Modeling the Risks of Lane-Changing on Adjacent Sections of Tunnel Entrances.

The entrances of tunnels are generally considered to be accident-prone locations, and accidents related to this area mainly include rear-end and sideswipe crashes, which are also associated with lane-changing behaviours. Despite the extensive literature on the safety of lane-changing, little attention has been given to lane-changing behaviours in front of the tunnel entrance. To this end, this study investigates the contributing factors to the potential risk status of lane-changing, taking into account lane-changing scenarios and the distance to tunnel entrances. Vehicular trajectory data on adjacent sections of tunnel entrances was collected by naturalistic driving tests, and 615 lane-changing scenarios were extracted for analysis. Furthermore, lane-changing risk margin (LCRM) is proposed to estimate whether there is at potential risk during lane-changing. To verify the influence of risk factors on the safety of lane-changing on adjacent sections of tunnel entrances, a mixed logit model is established for different lane-changing scenarios and distance levels to tunnel entrances. The model estimation results indicate that the leading vehicles in the current lane and target lane (defined as CLV and TLV, respectively) significantly affect the risk of lane-changing, with the presence of CLV increasing the probability of performing risky lane-changing as approaching the tunnel entrance, while the presence of TLV instead reduces the probability of performing risky lane-changing behaviour. The distance to the tunnel entrance also has a significant impact on the risk of lane-changing, and the probability of the risk of lane-changing is higher at relatively close distances than at relatively long distances. Moreover, on adjacent sections of tunnel entrances, drivers mainly change lanes to the left, which is likely to be related to safer driving on the left. This implies that drivers approaching the tunnel may try to achieve better driving conditions before entering the tunnel by changing lanes in view of the complex driving conditions inside the tunnel.