Application of modern ASUDD solutions on the example of Shchors street, Belgorod

Zagorodniy, Nikolay; Borovskoy, Alexey; Borovskaya, Olga; Novopisny, Evgeny · 2021 · Crossref

DOI: 10.1051/matecconf/202134100015

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Summary

This paper addresses the challenge of optimizing traffic management in complex urban environments through the application of modern Automated Systems for Urban Road Traffic Management (ASUDD). The authors argue that traditional traffic control methods are insufficient for handling significant daily variations in traffic intensity, human factors, and the need for public transport priority. To demonstrate the efficacy of modern ASUDD solutions, the study focuses on Shchors Street in Belgorod, Russia, specifically analyzing the complex intersection with Gubkin Street, which features public transport stops and regulated access to a shopping center. The methodology involved comprehensive field studies of traffic flows during morning rush hours, categorizing vehicle types and volumes. Additionally, "Infopro" transport detectors were installed to monitor lane-specific traffic intensity. The authors utilized Aimsun software to simulate both existing and projected traffic conditions, revealing increased load on Gubkin Street. Based on these simulations, a traffic light layout plan was developed, and specific technical requirements for controllers were formulated, including support for at least 124 channels, coordinated adaptive management, and compatibility with various detector types. A comparative analysis of four controller models was conducted against criteria such as adaptive control algorithms, phase limits, and configurability. The "KDSF SPECTRUM" controller by RIPAS was selected as it met all advanced requirements, and radar detectors were installed to monitor queue lengths. The results indicate that the implementation of the adaptive ASUDD system successfully redistributed traffic flows across directions without significantly altering the total load. Comparative analysis of the simulation data showed that public transport speed doubled, while personal transport speed decreased by 1.2 times. Post-implementation data from the evening rush hour demonstrated that the adaptive control system reduced driving time on Shchors Street from 650 seconds to 500 seconds. This represents a 23% reduction in travel time compared to basic traffic light settings. The system effectively managed varying intensity levels per lane, confirming the benefits of adaptive control over static timing plans. The study concludes that optimizing traffic flows requires controllers and software capable of meeting rigorous technical specifications, particularly regarding adaptive algorithms and detector integration. The use of radar detectors proved essential for monitoring traffic flow and queue lengths. The significant reduction in travel time highlights the practical value of modern ASUDD solutions in improving urban mobility, reducing congestion, and enhancing public transport efficiency. This case study provides a framework for selecting and implementing advanced traffic control systems in similar complex urban intersections.

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