Application of Unmanned Aerial Vehicles to Pedestrian Traffic Monitoring and Management for Shopping Streets

© 2017 The Authors. Published by Elsevier B.V. Collecting data of pedestrian traffic flows is typically complicated or labor-intensive. Using conventional techniques, such as manual observers, on-site video records, and questionnaire surveys, to investigate pedestrian flow characteristics and behavi...

Full description

Saved in:
Bibliographic Details
Main Authors: Chomphunut Sutheerakul, Nopadon Kronprasert, Manop Kaewmoracharoen, Preda Pichayapan
Format: Conference Proceeding
Published: 2018
Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85020167199&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/47272
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Chiang Mai University
id th-cmuir.6653943832-47272
record_format dspace
spelling th-cmuir.6653943832-472722018-04-25T07:28:59Z Application of Unmanned Aerial Vehicles to Pedestrian Traffic Monitoring and Management for Shopping Streets Chomphunut Sutheerakul Nopadon Kronprasert Manop Kaewmoracharoen Preda Pichayapan © 2017 The Authors. Published by Elsevier B.V. Collecting data of pedestrian traffic flows is typically complicated or labor-intensive. Using conventional techniques, such as manual observers, on-site video records, and questionnaire surveys, to investigate pedestrian flow characteristics and behavior along a pedestrian shopping street may be restrictive. This study focuses on applying an Unmanned Aerial Vehicle (UAV) - a small aircraft remotely controlled - to monitor pedestrian traffic flows and using data collected from UAVs to manage pedestrian demand and supply. An unmanned aerial vehicle (UAV), also known as a drone, is an innovative technology in various transportation applications. It is capable of carrying a video camera to record high-quality images and real-time videos, and global positioning system (GPS) to transmit spatial and temporal data to the ground. The efforts are made for two thrusts. The first part is to investigate the feasibility of UAV technology to collect data on pedestrian flow characteristics and data on pedestrian supply characteristics. The second part is to evaluate pedestrian service characteristics along shopping streets. The study selected a 2-km shopping street network in Chiang Mai City, Thailand, as a case study. The results showed that UAV can be an alternative viable technology in monitoring pedestrian traffic characteristics in outdoor pedestrian zones. Data collected from UAV technology can be used to develop traffic demand and supply management plans in a more efficient and cost-effective way than conventional data collection techniques. 2018-04-25T07:28:59Z 2018-04-25T07:28:59Z 2017-01-01 Conference Proceeding 23521465 23521457 2-s2.0-85020167199 10.1016/j.trpro.2017.05.131 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85020167199&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/47272
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
description © 2017 The Authors. Published by Elsevier B.V. Collecting data of pedestrian traffic flows is typically complicated or labor-intensive. Using conventional techniques, such as manual observers, on-site video records, and questionnaire surveys, to investigate pedestrian flow characteristics and behavior along a pedestrian shopping street may be restrictive. This study focuses on applying an Unmanned Aerial Vehicle (UAV) - a small aircraft remotely controlled - to monitor pedestrian traffic flows and using data collected from UAVs to manage pedestrian demand and supply. An unmanned aerial vehicle (UAV), also known as a drone, is an innovative technology in various transportation applications. It is capable of carrying a video camera to record high-quality images and real-time videos, and global positioning system (GPS) to transmit spatial and temporal data to the ground. The efforts are made for two thrusts. The first part is to investigate the feasibility of UAV technology to collect data on pedestrian flow characteristics and data on pedestrian supply characteristics. The second part is to evaluate pedestrian service characteristics along shopping streets. The study selected a 2-km shopping street network in Chiang Mai City, Thailand, as a case study. The results showed that UAV can be an alternative viable technology in monitoring pedestrian traffic characteristics in outdoor pedestrian zones. Data collected from UAV technology can be used to develop traffic demand and supply management plans in a more efficient and cost-effective way than conventional data collection techniques.
format Conference Proceeding
author Chomphunut Sutheerakul
Nopadon Kronprasert
Manop Kaewmoracharoen
Preda Pichayapan
spellingShingle Chomphunut Sutheerakul
Nopadon Kronprasert
Manop Kaewmoracharoen
Preda Pichayapan
Application of Unmanned Aerial Vehicles to Pedestrian Traffic Monitoring and Management for Shopping Streets
author_facet Chomphunut Sutheerakul
Nopadon Kronprasert
Manop Kaewmoracharoen
Preda Pichayapan
author_sort Chomphunut Sutheerakul
title Application of Unmanned Aerial Vehicles to Pedestrian Traffic Monitoring and Management for Shopping Streets
title_short Application of Unmanned Aerial Vehicles to Pedestrian Traffic Monitoring and Management for Shopping Streets
title_full Application of Unmanned Aerial Vehicles to Pedestrian Traffic Monitoring and Management for Shopping Streets
title_fullStr Application of Unmanned Aerial Vehicles to Pedestrian Traffic Monitoring and Management for Shopping Streets
title_full_unstemmed Application of Unmanned Aerial Vehicles to Pedestrian Traffic Monitoring and Management for Shopping Streets
title_sort application of unmanned aerial vehicles to pedestrian traffic monitoring and management for shopping streets
publishDate 2018
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85020167199&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/47272
_version_ 1681423030185623552