Data supporting "Operational speed strategy opportunities for autonomous trucking on highways"
Citation
Bray, G., & Cebon, D. (2022). Data supporting "Operational speed strategy opportunities for autonomous trucking on highways" [Dataset]. https://doi.org/10.17863/CAM.81748
Description
Microsoft Excel spreadsheet containing data values for figures in paper including:
- Cumulative fuel consumption v time for sample reference 3. (Data acquired from fleet operator referred to in paper, simulated fuel consumption calculated using methodology described in paper)
- Instantaneous (rolling 5-second average) fuel consumption v time for sample reference 3. (Data acquired from fleet operator referred to in paper, simulated fuel consumption calculated using methodology described in paper)
- Summary of fuel consumption validation modelling. (Data acquired from fleet operator referred to in paper, simulated fuel consumption calculated using methodology described in paper)
- Sample highway drive-cycles (sourced from EPA, see reference in paper, and from fleet operator referred to in paper)
- Breakdown of fuel consumption rates (l/100km) by energy component for Tractor-trailer loaded to 50% cargo mass capacity (calculated using methodology described in paper)
- Combined driver and fuel cost £/100km under Drive cycle 1 conditions. (calculated using methodology described in paper)
- Combined cost v target speed for tractor-trailer, half load, Drive Cycle 1 (calculated using methodology described in paper)
- Combined cost for tractor trailer, half filled by mass, medium Vc, drive cycle 1 (calculated using methodology described in paper)
- Net savings (£/km) for human driver and AV resulting from reducing target speed from 90km/h to 80km/h and 70km/h. Vehicles loaded 50% to capacity by mass. (calculated using methodology described in paper)
- Savings in £/100km and % by scenario and speed strategy for HD and AV. (calculated using methodology described in paper)
- Allocation of case study distance travelled by road speed limit (sourced from fleet operator referred to in paper and calculated using methodology described in paper)
- Cargo value of time required to maintain baseline speed strategy £/tonne/hr (calculated using methodology described in paper)
- Distribution of in-use fleet time across the day (sourced from fleet operator referred to in paper)
- Slow speed strategy outcomes replicated for US context. Tractor trailer, load to 50% cargo capacity by mass. Drive cycle 1. No allowance for cargo value of time (calculated using methodology described in paper)
Format
Microsoft Excel
Keywords
heavy goods vehicles, autonomous trucks, driverless trucks, Freight Value of Transport Time, Highway speed strategy, Fuel consumption, CO2 emissions
Relationships
Publication Reference: https://doi.org/10.1016/j.tra.2022.01.014
Sponsorship
The Authors would like to acknowledge the support of Arup and the Centre for Sustainable Road Freight, which is funded by Industry Partners and UKRI under EPSRC Grant EP/R035199/1. The authors are grateful for input from Professor John Miles, Dr Gerard Casey, Dr Anil Madhusudhanan, Dr Xiaoxiang Na, Dr Daniel Ainalis, Mr Justin Laney, Mr Joshua Subel, Professor Alan McKinnon, Professor Phil Greening and Professor Gerard de Jong.
Identifiers
This record's DOI: https://doi.org/10.17863/CAM.81748
Rights
Attribution 4.0 International (CC BY 4.0)
Licence URL: https://creativecommons.org/licenses/by/4.0/
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