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Saturated arterial coordinate control strategy optimization considering macroscopic fundamental diagram

Lin Xuanhua, Lin Xiaohui, Chen Kelian

Archives of Transport

2022

Vol. 62, iss. 2

73--90

MFD is widely used in traffic state evaluation because of its description of the macro level of urban road network. Aiming at the control strategy optimization problem of urban arterial road network under saturated traffic flow state, this study analyzes the MFD characteristics of a typical three-segment "ascending-stable-descending segment" and its advantages in characterizing the macroscopic operation efficiency of the road network, a arterial coordination control strategy considering MFD is proposed. According to the characteristics of MFD, it is proposed that the slope of the ascending segment and the capacity of the road network represent the operating efficiency of the free flow and saturated flow of the road network respectively. The traffic flow and density data of road segment are obtained by the road detector through Vissim simulation software. Aiming at the problem that the MFD is too discrete due to unreasonable control strategy or traffic condition, and in order to extract the MFD optimization target indicators, it is proposed to extract the key boundary points of the MFD by the “tic-tac-toe” method and divide the MFD state by Gaussian mixture clustering. The genetic algorithm integrates the multi-objective particle swarm algorithm as the solution algorithm, and the simulation iterative process is completed through Python programming and the com interface of Vissim software. In order to verify the validity of the model and algorithm, the actual three-intersections arterial road network is used for verification, and the model in this study is compared with the optimization model without considering MFD, the model solved by traditional algebraic method, and the optimization model solved by typical multi-objective particle swarm. Results show that the model in this research performs well in efficiency indicators such as total delay, average delay, and queue coefficient. At the same time, the MFD form has highest stability, the control effect is the best in the saturated state. The solution algorithm GA-MOPSO also has a better solution effect.

Detailed evaluation and analysis of vision-based online traffic parameters estimation approach using low resolution web cameras

Ali M., Touko Tcheumadjeu L., Zuev S., Ruppe S.

Archives of Transport System Telematics

2014

Vol. 7, iss. 2

9--13

In this paper, we give an overview and a detail analysis of our approach for vision-based real-time traffic parameters estimation using low-resolution web cameras. Traffic parameters estimation approach mainly includes three major steps, (1) stable background estimation, (2) vehicle detection, mean speed and traffic flow estimation, and (3) traffic scene classification into three states (normal and congested). The background image is estimated and updated in realtime by novel background estimation algorithm based on the median of First-in-First-Out (FIFO) buffer of rectified traffic images. Vehicles are detected by background subtraction followed by post-processing steps. By exploiting the domain knowledge of real-world traffic flow patterns, mean speed and traffic flow can be estimated reliably and accurately. Naive Bayes classifier with statistical features is used for traffic scene classification. The traffic parameter estimation approach is tested and evaluated at the German Aerospace Center’s (DLR) urban road research laboratory in Berlin for 24 hours of live streaming data from web-cameras with frames per second 1, 5 and 10. Image resolution is 348 x 259 and JPEG compression is 50%. Processed traffic data is cross-checked with synchronized induction loop data. Detailed evaluation and analysis shows high accuracy and robustness of traffic parameters estimation approach using low-resolution web-cameras under challenging traffic conditions.

A method for automatic traffic-state identification from the Dresden live-camera system

Doge K.

Zeszyty Naukowe. Transport / Politechnika Śląska

2003

z. 51

95-104

The presented paper wonts to describe a new solution for the problem of real-time identification of the traffic state from live-camera images based on the analysis of stochastic signals. By using the Dresden Live-Camera-System which is providing real-time information about the traffic state on 22 focal points one is able to analyze a wide range of image types under different are severe conditions. At the present time 22 Live-Cameras are in use from Pirna in southeast until the north of Dresden and can be surveyed at "www.intermobil.org"

Artykuł opisuje nowe rozwiązanie dla problemu identyfikacji w czasie rzeczywistym stanu ruchu z obrazów pochodzących z kamery w oparciu o analizę sygnałów stochastycznych. Poprzez wykorzystanie drezdeńskiego systemu monitoringu, który dotarcza informację w czasie rzeczywistym o stanie ruchu z 22 punktów, istnieje możliwość analizy szerokiego zakresu typów obrazu w różnych warunkach. Obecnie 22 kamery znajdują się w eksploatacji w Dreźnie i mogą być śledzone na stronie internetowej www.intermobil.org