Abstract
Lane-changing in undersea tunnels has a negative impact on the normal traffic flow, and even lays hidden dangers for the occurrence of traffic accidents. Lane-changing behavior in undersea tunnels was divided into free, compulsory, and collaborative lane-changing types according to the characteristics of traffic flow to explore lane-changing risk in undersea tunnels. A fuzzy inference analysis on the three lane-changing behaviors was conducted on the basis of the behavior characteristics of fuzzy uncertainty of drivers. The most representative influencing variables, including speed difference, initial space of vehicles, traffic density, and distance for minimum lane-changing, were selected as fuzzy input variables, and lane-changing risk was used as an output variable to construct fuzzy rules for different lane-changing behavior. Risks of the three lane-changing behaviors were simulated by MATLAB/Simulink. Results demonstrated that the compulsory lane-changing in undersea tunnel was the riskiest, followed by collaborative and free lane-changing. Slope considerably influenced lane-changing risk. Specifically, the lane-changing risk at the downhill section was the highest, and the lane-changing risk at the uphill section was the lowest. The lane-changing risk at the flat section was between them.
Highlights
Undersea tunnel is a large traffic infrastructure for solving traffic interruption between the two sides of straits and bays
The influencing factors of traffic safety in undersea tunnels are explored, and this exploration is important in preventing traffic accidents
Different lane-changing behavior models in an undersea tunnel were constructed on the basis of fuzzy inference
Summary
Undersea tunnel is a large traffic infrastructure for solving traffic interruption between the two sides of straits and bays. Different lane-changing behavior models in an undersea tunnel were constructed on the basis of fuzzy inference. A new method for recognizing the risk degree of lane-changing behaviors in an undersea tunnel under different slopes was provided by constructing a model based on fuzzy inference. No vehicles are allowed to change lanes or overtake other cars under normal driving conditions in undersea tunnels due to their V-shaped physical structure and large traffic flow. B. LANE-CHANGING BEHAVIORAL CHARACTERISTICS Relevant traffic laws state that vehicles are prohibited to change lanes or overtake other cars in an undersea. The psychological conditions for safe lane-changing mean that the driver estimates that the current traffic environment supports safe lane-changing In this process, the lanechanging behavior of the driver experiences four programs, namely, perception, impulsion, judgment, and operation [19].
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