Research on the Influence of Freeway Truck Mixing Rate on Traffic State

2021 ◽  
pp. 349-361
Author(s):  
Fengchun Han ◽  
Na Li ◽  
Dan Zhao ◽  
Yumeng Zhang
Keyword(s):  
Mixing Rate ◽  
Traffic State

Quantification of mixing and mixing rate from experimental observations

AIAA Journal ◽  
1998 ◽  
Vol 36 ◽  
pp. 121-127
Author(s):  
R. Everson ◽  
D. Manin ◽  
L. Sirovich ◽  
M. Winter
Keyword(s):  
Mixing Rate

The Analysis of Urban Road Traffic State Based on Kinds Floating Car Data

2014 ◽  
Vol 694 ◽  
pp. 80-84
Author(s):  
Xiao Tong Yin ◽  
Chao Qun Ma ◽  
Liang Peng Qu
Keyword(s):  
Road Traffic ◽  
Velocity Estimation ◽  
Least Square ◽  
Single Type ◽  
Estimation Model ◽  
Average Speed ◽  
Urban Road ◽  
Traffic State ◽  
Floating Car Data ◽  
Different Types

The analysis of the unban road traffic state based on kinds of floating car data, is based on the model and algorithm of floating car data preprocessing and map matching, etc. Firstly, according to the characteristics of the different types of urban road, the urban road section division has been carried on the elaboration and optimization. And this paper introduces the method of calculating the section average speed with single floating car data, also applies the dynamic consolidation of sections to estimate the section average velocity.Then the minimum sample size of floating car data is studied, and section average velocity estimation model based on single type of floating car data in the different case of floating car data sample sizes has been built. Finally, the section average speed of floating car in different types is fitted to the section average car speed by the least square method, using section average speed as the judgment standard, the grade division standard of urban road traffic state is established to obtain the information of road traffic state.

Using Traffic Disturbance Metrics to Estimate and Predict Freeway Traffic Breakdown and Safety Events

2021 ◽  
pp. 036119812110124
Author(s):  
Leila Azizi ◽  
Mohammed Hadi
Keyword(s):  
Traffic Safety ◽  
Management Strategies ◽  
Connected Vehicles ◽  
Freeway Traffic ◽  
Transportation Management ◽  
Time To Collision ◽  
Decision Tools ◽  
Traffic State ◽  
Traffic Performance ◽  
Traffic Disturbance

The introduction of connected vehicles, connected and automated vehicles, and advanced infrastructure sensors will allow the collection of microscopic metrics that can be used for better estimation and prediction of traffic performance. This study examines the use of disturbance metrics in combination with the macroscopic metrics usually used for the estimation of traffic safety and mobility. The disturbance metrics used are the number of oscillations and a measure of disturbance durations in the time exposed time to collision. The study investigates using the disturbance metrics in data clustering for better off-line categorization of traffic states. In addition, the study uses machine-learning based classifiers for the recognition and prediction of the traffic state and safety in real-time operations. The study also demonstrates that the disturbance metrics investigated are significantly related to crashes. Thus, this study recommends the use of these metrics as part of decision tools that support the activation of transportation management strategies to reduce the probability of traffic breakdown, ease traffic disturbances, and reduce the probability of crashes.

scholarly journals Deep Learning-Based Congestion Detection at Urban Intersections

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2052
Author(s):  
Xinghai Yang ◽  
Fengjiao Wang ◽  
Zhiquan Bai ◽  
Feifei Xun ◽  
Yulin Zhang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Optical Flow ◽  
Traffic Congestion ◽  
Detection Algorithm ◽  
Input Image ◽  
Vehicle Speed ◽  
Position Information ◽  
Traffic State ◽  
State Discrimination ◽  
Discrimination Method

In this paper, a deep learning-based traffic state discrimination method is proposed to detect traffic congestion at urban intersections. The detection algorithm includes two parts, global speed detection and a traffic state discrimination algorithm. Firstly, the region of interest (ROI) is selected as the road intersection from the input image of the You Only Look Once (YOLO) v3 object detection algorithm for vehicle target detection. The Lucas-Kanade (LK) optical flow method is employed to calculate the vehicle speed. Then, the corresponding intersection state can be obtained based on the vehicle speed and the discrimination algorithm. The detection of the vehicle takes the position information obtained by YOLOv3 as the input of the LK optical flow algorithm and forms an optical flow vector to complete the vehicle speed detection. Experimental results show that the detection algorithm can detect the vehicle speed and traffic state discrimination method can judge the traffic state accurately, which has a strong anti-interference ability and meets the practical application requirements.

scholarly journals Effect of Enhanced ADAS Camera Capability on Traffic State Estimation

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 1996
Author(s):  
Hoe Kyoung Kim ◽  
Younshik Chung ◽  
Minjeong Kim
Keyword(s):  
State Estimation ◽  
Traffic Engineering ◽  
Flow Density ◽  
Microscopic Simulation ◽  
Traffic Demand ◽  
Traffic System ◽  
Traffic Conditions ◽  
Traffic State ◽  
Vehicle Identification ◽  
Traffic State Estimation

Traffic flow data, such as flow, density and speed, are crucial for transportation planning and traffic system operation. Recently, a novel traffic state estimating method was proposed using the distance to a leading vehicle measured by an advanced driver assistance system (ADAS) camera. This study examined the effect of an ADAS camera with enhanced capabilities on traffic state estimation using image-based vehicle identification technology. Considering the realistic distance error of the ADAS camera from the field experiment, a microscopic simulation model, VISSIM, was employed with multiple underlying parameters such as the number of lanes, traffic demand, the penetration rate of ADAS vehicles and the spatiotemporal range of the estimation area. Although the enhanced functions of the ADAS camera did not affect the accuracy of the traffic state estimates significantly, the ADAS camera can be used for traffic state estimation. Furthermore, the vehicle identification distance of the ADAS camera and traffic conditions with more lanes did not always ensure better accuracy of the estimates. Instead, it is recommended that transportation planners and traffic engineering practitioners carefully select the relevant parameters and their range to ensure a certain level of accuracy for traffic state estimates that suit their purposes.

CFD analysis and RSM optimization of obstacle layout in Tesla micromixer

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Xiaowen Wang ◽  
Lihong Yang ◽  
Fujia Sun
Keyword(s):  
Chemical Reaction ◽  
Chemical Engineering ◽  
Design Method ◽  
Mixing Rate ◽  
Special Flow ◽  
Surface Method ◽  
Rsm Optimization ◽  
Effective Technology ◽  
Optimal Design Method ◽  
Lateral Offset

Abstract As a kind of fast and efficient mixing equipment, micromixer has been applied to chemical reaction detection. Its application can not only save experimental samples but also reduce the experimental time. In micromixers, Tesla structure is widely used due to its simple structure and special flow mechanism. In this paper, CFD and response surface method are used to analyze and verify the flow field of the configuration of adding diamond obstacles in the Tesla mixer. The results show that the order of layout parameter weight from large to small is obstacle size > vertical offset > horizontal offset. And the Desirability was 0.806, the optimal diamond obstacle size is 46.35 μm and the optimal lateral offset is 18.78 μm. In addition, a constant value OF 20 μm is predicted as the optimal vertical offset of the micromixer. Compared with the Tesla-type micromixer without obstacles, the diamond-shaped barrier Tesla-type micromixer designed in this paper has higher mixing rate and lower pressure drop under the same conditions, which can be applied to chemical reactors, and can also help to improve the accuracy of chemical reaction. It can be demonstrated that the presented optimal design method of obstacles layout in Tesla mixer is a simple and effective technology to improve the liquid mixing in microfluidic devices, and it has a broad application prospect in chemical engineering.

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