Bicycle Trip Assignment: Understanding Energy Consumption for Travel Cost Optimization

Bicycle Trip Assignment:
Energy Consumption as Travel Cost Variable
Olena Tokmylenko
MCRP candidate 2013
Clemson University
 
Source: Los Angeles Bicycle Plan
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What we think people experience
What people actually experience
Model Structure
speed
Physiological
conditions
athleticism
gender
age
distance
slope
riders
mass
wind
resistance
etc.
power
Level of proficiency
Wingate Anaerobic Test Classification of Peak Power and Anaerobic
Capacity for Female and Male NCAA Division I Collegiate Athletes
Human Power
Aerobic Capacity vs Anaerobic capacity
Functional Threshold Power
Critical Power
Bicycling Power
 
Where 
Characteristics of five types of
bicycle and rider
Source: “Bicycling Science” David G. Wilson
Constant parameters
U.S. Measurement System
Metric Measurement System
Bicycling Power
Types of bicyclists
Utilitarian
Recreational
Model Assumptions
Utilitarian cyclists
Different level of skills with a stress to
average
Decision is made and origins and
destinations are known
Model Structure
speed
Physiological
conditions
athleticism
gender
age
distance
slope
riders
mass
wind
resistance
etc.
power
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
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
Questions?
 
For questions or propositions contact :
 Olena Tokmylenko
otokmyl@clemson.edu
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Analyzing the energy consumption as a variable for travel cost on bicycle trips using a model structure that includes factors like gender, age, athleticism, slope, mass, wind resistance, and more. The study also explores the impact of rider proficiency levels and physiological conditions on energy expenditure and travel time, aiming to determine the optimal route. Additionally, the research delves into the characteristics of different types of bicycles and riders, along with constant parameters like velocity, mass, slope, and headwind velocity.

  • Bicycle Trip
  • Energy Consumption
  • Travel Cost
  • Optimization
  • Rider Proficiency

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  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 experience What people actually experience

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

  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 1 (anaerobic = critical + Sustained Power work capacity ) power duration

  8. Bicycling Power = + + + 2 [ V ( ) ( )] W K V mg s C V w A w R Where

  9. Characteristics of five types of bicycle and rider Roadster (Utility) bicycle 0.5 1.2 15 77 0.008 Sports bicycle Road racing bicycle 0.33 0.9 9 75 0.003 Frontage area, A (m ) Drag coefficient, ?? Bicycle mass (kg) Rider mass (kg) Rolling resistance coefficient, ?? Force of rolling resistance, ??(N) Aerodynamic drag factor, ??(kg/m) 0.4 1 11 75 0.004 7.218 3.374 2.471 0.368 0.245 0.182 Source: Bicycling Science David G. Wilson

  10. Constant parameters Metric Measurement System Velocity, m/s Rider s Mass, kg Slope,% Headwind Velocity, m/s 5 70 0 3 U.S. Measurement System Velocity, mi/h Rider s Mass, lb Slope,% Headwind Velocity, mi/h ~ 11 ~155 0 ~7

  11. Bicycling Power 1400 1400 1200 1200 1000 1000 power, watt power, watt 800 800 600 600 400 400 200 200 0 0 1 2 3 4 5 6 velocity, m/s 7 8 9 10 11 12 13 14 15 50 55 60 65 70 75 80 85 90 95 100 105 110 115 120 mass, kg 1400 1400 1200 1200 1000 1000 power, watt power, watt 800 800 600 600 400 400 200 200 0 0 0 1 2 3 4 5 6 7 8 9 wind velocity, m/s slope

  12. Types of bicyclists Utilitarian Recreational

  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 gender age athleticism slope riders mass wind resistance Physiological conditions etc. distance speed power Energy Expenditure Travel Time Optimal route

  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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