Capacity Analysis of Urban Arterial Midblock Sections Under Mixed Traffic Conditions

Dhamaniya, Ashish; Bari, Chintaman; Patkar, Manish

doi:10.1007/s13177-022-00298-1

Cited by 6 publications

(5 citation statements)

References 21 publications

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“…Dhamaniya et al [14] measured traffic flow density in mixed traffic conditions from the ratio of speed, flow, and density, and a rationale was provided for changes in speed depending on the traffic flow structure and traffic density.…”

Section: Literature Reviewmentioning

confidence: 99%

Studying the Relationship between the Traffic Flow Structure, the Traffic Capacity of Intersections, and Vehicle-Related Emissions

Shepelev,

Glushkov,

Slobodin

et al. 2023

Mathematics

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This paper proposes a new approach to assessing the impact of changes in the traffic flow on pollutant emissions and the traffic capacity of signal-controlled intersections. We present an intelligent vision system tailored to monitor the traffic behavior at signal-controlled intersections in urban areas. Traffic cameras are used to collect real-time vehicle traffic data. Our system provides valuable insight into the relationship between traffic flows, emissions, and intersection capacity. This study shows how changes in the traffic composition reduce the traffic capacity of intersections and increase emissions, especially those involving fine dust particles. Using the combination of fuzzy logic methods and Gaussian spline distribution functions, we demonstrate the variability of these relationships and highlight the need to further study compromises between mobility and air quality. Ultimately, our results offer promising opportunities for the development of intelligent traffic management systems aimed at balancing the demands of urban mobility while minimizing environmental impact. This study demonstrates the importance of taking into account the correlation between the change in the composition of traffic queues due to a random change in the traffic flow and its impact on emissions and the traffic capacity of intersections. This study found that the presence of various groups of vehicles and their position in the queue can reduce the traffic capacity by up to 70% and increase the growth of harmful emissions by 14 fold.

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Section: Literature Reviewmentioning

confidence: 99%

Studying the Relationship between the Traffic Flow Structure, the Traffic Capacity of Intersections, and Vehicle-Related Emissions

Shepelev,

Glushkov,

Slobodin

et al. 2023

Mathematics

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show abstract

“…The construction of urban roads and the upgrading and addition of traffic management equipment have improved urban traffic conditions [3]. However, with the rapid socio-economic development and the rapid increase in traffic mobility levels, urban traffic problems have become more and more serious, with traffic congestion and traffic accidents occurring so frequently that road expansion alone is not sufficient to fully solve the traffic problems [4][5].…”

Section: Introductionmentioning

confidence: 99%

Multi-objective Tracking Algorithm for Intelligent Networked Vehicles in Hybrid Traffic

Zhou,

Jiang

2024

Proceedings of the First International Conference on Science, Engineering and Technology Practices for Sustainable Development,

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The increase in the number of automobiles has expanded the scope of public travel, bringing great convenience to people's lives and bringing many social problems such as traffic accidents, urban road congestion and the gradual increase of foggy weather. As an important part of the intelligent transportation system, intelligent networked vehicles are of great value and significance in solving the negative problems that exist in current hybrid transportation. The objective of this paper is to study the multi-objective tracking algorithm for intelligent networked vehicles based on hybrid traffic. A robust VB-RMTCT multi-target tracking algorithm is proposed. Considering the unknown localization noise statistics and random wild values of the relative positions of Hv and Cv, the mean-field theory is used to model the student t-distribution and non-Gaussian properties for numerical simulation of the localization noise, and the results show that the VB-RMTCT tracking algorithm can effectively and consistently improve the target state estimation performance compared with other traditional research methods.

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“…The objectives of this study come in twofold, i.e. (1) to develop a new capacity model for urban roads, termed the UrbanCap model, and (2) to determine the factors that influence the urban road capacity. Traffic data is collected from the sites selected before extracting the traffic parameters required for the model development.…”

Section: Introductionmentioning

confidence: 99%

New Capacity Model for Malaysian Urban Roads Using Macroscopic Fundamental Diagram and Multiple Linear Regression Approach

Khoo,

Lum Li Kai,

KS Ashita

2024

IEMJ

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The existing manuals used to estimate urban road capacity have limitations. Adapting these manuals to compute the road capacity at urban roads reduces estimation accuracy. This study attempts to develop a capacity model to characterize urban road capacity. Twenty-two sites consisting of the collector/distributor roads and local roads in the Cheras-Kajang area in Klang Valley are selected for traffic data collection during the morning peak hour from 8 a.m. to 9 a.m. Site video camera recording is carried out, and the traffic data is extracted from the video footage. The speed-density and flow-density curves of the macroscopic fundamental diagram are fitted with the traffic data extracted. The capacity value is then derived from these curves. The urban road capacity model, termed the UrbanCap model, is developed in this study using the multiple linear regression approach. The results show that the urban road capacity depends on the type of road and carriageway and speed limit. The comparison of the capacity values produced from the UrbanCap model with other manuals justifies that it has a better estimate than the existing manuals used in Malaysia. The results also signify a need to develop a manual/guideline to quantify the urban road capacity in Malaysia for road design and analysis.

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Capacity Analysis of Urban Arterial Midblock Sections Under Mixed Traffic Conditions

Cited by 6 publications

References 21 publications

Studying the Relationship between the Traffic Flow Structure, the Traffic Capacity of Intersections, and Vehicle-Related Emissions

Studying the Relationship between the Traffic Flow Structure, the Traffic Capacity of Intersections, and Vehicle-Related Emissions

Multi-objective Tracking Algorithm for Intelligent Networked Vehicles in Hybrid Traffic

New Capacity Model for Malaysian Urban Roads Using Macroscopic Fundamental Diagram and Multiple Linear Regression Approach

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