A Review of Big Data in Road Freight Transport Modeling: Gaps and Potentials

Abstract

Road transport accounted for 20% of global total greenhouse gas emissions in 2020, of which 30% come from road freight transport (RFT). Modeling the modern challenges in RFT requires the integration of different freight modeling improvements in, e.g., traffic, demand, and energy modeling. Recent developments in 'Big Data' (i.e., vast quantities of structured and unstructured data) can provide useful information such as individual behaviors and activities in addition to aggregated patterns using conventional datasets. This paper summarizes the state of the art in analyzing Big Data sources concerning RFT by identifying key challenges and the current knowledge gaps. Various challenges, including organizational, privacy, technical expertise, and legal challenges, hinder the access and utilization of Big Data for RFT applications. We note that the environment for sharing data is still in its infancy. Improving access and use of Big Data will require political support to ensure all involved parties that their data will be safe and contribute positively toward a common goal, such as a more sustainable economy. We identify promising areas for future opportunities and research, including data collection and preparation, data analytics and utilization, and applications to support decision-making.

Development of Big Data Analytics Technology on Sea Freight Operational Performance Using the Agile Model

“…BDA also faces various challenges that make it different from, among others, having a massive number of data points (big data volume, high dimensions), the presence of complex data (high data variations with different classes and types), and the presence of high uncertainty (Jović et al, 2019). This variety of formats presents challenges in data storage because one type of database may not be optimal for storing and managing all types of data (Shoman et al, 2023). The agile model approach is software development that provides customer satisfaction through functionality that is developed quickly and demonstrated that can be implemented (Dharmapal & Sikamani, 2016).…”

“…Research has been carried out in developing BDA on Road Freight Transport (RFT) models which require the integration of different cargo modeling improvements, for example, traffic, demand and energy modeling so that they can provide useful information such as individual behavior and activity in addition to aggregate patterns using aggregates. conventional data (Shoman et al, 2023). In e-commerce companies, BDA is applied to distribute file systems and non-relational databases using Hadoop which is a distributed file storage system that can store large amounts of unstructured data and a parallel database system that can be compatible with all types of data (Shen, 2020).…”

Innovative Thermal Management Operating Strategies for Battery-Electric Heavy-Duty Trucks

“…Therefore, the battery systems suitable for a heavy-duty truck must be much larger compared to that of a lightduty vehicle. Second there is a lack of fast charging stations, especially MW -Chargers [9], for trucks along the main transport routes resulting in longer stop times compared to conventionally powered vehicles. Third, electric trucks are still much more expensive than conventional trucks [10] and their diesel engines are already optimized on efficiency [2].…”