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Heavy commercial vehicle drivers may frequently shift gears when they are running on long and downhill roads in mountainous area. In order to improve driving safety and fuel economy, it is necessary to predict the slope of the road ahead in real time and correct the driver's shift strategy in time. At present, the road slope estimation is mainly based on the real-time estimation of the road slope at the current position of the vehicle based on the vehicle driving information obtained by the sensors, but the road slope of the road section that the vehicle is about to reach has not been predicted. In this paper, based on the road slope information of the road section that the driver has driven through, combined with Geographic Information System (GIS) information and road design standards, the slope of the road section ahead is predicted.

The mountain roads are curved and complicated, with undulating terrain and large distance between charging stations. Compared with traditional powered vehicles, in addition to safety issues, pure electric vehicles also need to deal with the driving range issue. At present, the relevant researches on automobile driving in mountainous areas mainly focus on the driving safety of traditional fuel oil vehicles when going uphill and downhill, while there are few researches on the driving planning of pure electric commercial vehicles on curved slope road. This paper presents a speed planning method for pure electric commercial vehicles based on vehicle-road collaboration technology. First, establish the vehicle dynamics model, analyze the vehicle dynamics characteristics when passing the downhill curve, calculate the safe speed range of the vehicle when passing the downhill curve, and establish the safe speed model of the downhill curve.