Optimizing Vehicle Data Transmission for Accurate
Regional Temperature Mapping

Electrification in heavy transport is essential to reduce dependence on fossil fuels and decrease emissions. The transition also requires adapting transportation to maximize the driving range of the vehicles. Energy consumption is influenced by various driving conditions, such as traffic, outdoor temperature, and wind, which can vary significantly over time. This means that driving missions and planning need to be updated on the road, including e.g. which route to take, where and when to charge the battery.

Enhanced information processing and distributed decision-making have the potential to streamline transportation and increase the sustainability of the transport system. Modern trucks are connected, allowing information to be shared during trips that can be used to plan and adjust routes for a fleet of vehicles. The goal of this project is to use data from vehicles on the road to dynamically estimate road conditions that are important for route optimization for a fleet of electrified trucks. An important aspect is that communication capacity is limited, requiring that information is aggregated within the vehicle and only shared when necessary.