Search

When the clear distance between the ramp and the longitudinal slope of the expressway is small, vehicles are easy to be affected by the diverging and merging when going up and down the slope, and the variation of speed is large, which is not conducive to driving safety. Based on the minimum clear distance between the ramp and the longitudinal slope, UC-Win /Road was used to establish the Inlet-uphill and downhill-exit section simulation model, and the experiment was carried out with Forum8 driving simulator and data were collected. The control variable method was used to adjust the characteristic indicators such as the mixing rate of large vehicles and the proportion of diverging and merging to study the real-time variation law of vehicle speed in longitudinal section. A velocity measurement model was built to quantify the relationship between the characteristic indicators and the velocity, and a single factor sensitivity analysis was conducted for the characteristic indicators. The results show that the change of ratio of diverging and merging and the mixing ratio of large vehicles have significant influence on the speed change, and the velocity magnitude and change trend of different vehicle types are quite different. The change of mixing ratio of large vehicles has a great influence on the running state of vehicles in the uphill section, while the change of diverging ratio has a great influence on the running state of vehicles in the downhill section. When the mixing ratio of large vehicles and the ratio of diverging and merging is 30%~40% and 10%~15% respectively, the velocity fluctuation is the largest and the sensitivity is strong. The research results can be used to provide a theoretical basis for vehicle operation management and improvement of safety measures when the clear distance between ramp and the longitudinal slope is small. [ABSTRACT FROM AUTHOR]

In order to explore the efficiency of drivers' visual recognition of traffic signs, an evaluation system of visual recognition efficiency of road signs in scenic spots was constructed. The field eye - tracking experiment was designed and data of drivers' visual recognition of traffic signs in scenic spots were collected. Based on the data variation rule and index characteristics, the optimal value and the critical value of the eye movement characteristic data were analyzed and the evaluation index set of traffic sign recognition efficiency was established. Then, support vector machine - recursive feature elimination was used to rank the significance of evaluation indexes to determine the degree of influence of each evaluation index on the evaluation system. In addition, the calibration index of efficacy coefficient method was adopted to establish the evaluation system of visual recognition efficiency. Finally, the system was used to evaluate the visual recognition in Nanjing Zhongshan Mountain National Park and some suggestions on improvement and optimization of traffic sign setting from the perspective of visual recognition efficiency were proposed. [ABSTRACT FROM AUTHOR]

The illumination of the entrance and exit sections of urban tunnels varies greatly,and the internal environment is monotonous,which has a significant impact on driving behavior. This paper intends to study the comprehensive risk factors of the driving behavior of the urban tunnel section in order to reduce the risk of driving behavior and improve the safety of urban tunnel traffic. The comprehensive risk of driving behavior in the urban tunnel section mainly comes from two aspects. The subjective risk refers to the drive’s own conditions such as the psychological load of the driver’s life,the driver’s risk cognition level,and the objective risk refers to road environmental conditions such as tunnel lighting conditions,road route shape,and traffic flow. In this paper,risk analysis and decision theory are introduced to model the risk degree function of the factors that make up the risk of driving behavior decision,and to explore the quantitative research method of comprehensive risk of driving behavior in urban tunnel section. Taking the basic data of three urban tunnels in a city as an example,the model is used to calculate the comprehensive risk value of driving behavior. The results show that the annual statistical accident number of tunnel B with higher comprehensive risk value of driving behavior is significantly higher than that of tunnel A and tunnel C. The accuracy and applicability of the model are verified. [ABSTRACT FROM AUTHOR]