As cities continue to grow in population, the demand for public transportation, particularly shuttle taxis, has increased. Shuttle taxis typically follow specific routes within or between cities. However, this transportation mode is not currently optimized, as taxi drivers often have to stop frequently to find passengers and inquire about their destination to see if it aligns with their route. With more stops, the average speed of taxis and other vehicles on the road decreases, leading to longer travel times for both shuttle taxis as well as other vehicles. Furthermore, frequent stop-start cycles increase fuel consumption, increase CO2 emissions, increase vehicles’ wear and tear and, therefore, reduce vehicles’ life. To address these issues, a matchmaking system between passengers and shuttle taxis called Shuttle Taxi with Targeted Stops (STTS) is proposed. Passengers can choose their taxi lines and get matched with a shuttle taxi with free capacity based on their source and destination locations. The STTS system aims to reduce travel times and enhance the overall quality of shuttle taxi services. Implementation of this system is expected to reduce urban traffic congestion, decrease the number of car stops, particularly taxis, and minimize fuel consumption and environmental impact caused by shuttle taxis and other vehicles on the road. Based on simulation results, the STTS method increases average speed of non-taxi cars and taxis up to 9.3% and 51.7%, respectively, while decreasing the average travel time of passengers by up to 20%.


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    Title :

    IoT-Based Intelligent Transportation System for Passenger-Shuttle Taxi Matchmaking


    Contributors:


    Publication date :

    2024-05-14


    Size :

    657355 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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