Off-Ramp Vehicle Mandatory Lane-Changing Duration in Small Spacing Section of Tunnel-Interchange Section Based on Survival Analysis

Abstract

Due to topography, geology, and other factors, small spacing sections are common between tunnels and interchange exits. There is mandatory lane-changing behavior for vehicles that need to leave the main line and drive inside the road before leaving the tunnel. Affected by the “white hole” of a tunnel, the lane-changing behavior of off-ramp vehicles differs significantly from that of original roadbed sections. To study the mandatory lane-changing duration (MLCD) of off-ramp vehicles in small spacing sections of the tunnel to interchange in mountainous areas, their time and trajectory data were collected based on a driving simulator. According to the characteristics of the data, the survival analysis method was used to analyze the influence on the MLCD of off-ramp vehicles of the spacing section between the tunnel and interchange, vehicle types, tunnel types, ramp types, highway service level, and whether to set exit advance guide signs in the tunnel and the Cox proportional hazards model of the MLCD was established. The results showed that the spacing of the tunnel interchange, the road service level, and whether to set exit advance guide signs in the tunnel had significant effects on the MLCD of vehicles, while the vehicle, the tunnel, and the ramp types did not. When the spacing section of the tunnel interchange was less than 500 m, the off-ramp vehicle had continuous mandatory lane-changing behavior, and when the distance decreased from 400 m to 300 m, the risk rate of lane changing increased by 5.68 times. Survival function curve estimation provided the 75% quantile of MLCD of off-ramp vehicles under different conditions, which could provide a theoretical reference for setting the minimum distance between a tunnel and interchange exit.

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

“…Intriguingly, this threshold is consistent with findings from ergonomics and traffic conflict studies [2,48], exceeding the diverging influence areas length recommended by the HCM [47]. According to Shang's study, the rapid environmental transitions within a limited space and time can exacerbate drivers' anxiety and competitive pressure, detrimentally affecting driving safety [23].…”

“…In addition, drivers' gap selection during LC displays the highest correlation with TC, with a coefficient exceeding 0.6. Contrarily, TL does not exhibit significant correlations with other indicators, aligning with findings from prior research [23]. Following analyses will be carried out focusing on combinations of independent and dependent variables with correlation coefficients higher than 0.25 (the bold terms).…”

“…Fatema and Hassan [20] posit that the closer a vehicle is to the end of the auxiliary lane, the more likely the driver is to diverge. Moreover, factors like roadway design [21,22], traffic control facilities [23], traffic flow [24], and interaction with surrounding vehicles [25] significantly dictate driving characteristics in divergence areas.…”

Research on Efficient Operation for Compound Interchange in China from an Auxiliary Lanes Configuration Aspect

“…It is worth noting that this hazardous behavior tends to occur near exit ramps. In a section with a small spacing between the tunnel exit and the interchange exit, when the spacing is less than 500 m, there will be continuously forced lane-changing behavior in the exit section [27].…”

Study on the Evolution Mechanism of Lane Change Decision in Urban Expressway Diversion Area

“…It is found that the stable time of the game vehicle is longer in the smaller speed interval. Based on incomplete information game, Shang Ting [7] and others considered the safety payoff and speed payoff of both sides of the game based on different driving styles, established the forced lane change scenario at the exit of the tunnel, solved the perfect Bayesian Nash equilibrium as the lane change strategy, and found that the aggressive driver completed the forced lane change earlier than the cautious driver through Netlogo simulation. The model uses the value of patience to define the type of driver's aggressiveness and caution, and assigns the value of safety payoff and speed payoff, which has a certain degree of onesidedness.…”