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  • Open Access

    ARTICLE

    Delivery Service Management System Using Google Maps for SMEs in Emerging Countries

    Sophea Horng, Pisal Yenradee*

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 6119-6143, 2023, DOI:10.32604/cmc.2023.038764

    Abstract This paper proposes a Delivery Service Management (DSM) system for Small and Medium Enterprises (SMEs) that own a delivery fleet of pickup trucks to manage Business-to-Business (B2B) delivery services. The proposed DSM system integrates four systems: Delivery Location Positioning (DLP), Delivery Route Planning (DRP), Arrival Time Prediction (ATP), and Communication and Data Sharing (CDS) systems. These systems are used to pinpoint the delivery locations of customers, plan the delivery route of each truck, predict arrival time (with an interval) at each delivery location, and communicate and share information among stakeholders, respectively. The DSM system deploys Google applications, a GPS tracking… More >

  • Open Access

    ARTICLE

    Deriving Driver Behavioral Pattern Analysis and Performance Using Neural Network Approaches

    Meenakshi Malik1, Rainu Nandal1,*, Surjeet Dalal2, Vivek Jalglan3, Dac-Nhuong Le4,5

    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 87-99, 2022, DOI:10.32604/iasc.2022.020249

    Abstract It has been observed that driver behavior has a direct and considerable impact upon factors like fuel consumption, environmentally harmful emissions, and public safety, making it a key consideration of further research in order to monitor and control such related hazards. This has fueled our decision to conduct a study in order to arrive at an efficient way of analyzing the various parameters of driver behavior and find ways and means of positively impacting such behavior. It has been ascertained that such behavioral patterns can significantly impact the analysis of traffic-related conditions and outcomes. In such cases, the specific vehicular… More >

  • Open Access

    ARTICLE

    NARX Network Based Driver Behavior Analysis and Prediction Using Time-series Modeling

    Ling Wu1, Haoxue Liu2, Tong Zhu2, Yueqi Hu3

    Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 633-642, 2018, DOI:10.31209/2018.100000030

    Abstract The objective of the current study was to examine how experienced and inexperienced driver behaviour changed (including heart rate and longitudinal speeds) when approaching and exiting highway tunnels. Simultaneously, the NARX neural network was used to predict real-time speed with the heart rate regarded as the input variable. The results indicated that familiarity with the experimental route did decrease drivers’ mental stress but resulted in higher speed. The proposed NARX model could predict synchronous speed with high accuracy. These results of the present study concern how to establish the automated driver model in the simulation environment. More >

  • Open Access

    ARTICLE

    Analysis of Bus Ride Comfort Using Smartphone Sensor Data

    Hoong-Chor Chin1, Xingting Pang1, Zhaoxia Wang2,3,*

    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 455-463, 2019, DOI:10.32604/cmc.2019.05664

    Abstract Passenger comfort is an important indicator that is often used to measure the quality of public transport services. It may also be a crucial factor in the passenger’s choice of transport mode. The typical method of assessing passenger comfort is through a passenger interview survey which can be tedious. This study aims to investigate the relationship between bus ride comfort based on ride smoothness and the vehicle’s motion detected by the smartphone sensors. An experiment was carried out on a bus fixed route within the University campus where comfort levels were rated on a 3-point scale and recorded at 5-second… More >

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