## 4 On-Road Test Results  
To verify the effectiveness of the control strategy proposed in this article, vehicles located in an actual driving dataset of a continuous 9000 m on National Highway 236 were selected as the basis for simulation, as Figure 18 shows. The labels for the driving styles of the vehicles on this section were acquired by classifying the driving styles in the preceding section, and the simulation platform incorporated the actual speed and road conditions. The approach put forth in this paper (DS-MPC) should be contrasted with that of PID control in a system for fixed speed cruise control.  
Figures 19 and 20 display the speed tracking and corresponding error curves under real operating conditions. The results indicate that the control method proposed in this paper effectively tracks the speed changes of heavy trucks, maintaining a low deviation in speed. The average error is 0.03147 m/s, indicating an improvement of 80.56% over the accuracy of PID control. Furthermore, the standard deviation is 0.03210 m/s, indicating an improvement of 65.81% over the speed maintenance performance of PID control. Consequently, the proposed control method significantly enhances the power performance and road safety of the intelligent driving assistance system for heavy-duty trucks.  
Figure 21 shows the fuel consumption comparison results of vehicles using DS-MPC control and PID control on this road section. As shown in the figure, during continuous changes in road slope, the total fuel consumption of vehicles using DS-MPC control method was 319.111g, while the fuel consumption of vehicles using the traditional control method was 329.881, with an average fuel saving rate of 3.27%, which constitutes a good fuel saving effect. In addition, the fuel consumption using the DS-MPC control method varied slightly under different driving styles, which is consistent with the fuel consumption results of the simulation results. But the fuel saving effects varied under different driving styles, with aggressive driving styles having a more significant reduction in fuel consumption. This is because after the DS-MPC control method accurately identifies the driving style, the changes in throttle opening and brake pressure of the aggressive driving style are smoother than those of the PID control method, thus achieving higher fuel efficiency. In summary, heavy-duty vehicles using the DS-MPC control method have high fuel efficiency and will effectively reduce emissions.  
The elevation changes of the vehicle under actual operating conditions are depicted in Figure 22. To further illustrate the correlation between elevation changes and vehicle  
Figure 21: DS-MPC and PID fuel consumption under actual working conditions.  
Figure 20: DS-MPC and PID speed tracking error curve under actual working conditions.  
speed, Figure 23 presents typical slope sections along with their corresponding changes in vehicle speed. The proposed method outlined in this paper exhibits superior speed tracking performance on typical slope sections within the same road section. DS-MPC can enhance the precision of speed tracking during the deceleration process, thereby ensuring a uniform speed change. During the deceleration process, the vehicle has the ability to reach its predetermined target ahead of schedule and then enhance its acceleration. In comparison to PID control, it can achieve the desired vehicle speed in a shorter time. Furthermore, the DS-MPC algorithm is capable of effectively tracking the target speed during the deceleration phase, with a minimal overshoot and error, thereby achieving rapid tracking. It maintains good stability during the phase of increasing speed and further enhances the safety of road driving.