate For Controlmentioning

confidence: 99%

Prediction of traffic convective instability with spectral analysis of the Aw–Rascle–Zhang model

et al. 2015

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“…Merging behavior is a complex task, because, typically, the driver has to focus on three or more vehicles in their current and target lanes in a limited timeframe [5]. This contrasts with the driver's task in the carfollowing process where she/he generally only needs to focus on the immediately preceding vehicle in their current lane [6]. Therefore, the study of merging behaviors is a challenging one.…”

Section: Introductionmentioning

confidence: 99%

Modeling and Predicting Stochastic Merging Behaviors at Freeway On-Ramp Bottlenecks

Sun

Zuo

Jiang

et al. 2018

Journal of Advanced Transportation

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Merging behavior is inevitable at on-ramp bottlenecks and is a significant factor in triggering traffic breakdown. In modeling merging behaviors, the gap acceptance theory is generally used. Gap acceptance theory holds that when a gap is larger than the critical gap, the vehicle will merge into the mainline. In this study, however, analyses not only focus on the accepted gaps, but also take the rejected gaps into account, and the impact on merging behavior with multi-rejected (more than once rejecting behavior) gaps was investigated; it shows that the multi-rejected gaps have a great influence on the estimation of critical gap and merging prediction. Two empirical trajectory data sets were collected and analyzed: one at Yan'an Expressway in Shanghai, China, and the other at Highway 101 in Los Angeles, USA. The study made three main contributions. First, it gives the quantitative measurement of the rejected gap which is also a detailed description of non-merging event and investigated the characteristics of the multi-rejected gaps; second, taking the multi-rejected gaps into consideration, it further expanded the concept of the "critical gap" which can be a statistic one and the distribution function of merging probability with respect to such gaps was analyzed by means of survival analysis. This way could make the full use of multi-rejected gaps and accepted gaps and reduce the sample bias, thus estimating the critical gap accurately; finally, considering multi-rejected gaps, it created logistic regression models to predict merging behavior. These models were tested using field data, and satisfactory performances were obtained.

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A behavioral car-following model that captures traffic oscillations

Cited by 193 publications

References 22 publications

The modified optimal velocity model: stability analyses and design guidelines

The modified optimal velocity model: stability analyses and design guidelines

Prediction of traffic convective instability with spectral analysis of the Aw–Rascle–Zhang model

Modeling and Predicting Stochastic Merging Behaviors at Freeway On-Ramp Bottlenecks

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