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Contextual Route Recommendation System in Heterogeneous Traffic Flow

Author

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  • Surya Michrandi Nasution

    (School of Electrical Engineering, Institut Teknologi Bandung, Jl. Ganesa 10, Bandung 40132, Indonesia)

  • Emir Husni

    (School of Electrical Engineering, Institut Teknologi Bandung, Jl. Ganesa 10, Bandung 40132, Indonesia)

  • Kuspriyanto Kuspriyanto

    (School of Electrical Engineering, Institut Teknologi Bandung, Jl. Ganesa 10, Bandung 40132, Indonesia)

  • Rahadian Yusuf

    (School of Electrical Engineering, Institut Teknologi Bandung, Jl. Ganesa 10, Bandung 40132, Indonesia)

  • Bernardo Nugroho Yahya

    (Department of Industrial & Management Engineering, Hankuk University of Foreign Studies Global Campus, Oedae-ro 81, Mohyeon-eup, Cheoin-gu, Yongin 17035, Gyeonggi, Korea)

Abstract

The traffic composition in developing countries comprises of variety of vehicles which include cars, buses, trucks, and motorcycles. Motorcycles dominate the road with 77.5% compared to other types. Meanwhile, route recommendation such as navigation and Advanced Driver Assistance Systems (ADAS) is limited to particular vehicles only. In this research, we propose a framework for a contextual route recommendation system that is compatible with traffic conditions and vehicle type, along with other relevant attributes (traffic prediction, weather, temperature, humidity, heterogeneity, current speed, and road length). The framework consists of two phases. First, it predicts the traffic conditions by using Knowledge-Growing Bayes Classifier on which the dataset is obtained from crawling the public CCTV feeds and TomTom digital map application for each observed road. The performances of the traffic prediction are around 60.78–73.69%, 63.64–77.39%, and 60.78–73.69%, for accuracy, precision, and recall respectively. Second, to accommodate the route recommendation, we simulate and utilize a new measure, called road capacity value, along with the Dijkstra algorithm. By adopting the compatibility, the simulation results could show alternative paths with the lowest RCV (road capacity value).

Suggested Citation

  • Surya Michrandi Nasution & Emir Husni & Kuspriyanto Kuspriyanto & Rahadian Yusuf & Bernardo Nugroho Yahya, 2021. "Contextual Route Recommendation System in Heterogeneous Traffic Flow," Sustainability, MDPI, vol. 13(23), pages 1-21, November.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:23:p:13191-:d:690343
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    References listed on IDEAS

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    1. Ma, Jie & Xu, Min & Meng, Qiang & Cheng, Lin, 2020. "Ridesharing user equilibrium problem under OD-based surge pricing strategy," Transportation Research Part B: Methodological, Elsevier, vol. 134(C), pages 1-24.
    2. Tanzina Afrin & Nita Yodo, 2020. "A Survey of Road Traffic Congestion Measures towards a Sustainable and Resilient Transportation System," Sustainability, MDPI, vol. 12(11), pages 1-23, June.
    3. Sara Paiva & Xabiel García Pañeda & Victor Corcoba & Roberto García & Próspero Morán & Laura Pozueco & Marina Valdés & Covadonga del Camino, 2021. "User Preferences in the Design of Advanced Driver Assistance Systems," Sustainability, MDPI, vol. 13(7), pages 1-25, April.
    4. Hamid R. Sayarshad & Vahid Mahmoodian & Nebojša Bojović, 2021. "Dynamic Inventory Routing and Pricing Problem with a Mixed Fleet of Electric and Conventional Urban Freight Vehicles," Sustainability, MDPI, vol. 13(12), pages 1-16, June.
    5. Hugo Ferreira & Carlos Manuel Rodrigues & Carlos Pinho, 2019. "Impact of Road Geometry on Vehicle Energy Consumption and CO 2 Emissions: An Energy-Efficiency Rating Methodology," Energies, MDPI, vol. 13(1), pages 1-27, December.
    6. Katarzyna Gładyszewska-Fiedoruk & Tomasz Janusz Teleszewski, 2020. "Modeling of Humidity in Passenger Cars Equipped with Mechanical Ventilation," Energies, MDPI, vol. 13(11), pages 1-14, June.
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    Cited by:

    1. Surya Michrandi Nasution & Emir Husni & Kuspriyanto Kuspriyanto & Rahadian Yusuf, 2022. "Personalized Route Recommendation Using F-AHP-Express," Sustainability, MDPI, vol. 14(17), pages 1-28, August.

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