Construction of Adjustment Model of Traffic Volume Forecast in The Latter Part of Expressway Operating

2012 ◽  
Vol 178-181 ◽  
pp. 1526-1531
Author(s):  
Ming Shun Li ◽  
Zuo Hui Zhu
Keyword(s):  
Linear Relationship ◽  
Traffic Flow ◽  
Feasibility Study ◽  
Least Square Method ◽  
Traffic Volume ◽  
Least Square ◽  
Adjustment Model ◽  
Traffic Flow Forecast ◽  
Method Model ◽  
Flow Forecast

This paper focuses on the problem of serious deviation about predicted traffic flow on the feasibility study stage of expressway,puts forward an idea to compare and analyse the predicted traffic flow in feasibility study stage and the actual traffic after project operation,introducts least square method model, and finds out the linear relationship between them, thus predicts traffic flow of expressway operation. Finally, the calculation is made by combining with concrete expressway project,which proves that this method is usefull to improving the accuracy of the traffic flow forecast.

scholarly journals Application of Artificial Intelligence Technology in Traffic Flow Forecast

2021 ◽  
Vol 1852 (2) ◽  
pp. 022076
Author(s):  
Yunxiang Li ◽  
Guochang Liu ◽  
Yingying Cheng ◽  
Jifei Wu ◽  
Yongyi Xiong ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Traffic Flow ◽  
Traffic Flow Forecast ◽  
Artificial Intelligence Technology ◽  
Flow Forecast

Research of Short-Term Traffic Flow Forecast Method Based on the Kalman Filter

ICCTP 2011 ◽  
2011 ◽  
Author(s):  
Feng Chen ◽  
Yuanhua Jia ◽  
Wenjuan An ◽  
Na Zhang ◽  
Zhonghai Niu
Keyword(s):  
Kalman Filter ◽  
Traffic Flow ◽  
Forecast Method ◽  
Short Term ◽  
Traffic Flow Forecast ◽  
Flow Forecast

Research on Traffic Flow Forecast Based on Cellular Signaling Data

2021 ◽  
Author(s):  
Liangyu Yao ◽  
Jianmin Bao ◽  
Fei Ding ◽  
Nianqi Zhang ◽  
En Tong
Keyword(s):  
Traffic Flow ◽  
Cellular Signaling ◽  
Traffic Flow Forecast ◽  
Flow Forecast

scholarly journals A TRAFFIC FUNDAMENTAL DIAGRAM CALIBRATING METHODOLOGY TO AVOID UNBALANCED SPEED–DENSITY OBSERVATIONS

Transport ◽  
2021 ◽  
Vol 36 (1) ◽  
pp. 13-24
Author(s):  
Chunbo Zhang ◽  
Zhaoguo Huang ◽  
Yonggang Wang
Keyword(s):  
Traffic Flow ◽  
Least Square Method ◽  
Least Square ◽  
Fundamental Diagram ◽  
Traffic Capacity ◽  
Density Relationship ◽  
Sample Method

Traffic fundamental diagram is extremely important to analyse traffic flow and traffic capacity, and the central part of traffic fundamental diagram is to calibrate speed–density relationship. However, because of unbalanced speed–density observations, calibrating results using Least Square Method (LSM) with all speed–density points always lead to inaccurate effect, so this paper proposed a selecting data sample method and then LSM was used to calibrate four well-known single-regime models. Comparisons were made among the results using LSM with all speed–density points and the selecting data sample. Results indicated that the selecting data sample method proposed by this paper can calibrate the singleregime models well, and the method overcomes the inaccurate effect caused by unbalanced speed–density observations. Data from different highways validated the results. The contribution of this paper is that the proposed method can help researchers to determine more precise traffic fundamental diagram.

scholarly journals Research on Air Traffic Flow Forecast Based on ELM Non-Iterative Algorithm

2020 ◽  
Author(s):  
Zhaoyue Zhang ◽  
An Zhang ◽  
Cong Sun ◽  
Shuaida Xiang ◽  
Jichen Guan ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Iterative Algorithm ◽  
Air Traffic ◽  
Air Traffic Flow ◽  
Traffic Flow Forecast ◽  
Flow Forecast

The Forecast and the Optimization Control of the Complex Traffic Flow Based on the Hybrid Immune Intelligent Algorithm

2014 ◽  
Vol 8 (1) ◽  
pp. 245-251 ◽  
Author(s):  
Li Qing ◽  
Tao Yongqin ◽  
Han Yongguo ◽  
Zhang Qingming
Keyword(s):  
Traffic Flow ◽  
Transportation Network ◽  
Guidance System ◽  
Predictive Values ◽  
Forecasting Error ◽  
Nonlinear Dynamic Characteristics ◽  
Traffic Flow Forecast ◽  
Search Speed ◽  
Traffic Guidance ◽  
Flow Forecast

Transportation system has time-varying, coupling and nonlinear dynamic characteristics. Traffic flow forecast is one of the key technologies of traffic guidance. It is very difficult to accurately forecast them effectively. This paper has analyzed the complexity and the evaluation index of urban transportation network and has proposed the forecasting model of the hybrid algorithm based on chaos immune knowledge. First of all, the chaos knowledge is introduced into the topology structure of immune network, so as to obtain the matching predictive values and knowledge base. Secondly, this algorithm can dynamically control and adjusted the regional search speed and can fuse the information obtained by the chaos and immune algorithm, in order to realize the short-term traffic flow forecast. Finally, the simulation experiment shows that the traffic flow forecasting error obtained by the method is small, feasible and effective and can better meet the needs of the traffic guidance system.

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