Automatic Methodology for Multi-modal Trip Generation with Roadside LiDAR
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Authors
Karambakhsh, Shabnam
Issue Date
2023
Type
Thesis
Language
Keywords
Alternative Title
Abstract
Transportation planning based on historical data and methods has major limitations. Trip data canbe useful to increase the transportation safety of the specific sites and the process and programming
purposes. One of the challenges in this regard is data collecting to gain an accurate analysis of land
use development. The previous methods of data gathering such as human observational data
counting and automatic methods like pneumatic tubes and video camera suffers some limitations
that affect the accuracy of trip analysis which cause over mitigating or set some wrong rules and
regulations. Light Detection and Ranging (LiDAR) sensing is a powerful tool that has been vastly
used for mapping, safety, and medical applications. [1] Also, its application in transportation has
drawn attention in recent years. However, LiDAR sense is yet to be further explored in trip
generation. This study is an initial attempt to: 1) perform a LiDAR-based trip generation data
gathering for a local area in midtown, Reno, and 2) analyze the resulting data based on the GIS
software to develop a systematic plan for the case study and beyond.