Using big data to analyze long-haul vs regional-short-haul trips for medium- and heavy-duty vehicles

利用大数据分析中型和重型车辆的长途运输与区域短途运输

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Abstract

This dataset outlines regional short-haul (RSH) and long-haul (LH) trips for medium- and heavy-duty vehicles (MDHDVs) within the Inland Empire, Southern California, collated through collaboration with a big data vendor employing standardized methodologies for traffic data capture. The compilation encompasses detailed records of trip origins, destinations, timestamps, vehicle classifications, and routes. This strategic categorization facilitates a granular analysis, enabling data scientists to differentiate between RSH and LH travel patterns efficiently. The genesis of this dataset was predicated on the necessity to comprehend the operational dynamics of MDHDVs in the context of transitioning to Zero Emission Vehicles. By offering a coherent framework to segregate RSH and LH trips, the dataset stands as a pivotal resource for stakeholders in environmental policy formulation, urban and transportation planning, and logistics management.

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