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Bicycle Trip Assignment: Energy Consumption as Travel Cost Variable Olena Tokmylenko MCRP candidate 2013 Clemson University.

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Presentation on theme: "Bicycle Trip Assignment: Energy Consumption as Travel Cost Variable Olena Tokmylenko MCRP candidate 2013 Clemson University."— Presentation transcript:

1 Bicycle Trip Assignment: Energy Consumption as Travel Cost Variable Olena Tokmylenko MCRP candidate 2013 Clemson University

2 Source: Los Angeles Bicycle Plan

3 What we think people experienceWhat people actually experience

4 Model Structure Optimal route Travel Time Energy Expenditure speed Physiological conditions athleticismgenderage distance slope riders mass wind resistance etc. power

5 Level of proficiency Group “A” Advanced or experienced Group “B” Basic or less confident Group “C” Children

6 Wingate Anaerobic Test Classification of Peak Power and Anaerobic Capacity for Female and Male NCAA Division I Collegiate Athletes

7 Human Power Aerobic Capacity vs Anaerobic capacity Functional Threshold Power Critical Power

8 Bicycling Power Where

9 Characteristics of five types of bicycle and rider Roadster (Utility) bicycle Sports bicycleRoad racing bicycle Frontage area, A (m²)0.50.40.33 1.210.9 Bicycle mass (kg)15119 Rider mass (kg)7775 0.0080.0040.003 7.2183.3742.471 0.3680.2450.182 Source: “Bicycling Science” David G. Wilson

10 Constant parameters Velocity, m/sRider’s Mass, kgSlope,%Headwind Velocity, m/s 5700 3 Velocity, mi/hRider’s Mass, lbSlope,%Headwind Velocity, mi/h ~ 11~1550~7 U.S. Measurement System Metric Measurement System

11 Bicycling Power

12 Types of bicyclists UtilitarianRecreational

13 Model Assumptions Utilitarian cyclists Different level of skills with a stress to average Decision is made and origins and destinations are known

14 Model Structure Optimal route Travel Time Energy Expenditure speed Physiological conditions athleticismgenderage distance slope riders mass wind resistance etc. power

15 Conclusion One of the most important factor that affect bicycling power expenditure can be addressed by planners while designing infrastructure The results of the model can minimize the cost of data collection and enrich behavior models The effective planning based on travel time and energy expenditure can provide better experience to the cyclists

16 Next Steps Propose classes of cyclist based on their power level Apply slope-speed-power relationship to the road network to determine travel time Measure energy expenditure of the riders Test the model on real city network

17 Questions? For questions or propositions contact : Olena Tokmylenko otokmyl@clemson.edu


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