Model for Calculating Average Vehicle Mileage for Different Vehicle Classes Based on Real Data: A Case Study of Croatia
Mileage data collected via surveys based on self-estimation, reports from garages and other sources which use estimations are rough estimates and differ greatly from the actual mileage. Vehicle mileage is a major factor in emission calculations and needs to be as accurate as possible to obtain relia...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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University of Zagreb, Faculty of Transport and Traffic Sciences
2019-04-01
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| Series: | Promet (Zagreb) |
| Subjects: | |
| Online Access: | https://traffic.fpz.hr/index.php/PROMTT/article/view/3043 |
| _version_ | 1818497485436354560 |
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| author | Goran Pejić Franjo Bijelić Goran Zovak Zoran Lulić |
| author_facet | Goran Pejić Franjo Bijelić Goran Zovak Zoran Lulić |
| author_sort | Goran Pejić |
| collection | DOAJ |
| description | Mileage data collected via surveys based on self-estimation, reports from garages and other sources which use estimations are rough estimates and differ greatly from the actual mileage. Vehicle mileage is a major factor in emission calculations and needs to be as accurate as possible to obtain reliable emission models. Odometer readings are collected annually at the periodic technical inspection in Croatia. Average mileage data were analyzed for vehicles up to 20 years of age in 2017. Vehicles were classified by curb weight and fuel type. Such classification proved to follow driver behavior and the intended purpose of the vehicle. For each vehicle class, the model was applied using the vehicle age and its population size as inputs for calculating average mileage. Real data shows that vehicles in Croatia considerably exceed the estimated mileage in the years following the first registration of the vehicle and that they cannot be compared to data collected in other studies based on estimations. The difference lies in the covered mileage after vehicles reach ten years of age. The outcome of this study has resulted in a model for calculating average vehicle mileage. The model is suitable for use in various analyses for Croatia or for countries with similar driving habits and economic status now and for years to come. |
| first_indexed | 2024-12-10T18:46:18Z |
| format | Article |
| id | doaj.art-baa997507bb84429b99cfd18baa19673 |
| institution | Directory Open Access Journal |
| issn | 0353-5320 1848-4069 |
| language | English |
| last_indexed | 2024-12-10T18:46:18Z |
| publishDate | 2019-04-01 |
| publisher | University of Zagreb, Faculty of Transport and Traffic Sciences |
| record_format | Article |
| series | Promet (Zagreb) |
| spelling | doaj.art-baa997507bb84429b99cfd18baa196732022-12-22T01:37:29ZengUniversity of Zagreb, Faculty of Transport and Traffic SciencesPromet (Zagreb)0353-53201848-40692019-04-0131221322210.7307/ptt.v31i2.30433043Model for Calculating Average Vehicle Mileage for Different Vehicle Classes Based on Real Data: A Case Study of CroatiaGoran Pejić0Franjo Bijelić1Goran Zovak2Zoran Lulić3Center for Vehicles of Croatia, Faculty of Mechanical Engineering and Naval Architecture (Zagreb)Center for Vehicles of Croatia, Faculty of Mechanical Engineering and Naval Architecture (Zagreb)Center for Vehicles of CroatiaFaculty of Mechanical Engineering and Naval Architecture (Zagreb)Mileage data collected via surveys based on self-estimation, reports from garages and other sources which use estimations are rough estimates and differ greatly from the actual mileage. Vehicle mileage is a major factor in emission calculations and needs to be as accurate as possible to obtain reliable emission models. Odometer readings are collected annually at the periodic technical inspection in Croatia. Average mileage data were analyzed for vehicles up to 20 years of age in 2017. Vehicles were classified by curb weight and fuel type. Such classification proved to follow driver behavior and the intended purpose of the vehicle. For each vehicle class, the model was applied using the vehicle age and its population size as inputs for calculating average mileage. Real data shows that vehicles in Croatia considerably exceed the estimated mileage in the years following the first registration of the vehicle and that they cannot be compared to data collected in other studies based on estimations. The difference lies in the covered mileage after vehicles reach ten years of age. The outcome of this study has resulted in a model for calculating average vehicle mileage. The model is suitable for use in various analyses for Croatia or for countries with similar driving habits and economic status now and for years to come.https://traffic.fpz.hr/index.php/PROMTT/article/view/3043average vehicle mileagemileage modelperiodic technical inspection |
| spellingShingle | Goran Pejić Franjo Bijelić Goran Zovak Zoran Lulić Model for Calculating Average Vehicle Mileage for Different Vehicle Classes Based on Real Data: A Case Study of Croatia Promet (Zagreb) average vehicle mileage mileage model periodic technical inspection |
| title | Model for Calculating Average Vehicle Mileage for Different Vehicle Classes Based on Real Data: A Case Study of Croatia |
| title_full | Model for Calculating Average Vehicle Mileage for Different Vehicle Classes Based on Real Data: A Case Study of Croatia |
| title_fullStr | Model for Calculating Average Vehicle Mileage for Different Vehicle Classes Based on Real Data: A Case Study of Croatia |
| title_full_unstemmed | Model for Calculating Average Vehicle Mileage for Different Vehicle Classes Based on Real Data: A Case Study of Croatia |
| title_short | Model for Calculating Average Vehicle Mileage for Different Vehicle Classes Based on Real Data: A Case Study of Croatia |
| title_sort | model for calculating average vehicle mileage for different vehicle classes based on real data a case study of croatia |
| topic | average vehicle mileage mileage model periodic technical inspection |
| url | https://traffic.fpz.hr/index.php/PROMTT/article/view/3043 |
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