Truck traffic speed prediction under the extreme weather conditions

What is it about?

Truck speed prediction plays a key role in truck transportation management. However, it is a very challenging task since the truck traffic usually shows complex patterns. Most of the existing traffic prediction methods lack the ability to model the dynamic spatial-temporal correlations of truck traffic or ignore contributing contextual factors that impact traffic. Also, truck traffic data is typically sparse and noisy, which makes truck speed prediction an even more challenging task. How to improve the truck speed prediction by taking advantage of other relevant truck traffic information (such as the truck flow) has not been investigated in depth.

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Photo by Seb Creativo on Unsplash

Photo by Seb Creativo on Unsplash

Why is it important?

Truck speed prediction plays a key role in truck transportation management. There are distinct characteristics between the speed patterns of trucks and passenger cars. The passenger car speed, for example, shows clear patterns of morning and evening peaks, and the car volume in rush hours is usually busier than at night, while truck traffic does not necessarily follow these patterns. Additionally, even the best plans can be disrupted by extreme weather conditions, especially when it causes adverse driving conditions and road closures. Snowstorms, ice, fog, and floods can cause truck driving conditions to be extremely difficult and dangerous. Developing a highly effective model for truck traffic prediction under extreme weather conditions thus is crucial in truck transportation management.