Travel-time prediction model of ready-mixed concrete trucks for improving transportation efficiency
Ready-mixed concrete transportation planning is regarded as a core aspect of the construction industry, for which the key success factor is its effective time management. Travel time is the primary indicator of increased efficiency in advanced delivery scheduling. Therefore, this study aims to creat...
| Published in: | Engineering and Applied Science Research |
|---|---|
| Main Authors: | , |
| Format: | Article |
| Language: | English |
| Published: |
Khon Kaen University
2023-11-01
|
| Subjects: | |
| Online Access: | https://ph01.tci-thaijo.org/index.php/easr/article/view/250985/171468 |
| _version_ | 1852650899011272704 |
|---|---|
| author | Kittipong Thawongklang Ladda Tanwanichkul |
| author_facet | Kittipong Thawongklang Ladda Tanwanichkul |
| author_sort | Kittipong Thawongklang |
| collection | DOAJ |
| container_title | Engineering and Applied Science Research |
| description | Ready-mixed concrete transportation planning is regarded as a core aspect of the construction industry, for which the key success factor is its effective time management. Travel time is the primary indicator of increased efficiency in advanced delivery scheduling. Therefore, this study aims to create a travel-time prediction model for ready-mixed concrete business that have, insufficient knowledge of transportation, have recently started a business, or are expanding their factories to new locations. We prioritize the model calculation speed while the accuracy within acceptable ranges becomes secondary. Data were collected, -on the travel history of trucks within the area of the bypass ring road in, Udon Thani province, Thailand, from GPS devices installed in the trucks that transmitted signal every minute. Multiple linear regression (MLR) was selected for this model because it is reliable, widely accepted, and consistent with instant decisions made within business constraints. The obtained result was the optimal travel-time prediction model with confidence interval for an adjusted R2 of 81.35. The model was validated by using the remaining data, which demonstrate that RMSE was equal to 0.0868 hours or 5.208 minutes. |
| format | Article |
| id | doaj-art-e8967ffbd5fc4b9db9853dbbfe7ab99b |
| institution | Directory of Open Access Journals |
| issn | 2539-6161 2539-6218 |
| language | English |
| publishDate | 2023-11-01 |
| publisher | Khon Kaen University |
| record_format | Article |
| spelling | doaj-art-e8967ffbd5fc4b9db9853dbbfe7ab99b2025-08-19T21:41:11ZengKhon Kaen UniversityEngineering and Applied Science Research2539-61612539-62182023-11-01506619625Travel-time prediction model of ready-mixed concrete trucks for improving transportation efficiencyKittipong ThawongklangLadda TanwanichkulReady-mixed concrete transportation planning is regarded as a core aspect of the construction industry, for which the key success factor is its effective time management. Travel time is the primary indicator of increased efficiency in advanced delivery scheduling. Therefore, this study aims to create a travel-time prediction model for ready-mixed concrete business that have, insufficient knowledge of transportation, have recently started a business, or are expanding their factories to new locations. We prioritize the model calculation speed while the accuracy within acceptable ranges becomes secondary. Data were collected, -on the travel history of trucks within the area of the bypass ring road in, Udon Thani province, Thailand, from GPS devices installed in the trucks that transmitted signal every minute. Multiple linear regression (MLR) was selected for this model because it is reliable, widely accepted, and consistent with instant decisions made within business constraints. The obtained result was the optimal travel-time prediction model with confidence interval for an adjusted R2 of 81.35. The model was validated by using the remaining data, which demonstrate that RMSE was equal to 0.0868 hours or 5.208 minutes.https://ph01.tci-thaijo.org/index.php/easr/article/view/250985/171468travel time predictionmultiple linear regressionready-mixed-concrete truck |
| spellingShingle | Kittipong Thawongklang Ladda Tanwanichkul Travel-time prediction model of ready-mixed concrete trucks for improving transportation efficiency travel time prediction multiple linear regression ready-mixed-concrete truck |
| title | Travel-time prediction model of ready-mixed concrete trucks for improving transportation efficiency |
| title_full | Travel-time prediction model of ready-mixed concrete trucks for improving transportation efficiency |
| title_fullStr | Travel-time prediction model of ready-mixed concrete trucks for improving transportation efficiency |
| title_full_unstemmed | Travel-time prediction model of ready-mixed concrete trucks for improving transportation efficiency |
| title_short | Travel-time prediction model of ready-mixed concrete trucks for improving transportation efficiency |
| title_sort | travel time prediction model of ready mixed concrete trucks for improving transportation efficiency |
| topic | travel time prediction multiple linear regression ready-mixed-concrete truck |
| url | https://ph01.tci-thaijo.org/index.php/easr/article/view/250985/171468 |
| work_keys_str_mv | AT kittipongthawongklang traveltimepredictionmodelofreadymixedconcretetrucksforimprovingtransportationefficiency AT laddatanwanichkul traveltimepredictionmodelofreadymixedconcretetrucksforimprovingtransportationefficiency |
