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Examining queue-jumping phenomenon in heterogeneous traffic stream at signalized intersection using UAV-based data

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Abstract

This research presents an in-depth microscopic analysis of heterogeneous and undisciplined traffic at the signalized intersection. Traffic data extracted from the video recorded using an unmanned aerial vehicle (UAV) at an approach of a signalized intersection is analyzed to study the within green time dynamics of traffic flow. Various parameters of Wiedemann 74, Wiedemann 99, and lateral behavior models used in microscopic traffic simulation package, Vissim, are calibrated for the local heterogeneous traffic. This research is aimed at exploring the queue-jumping phenomenon of motorbikes at signalized intersections and its impact on the saturation flow rate, travel time, and delay. The study of within green time flow dynamics shows that the flow of traffic within green time is not uniform. Surprisingly, the results indicate that the traffic flow for the first few seconds of the green time is significantly higher than the remaining period of green time, which shows a contradiction to the fact that traffic flow for the first few seconds is lower due to accelerating vehicles. Mode-wise traffic counted per second shows that this anomaly is attributed to the presence of motorbikes in front of the queue. Consequently, the outputs of simulation results obtained from calibrated Vissim show that the simulated travel time for motorbikes is significantly lower than the field-observed travel times even though the average simulated traffic flow matches accurately with the field-observed traffic flow. The findings of this research highlight the need to incorporate the queue-jumping behavior of motorbikes in the microsimulation packages to enhance their capability to model heterogeneous and undisciplined traffic.

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Acknowledgments

Authors are thankful to research assistants Amna Anwar, Anoosha Shoukat, Ain ul Huda Khan, Kanwar Kumar, Farhana, and Waqas Ahmed for their help in data collection and data extraction.

Funding

This collaborative research in UAE was supported by the Zayed University Research Cluster grant # R17075. In Pakistan, the research was carried out at Exascale Open Data Analytics Lab, National Center for Big Data & Cloud Computing (Funded by the Higher Education Commission of Pakistan).

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Authors and Affiliations

  1. NED University of Engineering and Technology, Karachi, Pakistan

    Afzal Ahmed & Syeda Ofaq Raza Zaidi

  2. Zayed University, Dubai, United Arab Emirates

    Fatma Outay

  3. Hasselt University, Hasselt, Belgium

    Muhammad Adnan

  4. Monash University, Melbourne, Australia

    Dong Ngoduy

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  1. Afzal Ahmed
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  2. Fatma Outay
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  3. Syeda Ofaq Raza Zaidi
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  4. Muhammad Adnan
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  5. Dong Ngoduy
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Correspondence to Muhammad Adnan.

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Ahmed, A., Outay, F., Zaidi, S.O.R. et al. Examining queue-jumping phenomenon in heterogeneous traffic stream at signalized intersection using UAV-based data. Pers Ubiquit Comput 25, 93–108 (2021). https://doi.org/10.1007/s00779-020-01434-y

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