How Reaction Time, Update Time, and Adaptation Time Influence the Stability of Traffic Flow

A novel Tyr-selective protein bioconjugation using the water-soluble persistent iminoxyl radical is described. The conjugation proceeded with high Tyr-selectivity and short reaction time under biocompatible conditions (room temperature in buffered media under air). The stability of the conjugates was tunable depending on the steric hindrance of iminoxyl. The presence of sodium ascorbate and/or light irradiation promoted traceless deconjugation, restoring the native Tyr structure. The method is applied to the synthesis of a protein-dye conjugate and further derivatization to azobenzene-modified peptides.

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Exploring the Distribution of Traffic Flow for Shared Human and Autonomous Vehicle Roads

Energies ◽

10.3390/en14123425 ◽

2021 ◽

Vol 14 (12) ◽

pp. 3425

Author(s):

Huanping Li ◽

Jian Wang ◽

Guopeng Bai ◽

Xiaowei Hu

Keyword(s):

Traffic Flow ◽

Autonomous Vehicles ◽

Flow Model ◽

Road Traffic ◽

Autonomous Vehicle ◽

Transformation Model ◽

Hydrodynamic Theory ◽

Traffic Flow Model ◽

Traffic System ◽

The Stability

In order to explore the changes that autonomous vehicles would bring to the current traffic system, we analyze the car-following behavior of different traffic scenarios based on an anti-collision theory and establish a traffic flow model with an arbitrary proportion (p) of autonomous vehicles. Using calculus and difference methods, a speed transformation model is established which could make the autonomous/human-driven vehicles maintain synchronized speed changes. Based on multi-hydrodynamic theory, a mixed traffic flow model capable of numerical calculation is established to predict the changes in traffic flow under different proportions of autonomous vehicles, then obtain the redistribution characteristics of traffic flow. Results show that the reaction time of autonomous vehicles has a decisive influence on traffic capacity; the q-k curve for mixed human/autonomous traffic remains in the region between the q-k curves for 100% human and 100% autonomous traffic; the participation of autonomous vehicles won’t bring essential changes to road traffic parameters; the speed-following transformation model minimizes the safety distance and provides a reference for the bottom program design of autonomous vehicles. In general, the research could not only optimize the stability of transportation system operation but also save road resources.

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Model and Stability of the Traffic Flow Consisting of Heterogeneous Drivers

Journal of Computational and Nonlinear Dynamics ◽

10.1115/1.4025896 ◽

2015 ◽

Vol 10 (3) ◽

Cited By ~ 4

Author(s):

Da Yang ◽

Liling Zhu ◽

Yun Pu

Keyword(s):

Traffic Flow ◽

Heterogeneous Traffic ◽

Model Parameters ◽

Optimal Velocity ◽

Stability Functions ◽

Car Following Model ◽

Traffic Wave ◽

The Stability ◽

Different Characteristics ◽

Stationary Velocity

Although traffic flow has attracted a great amount of attention in past decades, few of the studies focused on heterogeneous traffic flow consisting of different types of drivers or vehicles. This paper attempts to investigate the model and stability analysis of the heterogeneous traffic flow, including drivers with different characteristics. The two critical characteristics of drivers, sensitivity and cautiousness, are taken into account, which produce four types of drivers: the sensitive and cautious driver (S-C), the sensitive and incautious driver (S-IC), the insensitive and cautious driver (IS-C), and the insensitive and incautious driver (IS-IC). The homogeneous optimal velocity car-following model is developed into a heterogeneous form to describe the heterogeneous traffic flow, including the four types of drivers. The stability criterion of the heterogeneous traffic flow is derived, which shows that the proportions of the four types of drivers and their stability functions only relating to model parameters are two critical factors to affect the stability. Numerical simulations are also conducted to verify the derived stability condition and further explore the influences of the driver characteristics on the heterogeneous traffic flow. The simulations reveal that the IS-IC drivers are always the most unstable drivers, the S-C drivers are always the most stable drivers, and the stability effects of the IS-C and the S-IC drivers depend on the stationary velocity. The simulations also indicate that a wider extent of the driver heterogeneity can attenuate the traffic wave.

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The effects of drivers’ aggressive characteristics on traffic stability from a new car-following model

Modern Physics Letters B ◽

10.1142/s0217984916502432 ◽

2016 ◽

Vol 30 (18) ◽

pp. 1650243 ◽

Cited By ~ 12

Author(s):

Guanghan Peng ◽

Li Qing

Keyword(s):

Stability Analysis ◽

Nonlinear Analysis ◽

Traffic Flow ◽

Linear Stability Analysis ◽

Stable Condition ◽

Mkdv Equation ◽

Stable Region ◽

Car Following ◽

Car Following Model ◽

The Stability

In this paper, a new car-following model is proposed by considering the drivers’ aggressive characteristics. The stable condition and the modified Korteweg-de Vries (mKdV) equation are obtained by the linear stability analysis and nonlinear analysis, which show that the drivers’ aggressive characteristics can improve the stability of traffic flow. Furthermore, the numerical results show that the drivers’ aggressive characteristics increase the stable region of traffic flow and can reproduce the evolution and propagation of small perturbation.

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An extended optimal velocity difference model in a cooperative driving system

International Journal of Modern Physics C ◽

10.1142/s0129183115500540 ◽

2015 ◽

Vol 26 (05) ◽

pp. 1550054

Author(s):

Jinliang Cao ◽

Zhongke Shi ◽

Jie Zhou

Keyword(s):

Traffic Flow ◽

Linear Stability Theory ◽

Difference Model ◽

Optimal Velocity ◽

Driving System ◽

Cooperative Driving ◽

Proposed Model ◽

De Vries ◽

The Stability ◽

Theoretical Results

An extended optimal velocity (OV) difference model is proposed in a cooperative driving system by considering multiple OV differences. The stability condition of the proposed model is obtained by applying the linear stability theory. The results show that the increase in number of cars that precede and their OV differences lead to the more stable traffic flow. The Burgers, Korteweg–de Vries (KdV) and modified Korteweg–de Vries (mKdV) equations are derived to describe the density waves in the stable, metastable and unstable regions, respectively. To verify these theoretical results, the numerical simulation is carried out. The theoretical and numerical results show that the stabilization of traffic flow is enhanced by considering multiple OV differences. The traffic jams can be suppressed by taking more information of cars ahead.

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Heterogeneous traffic flow model under connected vehicles environment considering cyberattacks

Modern Physics Letters B ◽

10.1142/s0217984921505370 ◽

2021 ◽

Author(s):

Lizhen Lin ◽

Hongxia Ge ◽

Rongjun Cheng

Keyword(s):

Traffic Flow ◽

Road Traffic ◽

Heterogeneous Traffic ◽

Connected Vehicles ◽

Vehicle To Vehicle ◽

Car Following Model ◽

Time Extension ◽

Potential Impact ◽

The Stability ◽

Traffic Behavior

Under the Vehicle-to-Vehicle (V2V) environment, connected vehicles (CVs) can share the traveling information with each other to keep the traffic flow stable. However, the open network cooperation environment makes CVs vulnerable to cyberattacks, which leads to changes in driving behavior. The existing theories divide cyberattacks into three types: bogus information, replay/delay and collusion cyberattacks. In addition, the mixed flow consisting of truck and car is a common form of road traffic. In order to clarify the potential impact of cyberattacks on mixed traffic flow, this paper proposes an extended car-following model considering cyberattacks under CVs environment. Subsequently, the stability of the model is analyzed theoretically, and the stability condition of the model is obtained. The numerical simulation is carried out and the result shows that the cyberattacks lead to different degrees of traffic behavior hazards such as queue time extension, congestion and even rear end collision. Among them, cooperative attack is the most serious.

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A two-lane lattice model considering taillight effect and man–machine hybrid driving

Modern Physics Letters B ◽

10.1142/s0217984920503650 ◽

2020 ◽

Vol 34 (32) ◽

pp. 2050365

Author(s):

Siyuan Chen ◽

Changxi Ma ◽

Jinchou Gong

Keyword(s):

Traffic Flow ◽

Lattice Model ◽

Critical Density ◽

Mkdv Equation ◽

Flow Stability ◽

Stability Conditions ◽

Neutral Stability ◽

Nonlinear Stability Analysis ◽

Traffic Flow Stability ◽

The Stability

At present, drivers can rely on road communication technology to obtain the current traffic status information, and the development of intelligent transportation makes self-driving possible. In this paper, considering the mixed traffic flow with self-driving vehicles and the taillight effect, a new macro-two-lane lattice model is established. Combined with the concept of critical density, the judgment conditions for vehicles to take braking measures are given. Based on the linear analysis, the stability conditions of the new model are obtained, and the mKdV equation describing the evolution mechanism of density waves is derived through the nonlinear stability analysis. Finally, with the help of numerical simulation, the phase diagram and kink–anti-kink waveform of neutral stability conditions are obtained, and the effects of different parameters of the model on traffic flow stability are analyzed. The results show that the braking probability, the proportion of self-driving vehicles and the critical density have significant effects on the traffic flow stability. Considering taillight effect and increasing the mixing ratio of self-driving vehicles can effectively enhance the stability of traffic flow, but a larger critical density will destroy the stability of traffic flow.

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Activation of Soluble Polysaccharides with 1-Cyano-4-Dimethylaminopyridine Tetrafluoroborate (CDAP) for Use in Protein–Polysaccharide Conjugate Vaccines and Immunological Reagents. III Optimization of CDAP Activation

Vaccines ◽

10.3390/vaccines8040777 ◽

2020 ◽

Vol 8 (4) ◽

pp. 777

Author(s):

Andrew Lees ◽

Jackson F. Barr ◽

Samson Gebretnsae

Keyword(s):

Reaction Time ◽

Low Temperature ◽

Scale Up ◽

Optimal Time ◽

Conjugate Vaccines ◽

Maximal Activation ◽

Optimum Reaction ◽

Rapid Reaction ◽

The Stability ◽

High Level

CDAP (1-cyano-4-dimethylaminopyridine tetrafluoroborate) is employed in the synthesis of conjugate vaccines as a cyanylating reagent. In the published method, which used pH 9 activation at 20 °C (Vaccine, 14:190, 1996), the rapid reaction made the process difficult to control. Here, we describe optimizing CDAP activation using dextran as a model polysaccharide. CDAP stability and reactivity were determined as a function of time, pH and temperature. While the rate of dextran activation was slower at lower pH and temperature, it was balanced by the increased stability of CDAP, which left more reagent available for reaction. Whereas maximal activation took less than 2.5 min at pH 9 and 20 °C, it took 10–15 min at 0 °C. At pH 7 and 0 °C, the optimal time increased to >3 h to achieve a high level of activation. Many buffers interfered with CDAP activation, but DMAP could be used to preadjust the pH of polysaccharide solutions so that the pH only needed to be maintained. We found that the stability of the activated dextran was relatively independent of pH over the range of pH 1–9, with the level of activation decreased by 40–60% over 2 h. The use of low temperature and a less basic pH, with an optimum reaction time, requires less CDAP, improving activation levels while making the process more reliable and easier to scale up.

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An Extended Car-Following Model in a Multi-Interaction Driving System

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.178-181.2717 ◽

2012 ◽

Vol 178-181 ◽

pp. 2717-2720

Author(s):

Man Xian Tuo

Keyword(s):

Numerical Simulation ◽

Traffic Flow ◽

Flow Model ◽

Extended Model ◽

Traffic Flow Model ◽

Driving System ◽

Car Following ◽

Traffic Jams ◽

Car Following Model ◽

The Stability

An extended traffic flow model is proposed by introducing the multiple information of preceding cars. The linear stability condition of the extended model is obtained, which shows that the stability of traffic flow is improved by considering the interaction of preceding cars to the following car. Numerical simulation shows that the traffic jams are suppressed efficiently by taking into account the multiple information of the preceding cars.

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