Designing an effective road network is essential for constructing a comprehensive training platform. The proposed design integrates various traffic elements, enhances the authenticity of road network simulations, saves construction space, maximizes the integrated role of the sand table, and improves the comprehensiveness of the platform. Based on a multitype road network structure, different types of traffic facilities can be laid, which can replicate intelligent transportation application scenes. Then, the road elements can be enriched according to the requirements of the sand table and the actual road scene. Diversified road network design of training platforms can better facilitate platform construction and intelligent transportation personnel training.

A diversified road network design scheme is proposed to address the current and future requirements for intelligent transportation and personnel training. This involves comparing and analyzing different design schemes using multidimensional characteristic evaluation indices. This paper evaluates existing sand table applications and proposes five road network design schemes to meet different application requirements: ① customization- based road network design, ② modularization-based road network design, ③ projection-based road network design, ④ electronic screen-based road network design, and ⑤ print-based road network design. Each scheme supports diverse application scenarios, such as teaching demonstrations, scientific research experiments, popular science exhibitions, and professional competitions.

This study analyzes the functional differences among the five proposed road network design schemes, evaluating them based on multidimensional characteristic evaluation indices. These indexes include function display degree, cost advantage, deployment convenience, display effect, intelligent vehicle applicability, secondary expansion, occupied area, practical operation, and service life. Each scheme is compared from technical perspectives, typical application scenarios, advantages and disadvantages, improvement directions, and development trends.

To adapt to the development of intelligent transportation and meet personnel training needs, this research proposes five road network design schemes. These schemes provide guidance and reference for designing and selecting road networks for practical teaching, scientific research, exhibitions, and other purposes. They enhance the simulation effect between simulation road networks and real-world road conditions, improve the application effectiveness of scientific research, practical training, and exhibitions, and facilitate the training of intelligent transportation talents. The results provide guidance and reference for cost control and functional design of road network design throughout the platform’s life cycle. By guiding the construction of high-quality practical training platforms, this study can support high-quality construction projects and efficient personnel training. It also has far-reaching implications for actively serving the current needs of intelligent and connected road traffic systems.

This paper aims to use active fine lane management methods to solve the problem of congestion in a weaving area and provide theoretical and technical support for traffic control under the environment of intelligent connected vehicles (ICVs) in the future.

By analyzing the traffic capacities and traffic behaviors of domestic and foreign weaving areas and combining them with field investigation, the paper proposes the active and fine lane management methods for ICVs to optimal driving behavior in a weaving area. The VISSIM simulation of traffic flow vehicle driving behavior in weaving areas of urban expressways was performed using research data. The influence of lane-changing in advance on the weaving area was evaluated and a conflict avoidance area was established in the weaving area. The active fine lane management methods applied to a weaving area were verified for different scenarios.

The results of the study indicate that ICVs complete their lane changes before they reach a weaving area, their time in the weaving area does not exceed the specified time and the delay of vehicles that pass through the weaving area decreases.

Based on the vehicle group behavior, this paper conducts a simulation study on the active traffic management control-oriented to ICVs. The research results can optimize the management of lanes, improve the traffic capacity of a weaving area and mitigate traffic congestion on expressways.

Heavy fog results in low visibility, which increases the probability and severity of traffic crashes, and fog warning system is conducive to the reduction of crashes by conveying warning messages to drivers. This paper aims at exploring the effects of dynamic message sign (DMS) of fog warning system on driver performance.

First, a testing platform was established based on driving simulator and driver performance data under DMS were collected. The experiment route was consisted of three different zones (i.e. warning zone, transition zone and heavy fog zone), and mean speed, mean acceleration, mean jerk in the whole zone, ending speed in the warning zone and transition zone, maximum deceleration rate and mean speed reduction proportion in the transition zone and heavy fog zone were selected. Next, the one-way analysis of variance was applied to test the significant difference between the metrics. Besides, drivers’ subjective perception was also considered.

The results indicated that DMS is beneficial to reduce speed before drivers enter the heavy fog zone. Besides, when drivers enter a heavy fog zone, DMS can reduce the tension of drivers and make drivers operate more smoothly.

This paper provides a comprehensive approach for evaluating the effectiveness of the warning system in adverse conditions based on the driving simulation test platform. The method can be extended to the evaluation of vehicle-to-infrastructure technology in other special scenarios.