Research on Intersection Phase Timing Calculating Method Based on Interval Detection Data

Liu, Shuqing; Kawasaki, Tseuneo; Zhai, Zhanqiang

doi:10.1061/9780784482902.013

Cited by 2 publications

(2 citation statements)

References 8 publications

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“…In [ 21 ], a method of overflow identification and control at intersections is proposed based on millimeter-wave radar data, which is installed at the departure road intersection to detect data. Then, a new intersection phase-timing calculation method is proposed based on the data collected by radar [ 22 ].…”

Section: Related Workmentioning

confidence: 99%

A Trajectory Compensation Method Considering the Car-Following Behavior for Data Missing of Millimeter-Wave Radar in Roadside Detection Applications

Zhang

Liu

Teng

2023

Sensors

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Concerning roadside traffic detection applications, and to address the millimeter-wave radar’s missing data problem caused by target occlusion or the absence of features in low-speed conditions, this paper proposes a trajectory compensation method regarding car-following behavior. Referring to the installation scheme of the detector, a coordinate transformation method is presented to unify the radar spatial coordinates with the road coordinates. Considering the driver’s car-following behavior, the optimal velocity model (OV), full velocity difference model (FVD), and the full velocity difference and acceleration (FVDA) model are applied for tracking the vehicle’s trajectory related to the movement of the vehicle ahead. Finally, a data compensation scheme is presented. Taking actual trajectory data as samples, the proposed methods are verifiably useful for compensating for missing data and reconstructing target trajectories. Statistical results of different missing data trajectories demonstrate the rationality of the application of car-following models for the missing data compensation, and the FVDA model performs well compared with the OV and FVD models.

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Section: Related Workmentioning

confidence: 99%

A Trajectory Compensation Method Considering the Car-Following Behavior for Data Missing of Millimeter-Wave Radar in Roadside Detection Applications

Zhang

Liu

Teng

2023

Sensors

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“…In Ref. [35], a new method for calculating intersection phase time series based on interval detection data from millimeter-wave radars reduces vehicle congestion at intersections. And some systems based on the fusion of millimeter-wave radar and camera have been proposed to improve the robustness of vehicle information awareness on urban roads [36,37].…”

Section: Millimeter Wave Radar-based Road Application and Congestion ...mentioning

confidence: 99%

Urban traffic congestion alleviation system based on millimeter wave radar and improved probabilistic neural network

Yang

Zhang

et al. 2023

IET Radar Sonar & Navi

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The millimeter‐wave radar sensor is widely used for urban traffic surveillance because of its weather resistance and high detection accuracy. Methods such as fuzzy theory, pattern recognition, and artificial neural networks have been integrated into the research of traffic state discrimination. However, research on systematically describing the fusion of sensors and traffic state discrimination algorithms to alleviate urban road congestion is still lacking, especially based on millimeter‐wave radar. Thus, the authors propose an urban traffic congestion alleviation system framework. First, the design and deployment of the millimeter‐wave radar system, including waveforms, signal processing flow, and target tracking, are demonstrated to achieve vehicle information acquisition and output. Then, the appropriate traffic parameters are obtained by analysing traffic state influencing factors and the radar data characteristics. Finally, a traffic conditions identification algorithm combining spectral clustering and neural network algorithm is presented to realise road congestion level classification. The system is applied to real urban intersections rather than simulation or approximate real simulation. According to the current road congestion level, regulate the traffic light state to achieve road vehicle driving command. Experiments show that the proposed system can effectively reduce road congestion by 20% compared to the current fixed traffic light system.

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Research on Intersection Phase Timing Calculating Method Based on Interval Detection Data

Cited by 2 publications

References 8 publications

A Trajectory Compensation Method Considering the Car-Following Behavior for Data Missing of Millimeter-Wave Radar in Roadside Detection Applications

A Trajectory Compensation Method Considering the Car-Following Behavior for Data Missing of Millimeter-Wave Radar in Roadside Detection Applications

Urban traffic congestion alleviation system based on millimeter wave radar and improved probabilistic neural network

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