Abstract
Human-related factors are a crucial inducement of traffic accidents. Understanding the influence of freeway environments on the driving behavior and workload experienced by drivers has been demonstrated to be of primary importance for improving traffic safety. To study the effect of alignment, traffic flow, and sign information on drivers’ mental workload and behavior, 16 scenarios were constructed using the orthogonal design method, and simulated driving experiments were carried out with 45 participants. During driving, indicators such as the mean and standard deviation of vehicle speed and lane departure were collected, and the NASA-TLX questionnaire was adopted to measure workload. Analysis of variance results indicated that the radius of the horizontal curve, gradient, flow, and sign information level have a significant influence on drivers’ workload and speed keeping ability. In addition, the horizontal curve radius has a significant effect on lane keeping ability. The importance of safety influencing factors on driving workload and performance was quantitatively ranked by integrating the trend of Deng’s correlation degree, comprehensive correlation degree, and similar correlation degree, whose weight was calculated using the entropy method. Traffic sign information was found to have the greatest impact on workload. In terms of driving performance, traffic volume has the greatest influence on the mean and standard deviation of vehicle speed, followed by the amount of sign information. Lane departure is most affected by the radius of the horizontal curve. These findings provide guidance for freeway traffic safety regulation, including workload control and road facility optimization.
Highlights
Statistics of road traffic accidents show that 80% of accidents and 65% of dangerous driving conditions are directly or indirectly caused by human factors, and that the driver has no obvious illegal and subjective errors in 41% of these accidents [1]
Data Sequence and Dimensionless. e purpose of this study is to evaluate the effects of the horizontal curve radius, longitudinal slope, traffic flow, and sign information on driving workload and performance. erefore, in this paper, the subjective workload, the mean, and standard deviation of vehicle speed and lane offset are used as reference sequences {x0 (t)} (t 1, 2,...). e horizontal curve radius, longitudinal slope, traffic flow, and sign information are taken as comparison sequences, namely, {x1 (t)}, {x2 (t)}, {x3 (t)}, and {x4 (t)}
Results of Multivariate Analysis of Variance. e results of multivariate analysis of variance of the orthogonal test are listed in Table 1. e table shows that the radius of the horizontal curve had a significant effect on drivers’ workload, vehicle speed, and lane keeping ability (p < 0.001)
Summary
Statistics of road traffic accidents show that 80% of accidents and 65% of dangerous driving conditions are directly or indirectly caused by human factors, and that the driver has no obvious illegal and subjective errors in 41% of these accidents [1]. In 1988, John [2] proposed the concept of mental workload, known as mental load or cognitive load, and noted that the cognitive process of information will consume the memory resources of the brain and cause a certain workload. Extended to the field of transportation, driving workload is considered to be a measure of mental resources occupied by a series of activities related to driving tasks, such as receiving external stimuli, rapidly processing information and forming a clear judgment [3]. Mental workload can be defined as the ratio between the capacity of the information processing system needed to correctly perform the task and the amount of available attentional resources [4]. Mental workload is a multifaceted concept, and the measures available for the assessment of workload can be grouped into three categories: subjective, physiological, and performance.
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