The reasonable placement of the advance guide signs (AGSs) is important in improving driving efficiency and safety when exiting an expressway. By analysing the lane-changing process when approaching an exit on new two-way eight-lane expressways, we modified the tradi-tional AGS model lane-change distance formula. To this end, a field experiment was designed to explore the lane-change traversal time at the free flow condition (LOS 1). Considering the limitations of the experimental equip-ment, lane change distance at the worst levels of service was explored using VISSIM simulation. The results show that the eight-lane changing distance based on modified theoretical calculations, revealed a minor difference with VISSIM simulation in free flow condition. Further-more, placement distance at the worst levels of service are discussed. Then placement distance of all-level AGSs is recommended to be 3 km, 2 km, 1.2 km, and 0.8 km, considering the driver's short-term memory attenuation calculation formula. Determining the two-way eight-lane AGS placement distance from the perspective of LOS can provide a basis on which to supplement the existing stan-dards and references for the AGS placement distance af-ter the expressway expansion in China.
For the purpose of reducing the harm of expressway traffic accidents and improving the accuracy of traffic accident black spots identification, this paper proposes a method for black spots identification of expressway accidents based on road unit secondary division and empirical Bayes method. Based on the modelling ideas of expressway accident prediction models in HSM (Highway Safety Manual), an expressway accident prediction model is established as a prior distribution and combined with empirical Bayes method safety estimation to obtain a Bayes posterior estimate. The posterior estimated value is substituted into the quality control method to obtain the black spots identification threshold. Finally, combining the Xi'an-Baoji expressway related data and using the method proposed in this paper, a case study of Xibao Expressway is carried out, and sections 9, 19, and 25 of Xibao Expressway are identified as black spots. The results show that the method of secondary segmentation based on dynamic clustering can objectively describe the concentration and dispersion of accident spots on the expressway, and the proposed black point recognition method based on empirical Bayes method can accurately identify accident black spots. The research results of this paper can provide a basis for decision-making of expressway management departments, take targeted safety improvement measures.
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