loading
Documents

Research.Publish.Connect.

Paper

Author: Alwyn Hoffman

Affiliation: School of Electrical, Electronic and Computer Engineering, North-West University, Potchefstroom and South Africa

ISBN: 978-989-758-384-1

ISSN: 2184-2825

Keyword(s): Fuel Economy, Truck Driver, Performance Benchmarking, Generalized Regression Neural Network, Multilayer Perceptron.

Abstract: The transport industry is a primary contributor towards emissions that impact climate change. Fuel economy is also of critical importance to the profitability of road freight transport operators. Empirical evidence identified a variety of factors impacting fuel consumption, including route inclination, payload and truck driver behaviour. This creates the need for accurate fuel usage models and objective methods to distinguish the impact of drivers from other factors, in order to enable reliable driver performance assessment. We compiled a data set for 331 drivers completing 7332 trips over 21 routes to obtain evidence of the impact of route, payload and driver behaviour on fuel economy. We then extracted various regression and neural models for fuel economy and used these models to remove the impact of route inclination and payload, allowing the impact of driver performance to be measured more accurately. All models demonstrated significant out-of-sample predictive ability. Neural mod els in general outperformed regression models, while amongst neural models radial basis models slightly outperformed multi-layer perceptron models. The significance of compensating for factors not controlled by the driver was verified by demonstrating large differences in driver performance ranking before and after compensating for route inclination and payload. (More)

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.231.220.225

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Hoffman, A. (2019). Neural Models for Benchmarking of Truck Driver Fuel Economy Performance.In Proceedings of the 11th International Joint Conference on Computational Intelligence - Volume 1: NCTA, (IJCCI 2019) ISBN 978-989-758-384-1, ISSN 2184-2825, pages 379-390. DOI: 10.5220/0008065703790390

@conference{ncta19,
author={Alwyn J. Hoffman.},
title={Neural Models for Benchmarking of Truck Driver Fuel Economy Performance},
booktitle={Proceedings of the 11th International Joint Conference on Computational Intelligence - Volume 1: NCTA, (IJCCI 2019)},
year={2019},
pages={379-390},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008065703790390},
isbn={978-989-758-384-1},
}

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Computational Intelligence - Volume 1: NCTA, (IJCCI 2019)
TI - Neural Models for Benchmarking of Truck Driver Fuel Economy Performance
SN - 978-989-758-384-1
AU - Hoffman, A.
PY - 2019
SP - 379
EP - 390
DO - 10.5220/0008065703790390

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.