Big data and AI scheduling platforms have been widely implemented in the fields of mainline logistics and urban distribution. The system automatically matches the source of goods and transportation capacity based on real-time road conditions, order information, vehicle location, and loading and unloading cycles, and plans a reasonable transportation route.

Compared to traditional manual scheduling modes, digital scheduling can optimize the round-trip loading plan of vehicles and reduce the need for vehicles to travel without load. At the same time, the platform is equipped with vehicle dynamic monitoring function, which provides timely warnings for fatigue driving, speeding and other behaviors, balancing transportation efficiency and driving safety. Many small and medium-sized logistics enterprises are gradually integrating into lightweight scheduling systems to achieve digital upgrades in operations at lower costs.