Exploring the impact of road surface conditions on truck fleet fuel consumption through Big Data

QR Code

Exploring the impact of road surface conditions on truck fleet fuel consumption through Big Data

The thesis presents a novel approach for estimating the impact of road roughness and macro-texture on truck fleet fuel consumption based on Big Data. An extensive literature review was carried out to provide a comprehensive background for the study. Objectives of the study are defined as, primarily...

Full description

Bibliographic Details
Main Author:	Perrotta, Federico
Format:	Thesis (University of Nottingham only)
Language:	English
Published:	2019
Subjects:	road roughness; truck fleet; fuel consumption; Big Data
Online Access:	https://eprints.nottingham.ac.uk/56981/

Similar Items

A big data approach to assess the influence of road pavement condition on truck fleet fuel consumption
by: Perrotta, Federico, et al.
Published: (2017)

Using truck sensors for road pavement performance investigation
by: Perrotta, Federico, et al.
Published: (2017)

A machine learning approach for the estimation of fuel consumption related to road pavement rolling resistance for large fleets of trucks
by: Perrotta, Federico, et al.
Published: (2018)

Application of machine learning for fuel consumption modelling of trucks
by: Perrotta, Federico, et al.
Published: (2017)

Route level analysis of road pavement surface condition and truck fleet fuel consumption
by: Perrotta, Federico, et al.
Published: (2017)

Comparison of truck fuel consumption measurements with results of existing models and implications for road pavement LCA
by: Perrotta, Federico, et al.
Published: (2018)

A big data approach for investigating the performance of road infrastructure
by: Perrotta, Federico, et al.
Published: (2018)

Verification of the HDM-4 fuel consumption model using a Big data approach: a UK case study
by: Perrotta, Federico, et al.
Published: (2019)

Mine haul road design and management best practices for safe and cost-efficient truck haulage
by: Thompson, Roger
Published: (2010)

Computer aided analysis and design of mine transportation systems
by: Ashton, Andrew R.
Published: (1989)

Optimisation of a Mixed Truck Fleet Schedule through a MIP Model Considering a New Truck-Purchase Option
by: Fu, Z., et al.
Published: (2014)

Using coloured Petri nets to investigate fleet cannibalisation
by: Sheng, Jingyu, et al.
Published: (2015)

A stochastic fleet composition problem
by: Loxton, Ryan, et al.
Published: (2012)

Knowledge grid to facilitate knowledge sharing model in big data community
by: Hosseinioun, Sara
Published: (2022)

Factors affecting successful big data analytics implementation in public sector of Malaysia
by: Adrian, Cecilia
Published: (2019)

Local and global measures for measuring performance of big data analytics process
by: Ali, Ismail Mohamed
Published: (2019)

Generalised fleet maintenance modelling
by: Reyes Campaña, Héctor Rodrigo
Published: (2019)

Unstructured big data processing in cloud computing environment by using Amazon Elastic Map Reduce
by: Busu, Norzaharawani
Published: (2017)

Analysing truck position data to study roundabout accident risk
by: Kamla, Jwan Jameel Shekh Mohammed
Published: (2016)

A hierarchical coloured Petri net model of fleet maintenance with cannibalisation
by: Sheng, Jingyu, et al.
Published: (2017)

Intention to use big data technology in teaching among higher education educators in Yunnan, China
by: Wang, Qianhui
Published: (2022)

Factors influencing user intention towards big data technology adoptions in educational organizations
by: Harun, Noor Baizura
Published: (2021)

Energy consumption and pass-trough effect of fuel price in Malaysia
by: Poh, Paik Xuan
Published: (2015)

A framework for accelerated product innovation in a big data environment
by: Zhan, Yuanzhu
Published: (2017)

Robust spatial diagnostic method and parameter estimation for spatial big data regression model
by: Ali, Mohammed Baba
Published: (2022)

From Big data to Smart Data with the K-Nearest Neighbours algorithm
by: Triguero, Isaac, et al.
Published: (2016)

Managing mine road maintenance interventions using mine truck on-board data
by: Marais, W., et al.
Published: (2008)

Evolutionary undersampling for extremely imbalanced big data classification under apache spark
by: Triguero, Isaac, et al.
Published: (2016)

Detecting danger in roads: an immune-inspired technique to identify heavy goods vehicles incident hot spots
by: Figueredo, Grazziela P., et al.
Published: (2017)

Fuel consumption and pollutant emissions of spark ignition engines during cold-started drive cycles
by: Darnton, Nicholas Julian
Published: (1997)

A risk management system for sustainable fleet replacement
by: Ansaripoor, Amir, et al.
Published: (2014)

Indexing strategies of MapReduce for information retrieval in big data
by: Ramadhan, Mazen Farid Ebrahim
Published: (2016)

Using big data to make better decisions in the digital economy
by: Tan, Kim Hua, et al.
Published: (2017)

The fleets on the northern frontier of the Roman empire from the 1st to 3rd century
by: Rummel, Christoph
Published: (2008)

Zynga’s FarmVille, social games, and the ethics of big data mining
by: Willson, Michele, et al.
Published: (2015)

Unlocking the power of big data in new product development
by: Zhan, Yuanzhu, et al.
Published: (2016)

Test process optimisation through big data analysis
by: Kho, Xiang Juan
Published: (2023)

Proportion of nonsteroidal anti-inflammatory drug prescription in equine practice
by: Marco, Duz, et al.
Published: (2018)

Reducing weight and fuel consumption of civil aircraft by electromagnetic launch
by: Bertola, Luca, et al.
Published: (2017)

Using Big Data to manage safety-related risk in the upstream oil & gas industry: a research agenda
by: Tan, Kim Hua, et al.
Published: (2016)