Effect evaluation of traffic guidance in urban underground road diverging and merging areas: A simulator study

Yan-ni, Huang; Chen, Feng; Song, Mingtao; Pan, Xiaodong; You, Kesi

doi:10.1016/j.aap.2023.107036

Cited by 18 publications

(2 citation statements)

References 41 publications

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“…To explore the driver's speed perception mechanism, Zhang et al [25] designed a driving simulation experiment to collect the driver's perceived speed and the actual driving speed and analyze the influence of factors such as geometric alignment and sidewall change frequency on the driver's speed perception sensitivity. Huang et al [26] proposed four different integrated traffic guidance schemes and studied their effects on driver behavior through driving simulator experiments and questionnaires. However, driving simulation analysis for urban UIs is relatively lacking.…”

Section: Introductionmentioning

confidence: 99%

Vehicle Driving Safety of Underground Interchanges Using a Driving Simulator and Data Mining Analysis

Liu,

Yang,

Wang

et al. 2024

Infrastructures

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In the process of driving in an underground interchange, drivers are faced with many challenges, such as being in a closed space, visual changes alternating between light and dark conditions, complex road conditions in the confluence section, and dense signage, which directly affect the safety and comfort of drivers in an underground interchange. Thus, driving simulation, building information modeling (BIM), and data mining were used to analyze the impact of underground interchange safety facilities on driving safety and comfort. Acceleration disturbance and steering wheel comfort loss values were used to assist the comfort analysis. The CART algorithm, classification decision trees, and neural networks were used for data mining, which uses a dichotomous recursive partitioning technique where multiple layers of neurons are superimposed to fit and replace very complex nonlinear mapping relationships. Ten different scenarios were designed for comparison. Multiple linear regression combined with ANOVA was used to calculate the significance of the control variables for each scenario on the evaluation index. The results show that appropriately reducing the length of the deceleration section can improve driving comfort, setting reasonable reminder signs at the merge junction can improve driving safety, and an appropriate wall color can reduce speed oscillation. This study indicates that the placement of traffic safety facilities significantly influences the safety and comfort of driving in underground interchanges. This study may provide support for the optimization of the design of underground interchange construction and internal traffic safety facilities.

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Section: Introductionmentioning

confidence: 99%

Vehicle Driving Safety of Underground Interchanges Using a Driving Simulator and Data Mining Analysis

Liu,

Yang,

Wang

et al. 2024

Infrastructures

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show abstract

“…These sections, characterized by their small spacing and rapid environmental changes, often lead to complex traffic flow patterns and frequent vehicle interweaving. This unique environment critically affects two key driving behaviors: car-following (CF) and lane-changing (LC) [1]. Influenced by road infrastructure, the driving environment, and driver characteristics, these behaviors govern vehicles' longitudinal and lateral movements, thereby impacting traffic flow efficiency and safety [2][3][4].…”

Section: Introductionmentioning

confidence: 99%

Investigation of Car Following and Lane Changing Behavior in Diverging Areas of Tunnel-Interchange Connecting Sections Based on Driving Simulation

Sun,

Xu,

et al. 2024

Preprint

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Tunnel-interchange connecting sections pose significant safety challenges on mountainous expressways due to their high incidence of accidents. Improving road safety necessitates a comprehensive understanding of driver behavior in such areas. This study explores the influences of road characteristics, signage information volume, and traffic conditions on drivers' car-following and lane-changing behavior in tunnel-interchange diverging areas. Utilizing driving data from 25 subjects of 72 simulated road models, driving performance is assessed using Friedman rank test and multivariate variance analysis. The results highlight the significant influence of both connection distance and signage information load on driving behavior. In tunnel-interchange scenarios, the reduction of velocity increased by 62.61%, and speed variability surged by 61.11%, indicating potential adverse effects on driving stability due to the environmental transitions. Decreased connection distances are associated with reduced lane-changing durations, larger steering angles, and increased failure rates. Furthermore, every two units increase in signage information leads to a 13.16% rise in maximum deceleration and a 5% increase in time headway. Notably, the signage information volume shows a significant interaction with connection distance (F=1.60, P=0.045) for most car-following indicators. Hence, the study recommends a maximum connection distance of 700 m and signage information not exceeding nine units for optimal safety and stability.

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A comprehensive approach to evaluate human–machine conflicts in shared steering systems

Li,

Deng,

et al. 2024

Accident Analysis & Prevention

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Effect evaluation of traffic guidance in urban underground road diverging and merging areas: A simulator study

Cited by 18 publications

References 41 publications

Vehicle Driving Safety of Underground Interchanges Using a Driving Simulator and Data Mining Analysis

Vehicle Driving Safety of Underground Interchanges Using a Driving Simulator and Data Mining Analysis

Investigation of Car Following and Lane Changing Behavior in Diverging Areas of Tunnel-Interchange Connecting Sections Based on Driving Simulation

A comprehensive approach to evaluate human–machine conflicts in shared steering systems

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