BibTex Citation Data :
@article{MKTS79549, author = {Alfa Narendra and Ahmad Wildan Diyafillah and Alfiansyah Nur Abdillah and Annas Ridho Agustiyar and Devi Sajna Risay Aszahro and Muhammad Rahil Danial Maula and Nadifa Silviana}, title = {Perencanaan Waktu Pencacahan Lalu Lintas Optimal di Jalan Kolektor Sekunder Perkotaan: Pemanfaatan Data Waktu Populer Google Maps (Studi Kasus: Kota Semarang, Indonesia)}, journal = {MEDIA KOMUNIKASI TEKNIK SIPIL}, volume = {32}, number = {1}, year = {2026}, keywords = {Google maps; peak traffic times; traffic counting}, abstract = { Conventional traffic volume surveys used to identify peak hours require extensive data collection periods, often taking up to 84 days. Although Narendra (2022) proposed leveraging the Google Maps \"Popular Times\" feature as a rapid alternative, empirical validation regarding its reliability on urban secondary collector roads remains limited. This study aims to empirically validate the effectiveness of this Google Maps-based peak hour estimation method. Primary traffic data were gathered through direct field observations over a 3-hour window (comprising 1 hour before, during, and 1 hour after the predicted peak) across six two-lane two-way undivided (2/2 UD) urban secondary collector road segments in Semarang, Indonesia. Statistical t-tests and exploratory data analysis were employed to evaluate the alignment between empirical observations and Google Maps secondary data. Results reveal no statistically significant difference between empirical peak times and Google Maps \"Popular Times\" predictions, with observed time discrepancies ranging from -60 to +50 minutes. Consequently, this Google Maps-based methodology serves as a valid and efficient alternative for urban traffic counting survey. A 3-hour observation window encompassing pre-peak, peak, and post-peak periods is recommended for application. }, issn = {25496778}, pages = {13--22} doi = {10.14710/mkts.v32i1.79549}, url = {https://ejournal.undip.ac.id/index.php/mkts/article/view/79549} }
Refworks Citation Data :
Conventional traffic volume surveys used to identify peak hours require extensive data collection periods, often taking up to 84 days. Although Narendra (2022) proposed leveraging the Google Maps "Popular Times" feature as a rapid alternative, empirical validation regarding its reliability on urban secondary collector roads remains limited. This study aims to empirically validate the effectiveness of this Google Maps-based peak hour estimation method. Primary traffic data were gathered through direct field observations over a 3-hour window (comprising 1 hour before, during, and 1 hour after the predicted peak) across six two-lane two-way undivided (2/2 UD) urban secondary collector road segments in Semarang, Indonesia. Statistical t-tests and exploratory data analysis were employed to evaluate the alignment between empirical observations and Google Maps secondary data. Results reveal no statistically significant difference between empirical peak times and Google Maps "Popular Times" predictions, with observed time discrepancies ranging from -60 to +50 minutes. Consequently, this Google Maps-based methodology serves as a valid and efficient alternative for urban traffic counting survey. A 3-hour observation window encompassing pre-peak, peak, and post-peak periods is recommended for application.
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Last update: 2026-10-01 04:10:15