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Data-driven Multimodal Transportation Energy Consumption Prediction and Analysis Framework for Sustainable Transit and Transportation Planning

项目名称：	Data-driven Multimodal Transportation Energy Consumption Prediction and Analysis Framework for Sustainable Transit and Transportation Planning
摘要：	Description: Transit agencies/mobility providers usually utilize time-based and distance-based link-level information in planning their routes and schedules. However, average energy consumption rates (e.g., gallons per mile, kWh per mile) on links of a road network are seldom considered in these planning activities. The major reason is a lack of accurate energy consumption information. For sustainable transportation planning, gathering and analyzing data on energy consumption, particularly considering new alternative vehicle technologies, is needed. Intellectual Merit: The goal of this project is to develop a high-resolution system-level transportation energy data analysis and prediction framework for transit schedule/operation planning, aimed at improving energy efficiency. Broader Impacts: The outcomes of this project will be utilized by regional planners or transit/mobility service providers for route/schedule planning and traveler guidance system integration. The goal is to reduce energy consumption, which will benefit transit agencies, transit patrons, and the public. Technology Transfer Plan: The tangible products of this project will be: 1) tools to estimate link-level transportation energy consumption, and 2) an energy consumption density map. Results will be made available for use by transit agencies/mobility providers.
状态：	Active
资金：	$46464
资助组织：	Benedict College
管理组织：	University of South Carolina, Columbia
项目负责人：	Chen, Yuche
执行机构：	Benedict College
主要研究人员：	Huynh, Nathan
开始时间：	20181201
预计完成日期：	20200831
实际结束时间：	0