Mesoscopic model of cycling trip energy expenditure based on operating modes
Cyclist physical exertion is largely ignored in quantitative travel analysis, partly due to a lack of appropriate tools. Microscopic models of second-by-second energy expenditure based on equations of motion are data intensive and cannot be applied to hypothetical routes (such as needed for route ch...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-12-01
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| Series: | Journal of Cycling and Micromobility Research |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2950105924000214 |
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| author | Fajar Ausri Alexander Bigazzi |
| author_facet | Fajar Ausri Alexander Bigazzi |
| author_sort | Fajar Ausri |
| collection | DOAJ |
| description | Cyclist physical exertion is largely ignored in quantitative travel analysis, partly due to a lack of appropriate tools. Microscopic models of second-by-second energy expenditure based on equations of motion are data intensive and cannot be applied to hypothetical routes (such as needed for route choice modelling). Macroscopic models of aggregate energy expenditure based on a fixed assumed energy intensity are insensitive to traveller, trip, and contextual factors that are relevant for behavioural research and policy analysis (such as bicycle type or trip purpose). Building on concepts from motor vehicle emissions analysis, this paper proposes a mesoscopic approach to model cycling trip energy expenditure based on the distribution of travel time across discrete states of motion (“operating modes”) for different classes of traveller and trip (“model segments”). We aim to answer two key questions for model implementation: 1) which variables most effectively classify trips into model segments and 2) what operating mode definition most consistently characterizes cycling energy expenditure within model segments? We also evaluate the precision of the mesoscopic model relative to cycling energy estimates from microscopic and macroscopic models. Applied to a dataset of naturalistic cycling trips in Vancouver, Canada, the proposed mesoscopic model with six model segments based on 3 segmenting variables (rider gender, electric-assist bicycle, and high or low speed tier) explains up to 28 % of the variance in trip-level energy estimates from the microscopic model (within around 35 W of the microscopic estimates, on average). Further research to develop cycling trip energy models for general application is discussed. |
| format | Article |
| id | doaj-art-d4a181f453704448be0c9f12e5fb9c57 |
| institution | OA Journals |
| issn | 2950-1059 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Cycling and Micromobility Research |
| spelling | doaj-art-d4a181f453704448be0c9f12e5fb9c572025-08-20T02:07:02ZengElsevierJournal of Cycling and Micromobility Research2950-10592024-12-01210003010.1016/j.jcmr.2024.100030Mesoscopic model of cycling trip energy expenditure based on operating modesFajar Ausri0Alexander Bigazzi1Department of Civil Engineering, The University of British Columbia, 2002 – 6250 Applied Science Lane, Vancouver V6T 1Z4, CanadaCorresponding author.; Department of Civil Engineering, The University of British Columbia, 2002 – 6250 Applied Science Lane, Vancouver V6T 1Z4, CanadaCyclist physical exertion is largely ignored in quantitative travel analysis, partly due to a lack of appropriate tools. Microscopic models of second-by-second energy expenditure based on equations of motion are data intensive and cannot be applied to hypothetical routes (such as needed for route choice modelling). Macroscopic models of aggregate energy expenditure based on a fixed assumed energy intensity are insensitive to traveller, trip, and contextual factors that are relevant for behavioural research and policy analysis (such as bicycle type or trip purpose). Building on concepts from motor vehicle emissions analysis, this paper proposes a mesoscopic approach to model cycling trip energy expenditure based on the distribution of travel time across discrete states of motion (“operating modes”) for different classes of traveller and trip (“model segments”). We aim to answer two key questions for model implementation: 1) which variables most effectively classify trips into model segments and 2) what operating mode definition most consistently characterizes cycling energy expenditure within model segments? We also evaluate the precision of the mesoscopic model relative to cycling energy estimates from microscopic and macroscopic models. Applied to a dataset of naturalistic cycling trips in Vancouver, Canada, the proposed mesoscopic model with six model segments based on 3 segmenting variables (rider gender, electric-assist bicycle, and high or low speed tier) explains up to 28 % of the variance in trip-level energy estimates from the microscopic model (within around 35 W of the microscopic estimates, on average). Further research to develop cycling trip energy models for general application is discussed.http://www.sciencedirect.com/science/article/pii/S2950105924000214CyclingBicyclesEnergy expenditureMesoscopic model |
| spellingShingle | Fajar Ausri Alexander Bigazzi Mesoscopic model of cycling trip energy expenditure based on operating modes Journal of Cycling and Micromobility Research Cycling Bicycles Energy expenditure Mesoscopic model |
| title | Mesoscopic model of cycling trip energy expenditure based on operating modes |
| title_full | Mesoscopic model of cycling trip energy expenditure based on operating modes |
| title_fullStr | Mesoscopic model of cycling trip energy expenditure based on operating modes |
| title_full_unstemmed | Mesoscopic model of cycling trip energy expenditure based on operating modes |
| title_short | Mesoscopic model of cycling trip energy expenditure based on operating modes |
| title_sort | mesoscopic model of cycling trip energy expenditure based on operating modes |
| topic | Cycling Bicycles Energy expenditure Mesoscopic model |
| url | http://www.sciencedirect.com/science/article/pii/S2950105924000214 |
| work_keys_str_mv | AT fajarausri mesoscopicmodelofcyclingtripenergyexpenditurebasedonoperatingmodes AT alexanderbigazzi mesoscopicmodelofcyclingtripenergyexpenditurebasedonoperatingmodes |