{"id":4922,"date":"2026-06-10T22:29:45","date_gmt":"2026-06-10T22:29:45","guid":{"rendered":"https:\/\/catlec.cl\/?p=4922"},"modified":"2026-09-22T18:58:33","modified_gmt":"2026-09-22T18:58:33","slug":"decoding-built-environment-impacts-on-freight-truck-speeds-through-spatial-regression-a-case-study-of-valparaiso-chile","status":"publish","type":"post","link":"https:\/\/catlec.cl\/en-us\/decoding-built-environment-impacts-on-freight-truck-speeds-through-spatial-regression-a-case-study-of-valparaiso-chile\/","title":{"rendered":"Decoding Built-Environment Impacts on Freight Truck Speeds Through Spatial Regression: A Case Study of Valpara\u00edso, Chile"},"content":{"rendered":"\n<p class=\"has-medium-font-size wp-block-paragraph\"><strong>Fecha:<\/strong> 01\/05\/2026<br><strong>Autores:<\/strong> Emilio Condori<sup>a<\/sup>, Marcel&nbsp;Favereau<sup>bc<\/sup><\/p>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\"><sup>a<\/sup> Universidad Andr\u00e9s Bello<\/p>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\"><sup>b<\/sup> Universidad de los Andes<\/p>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\"><sup>c<\/sup> <a href=\"https:\/\/catlec.cl\" data-type=\"link\" data-id=\"catlec.cl\">Centro Avanzado de Transporte, Log\u00edstica y Competitividad Econ\u00f3mica (CATLEC)<\/a><\/p>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\"><br><strong>Revista cient\u00edfica \/ editorial:<\/strong> Advanced Research in Technologies, Information, Innovation and Sustainability<br><\/p>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\"><strong>Abstract o breve resumen:<\/strong> La movilidad de carga en las ciudades portuarias latinoamericanas a menudo se ve limitada por la topograf\u00eda escarpada, los patrones irregulares de las calles y los usos mixtos del suelo que, en conjunto, reducen la velocidad de operaci\u00f3n de los camiones. Esta investigaci\u00f3n analiza c\u00f3mo el entorno construido influye en la velocidad de los camiones de carga en las ciudades portuarias, utilizando el caso de Valpara\u00edso, Chile. Integramos nueve meses de datos GPS de alta frecuencia de veh\u00edculos pesados \u200b\u200bcon t\u00e9cnicas de regresi\u00f3n espacial multiescala, en particular el modelo de Regresi\u00f3n Ponderada Geogr\u00e1fica Multiescala (MGWR). Los predictores urbanos incluyen la jerarqu\u00eda vial, el uso del suelo, la pendiente, la densidad de poblaci\u00f3n y la distancia a las terminales portuarias. El modelo MGWR supera tanto al m\u00e9todo tradicional de M\u00ednimos Cuadrados Ordinarios (OLS) como a la Regresi\u00f3n Ponderada Geogr\u00e1ficamente (GWR) de escala \u00fanica en todas las m\u00e9tricas de rendimiento. Alcanza valores de R2 ajustados entre 0,4816 (mayo) y 0,5854 (febrero), superando consistentemente a GWR (0,3026 a 0,4032) y OLS (m\u00e1ximo de 0,1889). En t\u00e9rminos del AICc, MGWR registra valores tan bajos como 637,2 (julio) y nunca supera los 732,3 (enero), en comparaci\u00f3n con OLS, que oscila entre 2321,4 y 2617,3. La variaci\u00f3n espacial de los coeficientes revela una marcada no estacionariedad: las v\u00edas de servicio y la distancia al puerto aumentan la velocidad de forma consistente, mientras que las calles residenciales y la densidad de poblaci\u00f3n ejercen efectos negativos en corredores clave. Estos hallazgos respaldan el desarrollo de pol\u00edticas de transporte de mercanc\u00edas dirigidas a nivel local. Este enfoque es transferible a otras ciudades portuarias que buscan equilibrar la eficiencia del transporte de mercanc\u00edas con la calidad de vida urbana.<\/p>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\"><strong>Enlace al documento o DOI:<\/strong> <a href=\"https:\/\/doi.org\/10.1007\/978-3-032-16764-4_17\"><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-vivid-cyan-blue-color\">https:\/\/doi.org\/10.1007\/978-3-032-16764-4_17<\/mark><\/a><\/p>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\"><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Fecha: 01\/05\/2026Autores: Emilio Condoria, Marcel&nbsp;Favereaubc a Universidad Andr\u00e9s Bello b Universidad de los Andes c Centro Avanzado de Transporte, Log\u00edstica<\/p>\n","protected":false},"author":6,"featured_media":4923,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[87,50],"tags":[151,152],"class_list":["post-4922","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-articulos-cientificos","category-publicaciones","tag-competitividad-logistica-nacional","tag-marcel-favereau"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.6 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Decoding Built-Environment Impacts on Freight Truck Speeds Through Spatial Regression: A Case Study of Valpara\u00edso, Chile - CATLEC<\/title>\n<meta name=\"description\" content=\"Estudio analiza c\u00f3mo el entorno urbano influye en la velocidad de camiones de carga en Valpara\u00edso mediante datos GPS y regresi\u00f3n espacial.\" \/>\n<meta name=\"robots\" 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