Abstract: Heavy mining trucks are key equipment in open-pit haulage systems, where the available roadway space is often narrow in relation to the vehicle’s size, resulting in extremely difficult driving. With the rapid advancement of mining intelligence, autonomous-driving technology has become an essential means of improving production efficiency to ensure operational safety and reduce operating costs. As a core component of autonomous-driving systems, path tracking control plays a decisive role in ensuring stable vehicle motion along a reference path. However, heavy mining trucks exhibit pronounced steering-mechanism constraints and significant signal transmission delays. Under the combined influence of sharp curves and long delays, path tracking systems tend to exhibit sluggish responses that rapidly increase tracking errors and even instability. Existing control methods struggle to simultaneously handle the compound effects of steering constraints and time delay, limiting their engineering applicability. To address the response lag caused by front-wheel steering-rate constraints in sharp-curve environments, a preview correct control (PCC) algorithm was developed by introducing the future heading of the reference path as preview information and incorporating the keypoint displacement error. The preview component improves steering proactiveness, while the correction component enhances responsiveness to current deviations to enable stable posture adjustments during curve entry, mid-curve, and exit. The PCC does not rely on complex models or high-performance computing platforms, making it suitable for the real-time operation of low-power onboard controllers. To address signal transmission delays in autonomous-driving systems, a multistep motion-compensation delay compensator is established by analyzing the PCC output structure and dynamic characteristics of a heavy mining truck to predict the vehicle’s posture evolution during the delay interval and generate new control inputs that counteract the delay effects. By integrating the PCC with the delay compensator, a path tracking control system capable of simultaneously handling steering mechanism constraints and long delays was achieved for heavy mining trucks. Simulations were conducted under no-load and full-load conditions, followed by full-load field experiments. In no-load simulations at 20 km·h⁻¹ on a U-shaped curve with a radius of 35 m, the PCC achieved a maximum displacement error of 0.0892 m, which is significantly more accurate than proportional-integral-derivative (PID) and preview PID and close to the nonlinear model predictive control (NMPC). Its average computation time was only 0.1514 ms, outperforming NMPC in terms of real-time capability. Under fully loaded conditions with a 0.4 s signal delay, the PCC combined with the delay compensator maintained the maximum displacement error within 0.1537 m, while the uncompensated PCC showed error divergence in sharp-curve sections. This demonstrates the critical role of the proposed compensation strategy in ensuring system stability under long-delay conditions. The compensator increased the average computation time by only 0.0982 ms, which had a negligible impact on real-time performance. Two sets of full-load field tests were conducted, with an actual signal delay of approximately 0.4 s. The maximum displacement errors were 0.1976 and 0.2073 m. In both tests, the vehicle navigated the sharp curve stably, without any loss of control or noticeable yaw deviations. Overall, the simulation and experimental results demonstrate that the proposed control system maintained a stable and reliable path tracking performance under significant steering-mechanism constraints and long signal delays, achieving a favorable balance between accuracy, real-time capability, and engineering deployability. Therefore, it is well suited for practical autonomous-driving applications in heavy mining trucks.