Modeling faults among mountainous highway fatal crash-involved drivers with different route familiarity levels

Abstract

Objective

With the constrained topography and road geometry, adverse weather conditions and restricted roadway facilities, mountainous highway crash rates and fatality rates are much higher. Considering the potential influence of driver’s route familiarity level on driving behavior and fault assignment, this research investigates high- and low- route familiarity level drivers (HRF and LRF drivers) fault assignment in mountainous highway fatal crashes in Yunnan Province of China by examining factors of driver, crash/environment and pre-crash behaviors.

Methods

Yunnan Province is famous for its tourism, and tourism can also bring in many drivers with low-route familiarity levels. Spatial distance away from residence-based method is used for identifying route familiarity levels of the drivers in this study. We employed two separate binary logistic regression models to investigate the effects of the explanatory variables on the likelihoods that the HRF or LRF drivers were at fault in the mountainous highway fatal crashes.

Results

The results show that driver under alcohol influence, sharp turn, dawn/dusk and left turning are 4 common factors that significantly influence both HRF and LRF drivers’ fault assignments. Factors including driver age, driver seatbelt use, weather condition, road type, section type, lighting condition and pre-crash behaviors have different or opposite influences on HRF and LRF drivers’ fault assignments. HRF drivers are much easier to be distracted under the conditions that are without the need of extra attention. LRF drivers have much more difficulties in figuring out, responding to and making timely driving behavior adjustment to ensure their driving safety on the high-risk sections like tunnels, continuous long downhills and sharp turns. Street parking/backing and left turning of the LRF drivers are very serious problems on the mountainous highways in China.

Conclusions

There is a large difference of significant factors contributing to the fault assignment of HRF and LRF drivers in mountainous highway fatal crashes. Some more effective and targeted countermeasures are put forward for HRF and LRF drivers and transportation managers to improve mountainous highway traffic safety.

Keywords:

• Route familiarity level
• mountainous highway fatal crash
• fault assignment
• binary logistic regression model

Conflict of interest

The authors declare that there is no conflict of interests regarding the publication of this paper.

Additional information

Funding

This work was funded by the Talent Project from Guangdong Polytechnic Normal University (No. 99166030420 and No. 99166990174) and National Natural Science Foundation of China (Grant No. 52172345, 61863019).