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Route time estimation of solid waste collection vehicles based on population densityView Crossref metadata(active tab) <div id="edit-xml" class="form-item form-type-item"> <?xml version="1.0"?> <doi_batch version="4.4.1" xmlns="http://www.crossref.org/schema/4.4.1" xmlns:jats="http://www.ncbi.nlm.nih.gov/JATS1" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.crossref.org/schema/4.4.1 http://www.crossref.org/schemas/crossref4.4.1.xsd"><head><doi_batch_id>000690</doi_batch_id><timestamp>1713630108</timestamp><depositor><depositor_name>University of the Aegean</depositor_name><email_address>uoa@university.com</email_address></depositor><registrant>Global NEST Journal</registrant></head><body><journal><journal_metadata><full_title>Global NEST Journal</full_title><full_title>Global NEST: the international Journal</full_title><issn media_type="print">1790-7632</issn><issn media_type="electronic">2241-777X</issn></journal_metadata><journal_issue><titles><title>Issue 2</title></titles><publication_date><month>06</month><year>2024</year></publication_date><journal_volume><volume>13</volume></journal_volume><issue>2</issue></journal_issue><journal_article><titles><title>Route time estimation of solid waste collection vehicles based on population density</title></titles><abstract xmlns="http://www.ncbi.nlm.nih.gov/JATS1"><p>In this study, a model for stationary container system is presented to estimate collection time based on population density per 100 m road distance (LPD100). The model also estimates travel and collection times, and time spent on waiting at stop signs and traffic lights separately for stationary collection. The main scope of the model is to determine required container number (NC), the number of container locations (NCL) and collection time with stationary solid waste collection (PTC) based on LPD100. Model parameters are based on route observation using a video camera of solid waste collection in 39 districts (having 38.6 sq m area) in Trabzon City in Turkiye. Moreover, a digitized route map of Trabzon City including many layers such as road distance, container location, road direction, traffic lights was used to simulate the model. The model was tested using data obtained from collection route in Erdogdu district in Trabzon, located in Eastern Black Sea of Turkiye. Compared to observed values form a collection route in Trabzon, the model estimated route time (RTC) within % 2.9-4.9 of error margin.</p></abstract><publication_date><month>04</month><day>30</day><year>2013</year></publication_date><pages><first_page>162</first_page><last_page>169</last_page></pages><publisher_item><identifier id_type="pii">739</identifier></publisher_item><doi_data><doi>10.30955/gnj.000739</doi><timestamp>1713630108</timestamp><resource>https://journal.gnest.org/publication/739</resource></doi_data></journal_article></journal></body></doi_batch> </div>
