With the increasing number of elderly drivers and their growing driving demand, China has abolished the age limit for applying for small car driver’s license, and the travel safety of elderly drivers has become a hot research issue. Due to the biological and psychological decline related to driving behavior with aging, the elderly need to consider the impact of decreased physical function while maintaining mobility through self-regulation. Self-regulation is an effective compensation strategy for the elderly to prolong driving life and reduce driving risk. Based on the theory of planned behavior (TPB), this study introduced four extended variables, including physical condition, risk perception, driving skills and alternative traffic quality, to establish an extended TPB model and analyzed elderly drivers’ selfe-regulation behavior and its influencing factors. Cronbach’s α coefficient and confirmatory factor were used to verify the reliability and validity of the self-regulation behavior questionnaires collected from 849 elderly drivers, and path analysis was used to explore the factors influencing elderly drivers’ self-regulation behavior. The results show that the relationship among basic TPB variables is consistent with the assumptions of the basic model. Physical condition, alternative traffic quality, driving ability and risk perception all indirectly affect the self-regulation behavior of the elderly. The results are helpful to understand elderly drivers’ self-regulation behavior and influencing factors, and provide the theoretical basis for further research on elderly drivers’ driving behavior training and safety education.

In order to demonstrate the effectiveness of the warning system, this study explored the influence of the head up display warning system on driving behavior under different weather conditions in the connected environment for pedestrian crossing events. Firstly, this paper designed three warning systems: baseline, head down display (HDD), and head up display (HUD). Based on the driving simulation platform, it developed connected scenarios of urban roads under clear and foggy weather conditions and extracted driving behavior parameters through experimental testing. Then, from the micro level, the paper described the whole spatial change process of driving behavior under the action of connected HUD warning system for pedestrian crossing events, analyzed the influence rules of the warning systems and weather conditions on driving behavior, and constructed the influence model of driving behavior including risk avoidance stage and recovery stage. Next, a comprehensive index system was proposed to reflect the safety level at the risk avoidance stage, the recovery level at the recovery stage and the stability level of the whole process, including the first braking distance, the minimum conflict distance, the recovery stabilization time, the recovery amount of velocity, the maximum deceleration and the maximum acceleration. Finally, it quantified the effects of different warning systems (Baseline/ HDD/ HUD), weather conditions (clear weather/ foggy weather) and the interaction between the two factors on driving behavior. Research shows that the connected HUD warning system for pedestrian crossing events has a significant effect on drivers’driving behavior in the risk avoidance and recovery stage, and it significantly improves the safety level of driving behavior in the risk avoidance stage. At the same time, it has a significant improvement effect on the recovery efficiency during the recovery stage, and also significantly affects the stability level of the operational characteristics throughout the whole process. The connected HUD warning system for pedestrian crossing events shows more obvious advantages under foggy conditions.

In order to improve traffic operation of freeway bridge sections in fog, this paper proposed a human factor-oriented operation risk active warning prevention and control strategy for bridges. This strategy integrates traditional traffic safety facilities with intelligent technologies such as risk warning, dynamic speed limits, and visual guidance. Through changes in prevention and control levels under different risk levels, the facility resources were fully utilized to achieve the goal of multi-level and differentiated prevention and control from static notification to dynamic guiding. However, it is not yet clear whether this process will improve the driving behavior and the safety and efficiency of traffic operation, so it is difficult to support the effective design and application of the prevention and control strategy. Therefore, E’dong Yangtze River Bridge was taken as an example to quantitatively evaluate the improvement effectiveness of the prevention and control strategy through driving simulation test and to verify its validity. The optimization and implementation is based on the fact that human factor needs are subjected to the prevention and control strategy, then it has a better effect in guiding the practical application. The improvement effectiveness evaluation of prevention and control strategy was realized through the improvement rate of each indicator from three aspects (psychological perception, safety effectiveness and traffic efficiency). The results show that the prevention and control strategy is helpful to improve driver’s confidence and alleviate tension; it can significantly improve the driver’s behavioral performance and traffic operation state and enhance the traffic efficiency and the safety of horizontal and longitudinal operation of vehicles; it has the strongest ability to improve safety effectiveness, especially at the longitudinal level; the higher brightness line-of-sight induction strategy is more conducive to improving the safety level and significantly increasing the traffic capacity. Compared with the low brightness condition, it may have a negative impact on the driver’s psychological feelings, but it is not obvious. When the visibility is 100 m on bridge, it is recommended that the flashing frequency of visual guidance technology is 0.5 Hz and the brightness is 3500 cd/m². The results provide the necessary theoretical basis for the practical application of prevention and control strategy on foggy bridges. The proposed solution and the analytical idea of its improvement effectiveness provide a reference for targeted prevention and management of risky sections.