| In the new era,the road traffic system of our country is developing rapidly,and the construction of transport infrastructure is accelerating,playing an important role in supporting economic and social development.But at the same time,traffic safety problems are still very prominent,especially the high accident rate caused by driver factors.The driver is the core element in the traffic system,and his workload overload leads to cognitive errors and driving performance impairment,which is an important cause of traffic accidents.Therefore,the relationship between driving workload and driving performance needs to be analyzed in depth,and then the driving risk assessment method needs to be explored.In this paper,we analyzed the relationship between driving workload and driving performance on the basis of driving workload loading experiments,and conduct research on highway driving risk assessment and early warning.The specific research contents are as follows:(1)The orthogonal experiment was designed by controlling driving environment factors such as horizontal curve radius,longitudinal slope gradient,traffic flow,and sign information.The scenario construction was conducted and subjects were recruited to conduct the experiment.The driving workload data were collected by NASA-TLX scale,the driving behavior data were collected by UC-win/Road software,and the DBSCAN clustering algorithm was applied to pre-process the experimental data.In view of the unclear influence of road environment factors on driving workload and driving performance,the ANOVA and the Pearson correlation analysis were applied to investigate the correlation between them.Based on the experimental data obtained from the simulated driving experiment,the ANOVA was applied to investigate the influence of each factor of the driving environment on driving workload and driving performance respectively.The Pearson correlation analysis was applied to determine the correlations between the driving environment factors and driving workload and driving performance.The analysis of the correlations between driving workload factors and driving performance factors was further conducted.The results of the study identify the driving environment factors that can have an impact on driving workload and driving performance,clarify the importance of the sign information and the horizontal curve radius on driving workload and driving performance,and also demonstrate the close correlation between the factors of driving workload and driving performance.This section lays the foundation for further research on the mechanism of the impact of driving workload on driving performance.(2)For the problem of the unclear mechanism of driving workload on driving performance,the SEM-based analysis of the relationship between driving workload and driving performance was conducted to solve the problem of missing a quantitative relationship model between them in typical complex scenarios of highways.Firstly,the influence factors of driving performance were deconstructed.Based on the preliminary exploration of the correlation between driving workload factors and driving performance factors,the confirmatory factor analysis was applied to realize the construction of driving workload and performance impairment measurement models,respectively.After that,constructed the structural model of the relationship between them.At last,completed the model revision,and analyzed their direct and indirect influence paths.The results of the study verified the importance of the influence of driving workload on driving performance.During high-speed driving,sign information has the greatest degree of influence on driving workload,the longitudinal slope gradient and driving workload have the greatest degree of influence on driving performance.The importance of the mediating effect of driving workload between the sign information and driving performance was also found.This section provides theoretical support for the construction of subsequent driving risk assessment methods.(3)In response to the lack of a quantitative description of the relationship between driving environment,driving workload,and driving performance in the evaluation method of driving risk,a comprehensive evaluation method based on fuzzy logic is proposed to realize an effective estimate of highway driving risk.The index set of the model is constructed based on the relationship model between driving workload and driving performance.Its evaluation sets are constructed by applying the k-means clustering algorithm,and its weight system is constructed by applying the entropy weight method.Finally,the construction of the highway driving risk evaluation model is completed based on the fuzzy comprehensive evaluation method,and the validity of the proposed method is verified by comparing the results with those of the TOPSIS model.This paper focuses on driving workload,uses simulated driving experiments and theoretical modeling methods to analyze the mechanism of driving workload on driving performance under typical scenarios of highways,and establishes a comprehensive evaluation method of highway driving risk considering driving workload.The research results can provide the theoretical basis for the research and engineering application of highway accident warning systems,and provide a reference for accident prevention. |
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