scholarly journals Correlation degree analysis of arterial adjacent intersections for coordinated control subunit partition

2018 ◽  
Vol 10 (1) ◽  
pp. 168781401774874 ◽  
Author(s):  
Yawen Hu ◽  
Yunpeng Wang ◽  
Junfeng Zhang ◽  
Haiyang Yu
Keyword(s):  
High Resolution ◽  
Spatial Clustering ◽  
Control Unit ◽  
Traffic Data ◽  
Traffic State ◽  
Arterial Road ◽  
Correlation Degree ◽  
New Strategy ◽  
Partition Method ◽  
Status Data

To analyze the correlation between adjacent intersections and implement coordinated signal control on arterial roads is a burning issue. The vehicle detector is indispensable by which the traffic state data are collected directly to get a reasonable control strategy. The traditional methods have poor control performance because of lacking enough accuracy. In this article, the new layout method of vehicle detector is proposed to collect and store high-resolution traffic data continuously, which can identify a critical turning point of the change in traffic state. Thus, a correlation degree model to quantitative relevance between adjacent intersections on arterial road based on traffic status data is established. This model could make more exact measurement in order to achieve the control subunit partition of arterial roads, selecting density-based spatial clustering of applications with noise algorithm to cluster the deriving correlation indexes. The partition method is evaluated by an arterial road including 12 intersections, and this road is divided into five subunits. The simulation result validates that the partition method based on correlation indexes can significantly improve the operation efficiency of arterial roads and reduce the traffic delay. This research may provide a new strategy on the partition of control unit for arterial road more accurately based on high-resolution traffic data.

scholarly journals Development of Macroscopic Cell-Based Logistic Lane Change Prediction Model

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Christina Ng ◽  
Susilawati Susilawati ◽  
Md Abdus Samad Kamal ◽  
Irene Mei Leng Chew
Keyword(s):  
Prediction Model ◽  
Transmission Model ◽  
Lane Change ◽  
Traffic Data ◽  
Cell Transmission Model ◽  
Traffic State ◽  
Proposed Model ◽  
Significant Difference ◽  
The Mean ◽  
Change Prediction

This paper aims at developing a macroscopic cell-based lane change prediction model in a complex urban environment and integrating it into cell transmission model (CTM) to improve the accuracy of macroscopic traffic state estimation. To achieve these objectives, first, based on the observed traffic data, the binary logistic lane change model is developed to formulate the lane change occurrence. Second, the binary logistic lane change is integrated into CTM by refining CTM formulations on how the vehicles in the cell are moving from one cell to another in a longitudinal manner and how cell occupancy is updated after lane change occurrences. The performance of the proposed model is evaluated by comparing the simulated cell occupancy of the proposed model with cell occupancy of US-101 next generation simulation (NGSIM) data. The results indicated no significant difference between the mean of the cell occupancies of the proposed model and the mean of cell occupancies of actual data with a root-mean-square-error (RMSE) of 0.04. Similar results are found when the proposed model was further tested with I80 highway data. It is suggested that the mean of cell occupancies of I80 highway data was not different from the mean of cell occupancies of the proposed model with 0.074 RMSE (0.3 on average).

Vehicle Detection and Tracking in Complex Traffic Circumstances with Roadside LiDAR

2019 ◽  
Vol 2673 (9) ◽  
pp. 62-71 ◽  
Author(s):  
Zhenyao Zhang ◽  
Jianying Zheng ◽  
Hao Xu ◽  
Xiang Wang
Keyword(s):  
High Resolution ◽  
Traffic Safety ◽  
Traffic Accidents ◽  
Vehicle Detection ◽  
Traffic Data ◽  
The Road ◽  
Detection And Tracking ◽  
Area Of Interest ◽  
Vehicle Detection And Tracking ◽  
On The Road

The problem of traffic safety has become increasingly prominent owing to the increase in the number of cars. Traffic accidents often occur in an instant, which makes it necessary to obtain traffic data with high resolution. High-resolution micro traffic data (HRMTD) indicates that the spatial resolution reaches the centimeter level and that the temporal resolution reaches the millisecond level. The position, direction, speed, and acceleration of objects on the road can be extracted with HRMTD. In this paper, a LiDAR sensor was installed at the roadside for data collection. An adjacent-frame fusion method for vehicle detection and tracking in complex traffic circumstances is presented. Compared with the previous research, objects can be detected and tracked without object model extraction or a bounding box description. In addition, problems caused by occlusion can be improved using adjacent frames fusion in the vehicle detection and tracking algorithms in this paper. The data processing procedure are as follows: selection of area of interest, ground point removal, vehicle clustering, and vehicle tracking. The algorithm has been tested at different sites (in Reno and Suzhou), and the results demonstrate that the algorithm can perform well in both simple and complex application scenarios.

Modifications Needed for Performing High-Resolution Cryosem in a Hitachi S-4700 Fesem Using an Emitech K1250 Cryo-Preparation System

2001 ◽  
Vol 7 (S2) ◽  
pp. 720-721
Author(s):  
Ya Chen ◽  
Chris Frethem ◽  
Stanley L. Erlandsen
Keyword(s):  
High Resolution ◽  
Thermal Contact ◽  
Control Unit ◽  
Thermal Capacity ◽  
Electron Beam Evaporation ◽  
Sample Holder ◽  
Sputter Coating ◽  
Magnetron Sputter ◽  
Sample Transfer ◽  
Transfer Device

Cryo-techniques have been successfully used in scanning electron microscopy (SEM). They are especially promising for high-resolution SEM to improve specimen preservation and reduce radiation damage [1, 2]. A number of cryo-preparation systems are commercially available for SEM, however, our experience has shown that modifications are needed to perform highresolution imaging (>50,000x).Emitech K1250 system consists of a sample preparation chamber, control unit, and cryo-stage. Magnetron sputter coating is standard and electron-beam evaporation is optional. A vacuum transfer device facilitates the sample transfer between the preparation chamber and the SEM to prevent contamination. The Emitech cryo-stage replaces the Hitachi S-4700 standard stage and the cryo-stage temperature is monitored and controlled by the Emitech control unit.The specimen is mounted on a sample holder that mounts to the cryo-stage. Therefore, the distance from the specimen to cryo-stage, the thermal capacity of the sample holder, and the thermal contact between them will affect the actual temperature of the specimen.

A high-resolution spatial and temporal on-road vehicle emission inventory in an Iranian metropolitan area, Isfahan, based on detailed hourly traffic data

2020 ◽  
Vol 11 (9) ◽  
pp. 1598-1609 ◽  
Author(s):  
Omid Ghaffarpasand ◽  
Mohammad Reza Talaie ◽  
Hossein Ahmadikia ◽  
Amirreza Talaie Khozani ◽  
Maryam Davari Shalamzari
Keyword(s):  
High Resolution ◽  
Metropolitan Area ◽  
Emission Inventory ◽  
Vehicle Emission ◽  
Traffic Data ◽  
Road Vehicle

scholarly journals Urban Arterial Road Optimization and Design Combined with HOV Carpooling under Connected Vehicle Environment

2019 ◽  
Vol 2019 ◽  
pp. 1-11
Author(s):  
Lina Mao ◽  
Wenquan Li ◽  
Pengsen Hu ◽  
Guiliang Zhou ◽  
Huiting Zhang ◽  
...  
Keyword(s):  
Traffic Congestion ◽  
Negative Impact ◽  
Traffic Volume ◽  
Road Segment ◽  
Connected Vehicle ◽  
Traffic Data ◽  
Average Speed ◽  
The Road ◽  
Arterial Road ◽  
Urban Arterial

The HOV carpooling lane offers a feasible approach to alleviate traffic congestion. The connected vehicle environment is able to provide accurate traffic data, which could optimize the design of HOV carpooling schemes. In this paper, significant tidal traffic flow phenomenon with severe traffic congestion was identified on North Beijing road (bidirectional four-lane) and South Huaihai road (bidirectional six-lane) in Huai’an, Jiangsu Province. The historical traffic data of the road segments were collected through the connected vehicle environment facilities. The purpose of this study is to investigate the effect of adopting two HOV schemes (regular HOV scheme and reversible HOV carpooling scheme) on the urban arterial road under connected vehicle environment. VISSIM was used to simulate the proposed two HOV carpooling schemes at the mentioned road segment. The simulation results showed that the reversible HOV carpooling scheme could not only mitigate the traffic congestion caused by traffic tidal phenomenon but also improve the average speed and traffic volume of the urban arterial road segment, while the regular HOV scheme may exert a negative impact on the average speed and traffic volume on the urban arterial road segment.

Sign in / Sign up

Export Citation Format

Share Document