http://yetl.yabesh.ir/yetl1/handle/yetl/19017 2026-04-21T14:14:16Z http://yetl.yabesh.ir/yetl1/handle/yetl/4296071 Prediction Model for Traffic Flow with Missing Values Based on Generative Adversarial and Graph Convolutional Networks Jian-zhong Chen; Ze-kai Lü; Hao-meng Lin In order to improve the accuracy of urban road network traffic-flow prediction with missing values, the generator and discriminator of the generative adversarial network were reconstructed, the loss function was improved, and the traffic generative adversarial imputation network (TGAIN) was proposed for the completion of the missing data in traffic flow. Based on empirical mode decomposition (EMD), graph convolutional networks (GCN), and gated recurrent unit (GRU), the EMD-GCN-GRU model was designed for urban road network traffic-flow prediction. First, the traffic-flow data was processed using empirical mode decomposition and each component of the same level was reconstructed as the input of the subsequent prediction model. Then, the graph convolutional networks were used to learn the road network topology to capture the spatial characteristics of the traffic flow, and the gated recurrent unit was employed to capture the temporal characteristic of traffic flow. For the road network traffic-flow data with missing values, TGAIN was used to complete the data, and then the EMD-GCN-GRU was used to predict the traffic flow. The Shenzhen average vehicle speed data set was used to construct a variety of typical traffic-flow data with different missing patterns and different missing rates to simulate the actual missing situation. The effectiveness of the method was verified on the ModelArts development platform. The results show that compared with the commonly used matrix factorization imputation method, the TGAIN model has higher completion accuracy in the random missing mode of the data set and has better completion performance when the nonrandom missing rate is lower than 50%. Compared with seven other prediction algorithms, the proposed prediction method has higher prediction accuracy. Combining the data imputation method TGAIN with the traffic-flow prediction method EMD-GCN-GRU for urban road network traffic-flow prediction with missing values can significantly reduce the negative impact of missing data and data noise on traffic-flow prediction and capture the spatial and temporal correlation of network traffic flow, which improves the accuracy of urban road network traffic-flow prediction. 2023-01-01T00:00:00Z http://yetl.yabesh.ir/yetl1/handle/yetl/4296070 Optimal Warning Distance for Expressway Construction Area under Mixed Traffic Flow Rui Yuan; Ning Chen; Yao Tong; Jian-lin Jia; Yan-yan Chen To alleviate the sharp decline in traffic efficiency caused by the reduced number of lanes or the presence of obstacles and reduce the risk of accidents due to frequent lane changes or acceleration and deceleration in an expressway operation area, taking the Wufengshan north–south 4-lane river crossing channel in Jiangsu Province as the research environment, the related research on the typical operation area of expressway was conducted. A comprehensive indicator system for efficiency, safety, and fuel consumption in an expressway operation area was constructed. Based on Vissim simulation software, considering different traffic volumes, assembly rates, and warning distance conditions, the road scenario and warning model were created. The optimal warning distance for vehicles under different conditions in an expressway operation area was studied using a Bayesian neural network for prediction. The result shows that the average relative errors of this method for predicting the comprehensive safety and energy consumption indicators of an expressway operation area are 0.4%, 0.4% and 0.2% respectively. Through the analysis of the optimal warning distance for comprehensive efficiency, safety, and energy consumption indicators, it was concluded that (1) higher assembly rates lead to better results in all the three indicators, and the optimal warning distance becomes shorter; (2) under free-flow condition, the optimal warning distance is 300–800 m and it increases with the increase of traffic volume; (3) under saturated traffic-flow conditions, the optimal warning distance is 800–1,200 m, but the increase in traffic volume at this time has little influence on the warning distance; and (4) after traffic volume is oversaturated, the optimal warning distance is 1,200–1,800 m, and it continues to increase as the traffic volume increases. The research result can provide some reference for the safe driving of vehicles in an expressway operation area and the issuance of road warning by traffic management departments, and provide a method for predicting the optimal distance of vehicle warning in expressway operation areas. 2023-01-01T00:00:00Z http://yetl.yabesh.ir/yetl1/handle/yetl/4296069 Research on Asphalt Pavement Construction Temperature Control Model Based on Feedback and Control Theory Wei Si; Wei-jie Mao; Yan Shi; Duo Jie Ci Dan; Tian-jun Yang Based on data preprocessing, a digital analysis of the asphalt pavement construction process was conducted, and important construction processes and meteorological parameters affecting construction temperature were screened using the random forest (RF) algorithm. Based on the selected important parameters, the construction temperature prediction model was established using multilayer perception (MLP). Based on the feedback control theory, the control principle of the PID controller was analyzed, and a comprehensive and multistage temperature feedback control model was constructed in conjunction with the construction temperature prediction model. In order to solve the problem that the superparameter cannot be self-tuning, the genetic algorithm (GA) was used to optimize the feedback control model to make the model adaptive. The feedback control model’s construction process decision was compared and analyzed with the actual construction process parameters, and the robustness of the model’s feedback control results was evaluated to effectively adjust the construction process parameters and achieve precise control of the asphalt mixture’s construction temperature. The research results showed that the construction temperature prediction model could accurately predict the construction temperature. The comprehensive feedback control model could feedback control all parameters, while the multistage feedback control model could maintain the determined parameters and feedback control other parameters. In addition, the GA-PID feedback control model based on genetic algorithms had the performance of adaptive tuning of hyperparameters. Through analysis of the feedback control results, it was found that the construction process parameters obtained from the GA-PID feedback control model were evenly distributed within the effective range of actual process parameters, maintaining good consistency with the actual construction process parameters. The GA-PID control system had good robustness for different prediction models and different temperature control, and the proposed construction process decision was consistent with actual situations. 2023-01-01T00:00:00Z http://yetl.yabesh.ir/yetl1/handle/yetl/4296068 Exploration and Analysis on the Supervision System of Autopilot Taxis Rui Geng; Mi Zhou To support the commercial application of autonomous driving technology in taxis, and to solve the issues such as whether, what, and how to obtain transport operation qualifications for application subjects that have not been clearly defined by China, to avoid some cities not allowing intelligent connected vehicles to operate on charges due to the “lack of upper level legal support”, and to promote the current related transport operation management regulations to adapt to the management needs of the commercial operation and development of intelligent connected vehicles, the following 4 principles for the governance of autonomous passenger transport are proposed: (1) adhere to the principle of inclusiveness and prudence, and create a space for platform development; (2) adhere to the principle of full chain supervision and implement comprehensive supervision; (3) innovate regulatory concept and method to improve collaborative regulatory efficiency; and (4) respect the extension of existing institutional design, and fully consider new regulatory trends and requirements. It is proposed in the key regulatory system that it is recommended to adopt an administrative licensing approach for the admission system. The operating subjects allow multiple subjects to jointly apply and relies more on the self-regulation of the operating subjects. To explore a sandbox regulatory model for vehicle technology management and to ensure vehicle operational safety based on test and demonstration application results, practitioners are required to have the ability to be familiar with and master the autonomous driving technology system in their professional abilities, and reference can be made to the service quality requirements for cruiser and ride hailing drivers. The pricing mechanism is managed according to market adjustment prices and maintains a reasonable and relatively stable markup standard. To increase the coverage of carrier liability insurance and encourage the exploration of new types of insurance for the insurance mechanism, it is suggested to propose a regulatory system for autonomous driving taxis, to research and develop management measures for autonomous driving passenger transport services at the industry level, to establish a regulatory platform for autonomous driving passenger transport services, to strengthen interdepartmental regulatory cooperation, to promote third-party organization construction, to exert the self-discipline role of associations, and to timely revise relevant regulations on road passenger transport. 2023-01-01T00:00:00Z