详情

原文传递 Data-driven Network Models for Analyzing Multi-modal Transportation Systems.

题名：	Data-driven Network Models for Analyzing Multi-modal Transportation Systems.
作者：	Qian, Z.; Pi, X.; Ma, W.
关键词：	Highway, Multimodal transportation, Public transit, Public transportation, Network analysis(Planning), Parking, Passengers, Traffic flow, Transportation planning, Travel behavior, Highways, Planning, Forecasting, Carnegie Mellon University
摘要：	The project team proposes to establish a new theory and open-source tool for modeling both passenger and vehicle flow in a sophisticated transportation network. The model takes input of data collected from various source, and models individual travel activities and behavior on roadway systems, transit systems and parking systems. The multi-modal network model is the key to systematic planning and operations of transportation infrastructure. Planning, operational strategies and policies can be fully examined in the network model in terms of system delays, reliability, vehicle-miles traveled (VMT), fuel consumption and emissions. This research will use real-time and historical roadway, parking and transit data, in both Philadelphia and Pittsburgh Region, to test and validate the network model. This research can ultimately help the regional metropolitan planning organizations (MPOs) and departments of transportation (DOTs) quantitatively analyze and optimize various management strategies for sustainable mobility.
报告类型：	科技报告