scholarly journals Impact of Road Bends on Traffic Flow in a Single-Lane Traffic System

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Zeng Junwei ◽  
Qian Yongsheng ◽  
Xu Dejie ◽  
Jia Zhilong ◽  
Huang Zhidan
Keyword(s):  
Traffic Flow ◽  
Peak Flow ◽  
Inhibitory Effect ◽  
Arc Length ◽  
Traffic Flows ◽  
Bend Radius ◽  
Fundamental Diagram ◽  
Traffic System ◽  
Inhibition Effect ◽  
Road Friction

Taking the characteristics of road bends as a research object, this work proposes the cellular model (CA) with road bends based on the NaSch model, with which the traffic flow is examined under different conditions, such as bend radius, bend arc length, and road friction coefficiency. The simulation results show that, with the increase of the bend radius, the peak flow will be continuously increased, and the fundamental diagram will become more similar to that of the classic NaSch model; the smaller the bend radius is, the easier it is for the occurrence of blockage; for different bend lengths, all the corresponding traffic flows show that the phenomenon of go-and-stop and the bends exert slight inhibitory effect on traffic flow; under the same bend radius, the inhibition effect of the bends on the traffic flow will be weakened with the increase of the friction coefficiency.

Effect of Multi-Slowdown Sections on Traffic Flow

2012 ◽  
Vol 253-255 ◽  
pp. 1619-1622
Author(s):  
Yan Hong Fan ◽  
Hua Kuang ◽  
Guo Xin Zhang ◽  
Ling Jiang Kong ◽  
Xing Li Li
Keyword(s):  
Energy Consumption ◽  
Traffic Flow ◽  
Maximum Flow ◽  
Underlying Mechanism ◽  
Speed Limit ◽  
Fundamental Diagram ◽  
Mean Velocity ◽  
Traffic System ◽  
Flow Phase ◽  
Multi Phase

Based on the NS model, an extended cellular automaton model is proposed to simulate complex characteristics and energy consumption of traffic flow with some slowdown sections on a highway by considering the number, speed limit and distribution of slowdown sections. The simulation results show that the present model can exhibit a multi-phase coexistence phenomenon, i.e., the freely moving phase, the maximum flow phase and the jamming phase coexist in traffic system. The fundamental diagram shows that the number of slowdown section has no influence on the mean velocity and flow. However, energy consumption increases with increase of the number of slowdown section at low density. In addition, it can be found that the speed limit and distribution of different slowdown sections have an important effect on traffic flow and energy consumption, and the underlying mechanism is also analyzed.

Emergence of 4-D System Fundamental Diagram in Urban Air Mobility Traffic Flow

2021 ◽  
pp. 036119812110200
Author(s):  
Christopher Cummings ◽  
Hani Mahmassani
Keyword(s):  
Traffic Flow ◽  
Flow Characteristics ◽  
Urban Air ◽  
Traffic Flows ◽  
Traffic Patterns ◽  
Fundamental Diagram ◽  
Exhaustible Resource ◽  
Urban Streets ◽  
Macroscopic Fundamental Diagram ◽  
Resolution Scheme

Urban air mobility (UAM) is an emerging mode that promises to provide relief to congested urban streets. UAM relies on airspace, however, which is an exhaustible resource considering minimum aircraft separation requirements. In light of these requirements and UAM vehicle attributes, a simulation is developed to explore UAM traffic flows and congestion development. A decentralized conflict resolution scheme is employed in the form of a non-linear program (NLP) to offer improved flexibility in detours relative to past aircraft simulations. An expansion of Edie’s definitions of density and flow rate are used in conjunction with average speed to explore the relationships between traffic flow characteristics. The results find that UAM traffic flows emulate those of other modes, by following the familiar traffic patterns of build-up and breakdown captured in the macroscopic fundamental diagram. These findings also suggest the presence of a capacity of airspace that should be carefully managed by operators to achieve optimal system performance. The relationships established in this study highlight issues that UAM operators and aviation planners may face and could be used to improve the vehicle traffic modeling of other UAM models.

scholarly journals Estimation of Hourly Traffic Flows from Floating Car Data for Vehicle Emission Estimation

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yun Jiang ◽  
Guohua Song ◽  
Zeyu Zhang ◽  
Zhiqiang Zhai ◽  
Lei Yu
Keyword(s):  
Traffic Flow ◽  
Traffic Flows ◽  
Fundamental Diagram ◽  
Flow Estimation ◽  
Floating Car Data ◽  
Estimation Uncertainty ◽  
Spatial And Temporal Distributions ◽  
Significant Difference ◽  
Traffic Flow Estimation ◽  
Hysteresis Phenomena

In order to model air quality in heavy pollution days, a dynamic emission monitoring system is implemented in the Beijing road network, which requires the input of hourly traffic flows. Floating car data (FCD) is increasingly employed for flow estimation based on the fundamental diagrams to supplement data provided by stationary detectors. However, existing studies often used a typical fundamental diagram without considering the hysteresis phenomena and the uncertainty of traffic flow estimation. This study aims to develop a multiperiod fundamental diagram for the traffic flow estimation from FCD considering the hysteresis phenomena. The result shows that the proposed multiperiod fundamental diagram can improve the accuracy of flow estimation. The uncertainty of traffic flow estimation at both 10 minutes and 1 hour is also quantified, and the result indicates that the variation of the estimation uncertainty at 1 hour is lower than that at 10 minutes, with an average 7% reduction of the range of 95% confidence interval (CI). But there is no significant difference in magnitudes of the estimation uncertainty at 1 hour compared with that at 10 minutes. Moreover, the uncertainty for congested flows is lower than that for free flows. In the case study, the proposed model is employed to develop the spatial and temporal distributions of flows and emissions for the metropolitan area in Beijing.

Field Theory for Some Traffic Phenomena and Fundamental Diagram

2021 ◽  
pp. 036119812110064
Author(s):  
Daiheng Ni
Keyword(s):  
Field Theory ◽  
Traffic Flow ◽  
Causal Effect ◽  
Microscopic Approach ◽  
Fundamental Diagram ◽  
Longitudinal Control ◽  
Effect Analysis ◽  
Vehicle Trajectories ◽  
Vehicle Motion ◽  
Cross Reference

A fundamental diagram consists of a scatter of traffic flow data sampled at a specific location and aggregated from vehicle trajectories. These trajectories, if presented equivalently, constitute a microscopic version of the (conventional) fundamental diagram. The cross-reference between vehicle trajectories and the microscopic fundamental diagram provides details of vehicle motion dynamics which allow causal-effect analysis on some traffic phenomena and further reveal the microscopic basis of the conventional fundamental diagram. This observation inspires theoretical modeling by a microscopic approach to address traffic phenomena and the conventional fundamental diagram. Derived from the field theory of traffic flow, the longitudinal control model is capable of serving the purpose without the modifications or exceptions used by other approaches.

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

Energies ◽  
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.

TripRes

2021 ◽  
Vol 17 (2) ◽  
pp. 1-21
Author(s):  
Xiaolong Xu ◽  
Zijie Fang ◽  
Lianyong Qi ◽  
Xuyun Zhang ◽  
Qiang He ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Discrete Distribution ◽  
Resource Provisioning ◽  
Path Selection ◽  
Urban Traffic ◽  
Traffic Flows ◽  
Multimedia Services ◽  
Traffic Flow Prediction ◽  
The City ◽  
Multimedia Surveillance

The Internet of Vehicles (IoV) connects vehicles, roadside units (RSUs) and other intelligent objects, enabling data sharing among them, thereby improving the efficiency of urban traffic and safety. Currently, collections of multimedia content, generated by multimedia surveillance equipment, vehicles, and so on, are transmitted to edge servers for implementation, because edge computing is a formidable paradigm for accommodating multimedia services with low-latency resource provisioning. However, the uneven or discrete distribution of the traffic flow covered by edge servers negatively affects the service performance (e.g., overload and underload) of edge servers in multimedia IoV systems. Therefore, how to accurately schedule and dynamically reserve proper numbers of resources for multimedia services in edge servers is still challenging. To address this challenge, a traffic flow prediction driven resource reservation method, called TripRes, is developed in this article. Specifically, the city map is divided into different regions, and the edge servers in a region are treated as a “big edge server” to simplify the complex distribution of edge servers. Then, future traffic flows are predicted using the deep spatiotemporal residual network (ST-ResNet), and future traffic flows are used to estimate the amount of multimedia services each region needs to offload to the edge servers. With the number of services to be offloaded in each region, their offloading destinations are determined through latency-sensitive transmission path selection. Finally, the performance of TripRes is evaluated using real-world big data with over 100M multimedia surveillance records from RSUs in Nanjing China.

scholarly journals A Cellular Automaton Traffic Flow Model with Advanced Decelerations

2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
Yingdong Liu
Keyword(s):  
Cellular Automaton ◽  
Traffic Flow ◽  
Flow Model ◽  
Stable State ◽  
Practical Significance ◽  
Fundamental Diagram ◽  
Traffic Flow Model ◽  
Short Time ◽  
Vehicle Deceleration ◽  
Real Traffic

A one-dimensional cellular automaton traffic flow model, which considers the deceleration in advance, is addressed in this paper. The model reflects the situation in the real traffic that drivers usually adjust the current velocity by forecasting its velocities in a short time of future, in order to avoid the sharp deceleration. The fundamental diagram obtained by simulation shows the ability of this model to capture the essential features of traffic flow, for example, synchronized flow, meta-stable state, and phase separation at the high density. Contrasting with the simulation results of the VE model, this model shows a higher maximum flux closer to the measured data, more stability, more efficient dissolving blockage, lower vehicle deceleration, and more reasonable distribution of vehicles. The results indicate that advanced deceleration has an important impact on traffic flow, and this model has some practical significance as the result matching to the actual situation.

scholarly journals Fungicidal effect of silver nanoparticles on toxigenic fungi in cocoa

2016 ◽  
Vol 51 (12) ◽  
pp. 1929-1936 ◽  
Author(s):  
Raquel Villamizar-Gallardo ◽  
Johann Faccelo Osma Cruz ◽  
Oscar Orlando Ortíz-Rodriguez
Keyword(s):  
Silver Nanoparticles ◽  
Fusarium Solani ◽  
Theobroma Cacao ◽  
Mycelial Growth ◽  
Culture Media ◽  
Fungal Growth ◽  
Inhibitory Effect ◽  
Plant Tissues ◽  
Inhibition Effect ◽  
Toxigenic Fungi

Abstract: The objective of this work was to evaluate the microbicidal effect of silver nanoparticles (AgNPs) on potentially toxigenic fungi affecting cocoa (Theobroma cacao) crops. These fungi, isolated from diseased cocoa pods, were characterized phenotypically and genotypically. The microbicidal effect was assessed by measuring radial mycelial growth, in synthetic culture media, and at different AgNP concentrations in plant tissues. The inhibition effect was monitored in Petri dishes, and changes in fungal structures were observed through scanning electron microscopy. Two potentially toxigenic fungi were highly prevalent: Aspergillus flavus and Fusarium solani. The inhibition assays, performed in liquid and solid synthetic culture media, showed that AgNPs did not significantly affect the growth of these fungi, even at the highest concentration (100 ppm). By contrast, they showed a positive inhibitory effect in plant tissues, especially in the cortex, when infected with A. flavus, in which an 80 ppm dose completely inhibited fungal growth. However, once fungi have managed to penetrate inside the pods, their growth is unavoidable, and AgNP effect is reduced. On F. solani, the studied nanomaterial only induced some texture and pigmentation changes. The microbicidal effect of chemically synthesized silver nanoparticles is greater in plant tissues than in culture media.

scholarly journals Traffic flow features as metrics (TFFM): detection of application layer level DDOS attack scope of IOT traffic flows

2018 ◽  
Vol 7 (2.7) ◽  
pp. 203 ◽  
Author(s):  
Kalathiripi Rambabu ◽  
N Venkatram
Keyword(s):  
Traffic Flow ◽  
Traffic Flows ◽  
Application Layer ◽  
Continuous Growth ◽  
Loosely Coupled ◽  
Ddos Attack ◽  
Proposed Model ◽  
Flow Features ◽  
Target Network ◽  
Iot Devices

The phenomenal and continuous growth of diversified IOT (Internet of Things) dependent networks has open for security and connectivity challenges. This is due to the nature of IOT devices, loosely coupled behavior of internetworking, and heterogenic structure of the networks.  These factors are highly vulnerable to traffic flow based DDOS (distributed-denial of services) attacks. The botnets such as “mirae” noticed in recent past exploits the IoT devises and tune them to flood the traffic flow such that the target network exhaust to response to benevolent requests. Hence the contribution of this manuscript proposed a novel learning-based model that learns from the traffic flow features defined to distinguish the DDOS attack prone traffic flows and benevolent traffic flows. The performance analysis was done empirically by using the synthesized traffic flows that are high in volume and source of attacks. The values obtained for statistical metrics are evincing the significance and robustness of the proposed model

Sign in / Sign up

Export Citation Format

Share Document