On February 2019, the paper titled “Verification of the HDM-4 fuel consumption model using a Big data approach: A UK case study” by Federico Perrota (ESR13), his supervisors Tony Parry and Luis Neves from UNOTT, and collaborators Thomas Buckland and Emma Benbow from TRL, and Mohammad Mesgarpourd from Microlise, was published in Transportation Research Part D: Transport and Environment. The latter falls within the top quartile of journal publications in the civil and structural engineering subject. The paper can be downloaded at the DOI link of the publisher’s website provided with the full reference below.
Abstract:
This paper presents an assessment of the accuracy of the HDM-4 fuel consumption model calibrated for the United Kingdom and evaluates the need for further calibration of the model. The study focuses on HGVs and compares estimates made by HDM-4 to measurements from a large fleet of vehicles driving on motorways in England. The data was obtained from the telematic database of truck fleet managers (SAE J1939) and includes three types of HGVs: light, medium and heavy trucks. Some 19,991 records from 1645 trucks are available in total. These represent records of trucks driving at constant speed along part of the M1 and the M18, two motorways in England.
These conditions have been simulated in HDM-4 by computing fuel consumption for each truck type driving at a constant speed of 85 km/h on a flat and straight road segment in good condition.
Estimates are compared to real measurements under two separate sets of assumptions. First, the HDM-4 model calibrated for the UK has been used. Then, the model was updated to take into account vehicle weight and frontal area specific to the considered vehicles.
The paper shows that the current calibration of HDM-4 for the United Kingdom already requires recalibration. The quality of the model estimates can be improved significantly by updating vehicle weight and frontal area in HDM-4. The use of HGV fleet and network condition data as described in this paper provides an opportunity to verify HDM-4 continuously.
Keywords: HDM-4Fuel consumption; calibration; telematic data; big data
Comparison of HDM-4 estimates with measured fuel consumption distributions for heavy trucks
Transportation Research D: Transport and Environment (ISSN: 1361-9209), from Elsevier, publishes original research and review articles on the environmental impacts of transportation, policy responses to those impacts, and their implications for the design, planning, and management of transportation systems. It covers all aspects of the interaction between transportation and the environment, from localized to global impacts. All impacts are considered, including impacts on travel behavior, air quality, ecosystems, global climate, public health, land use, economic development, and quality of life. According to scimagojr, the journal has the following impact indicators:
