Research On The Decision-making Optimization Of Highway Accident Black-spot Safety Improvement

With the rapid development of economy and urbanization, the system of road transport hasmade great progress in China. It played a significant role in the economic and socialdeveloppment, but also brought many negative effects. Many problems affect the level of roadsafety seriously, such as frequent traffic accidents, high motality rates, and trafficsafety-control capability is weak.It affect the level of people’s life and property under seriousthreat. Combining science and technology projects, the paper expanded research on thehighway accident blackspots safety improvement measures and accident black spotsimprovement decision-making optimization.Through the analysis of distribution and causes of highway accidents, the paper summarizedthe main reason of accidents is people. But the road alignment, weather, time and other factorsand driver behavior is closely related to traffic safety. By setting traffic safety facilities orimproving road alignment, it can effectively improve road safety standards.It is a prerequisite for the highway to minimize the accident rate that identifying the locationof accident black spots and improving and governing targetedly. Based on a highway inGuangdong Province as an example in this paper, we used the cumulative frequency curvemethod to identify the black spots. And we established an accident black spot treatmenturgency sorting model on the evaluation of road alignment safety, equivalent number ofaccidents and economic losses caused by the accidents. Then we sorted the black spotsaccording to their degree of harm. By govern the black spot with max urgency value, wecould improve safety level of road effectively. Then it provided a quantitative basis forimprovement decision-making optimization.According to analysis of the common causes of highway accident blackspots, factors such aspoor flat curve, poor vertical alignment, poor linear combination and tunnels, we madealternative suggestions for policy decision by offered lots of simple improvement measures.To meet the requirements of practical applications that may be encountered, this paperestablished an accident black spot improvement decision-making optimization model underthe unconstrained conditions and an accident black spot improvement decision-making optimization model under funding constraints condition. We established the first model on theevaluations such as economy, effectiveness, construction impacts and environmental. to helppolicymakers to choose the best suggestions. The main considerations under fundingconstraints are cost and effectiveness of measures, the use of dual-objective programmingmodel could help decision-makers under conditions of limited funds to choose the greatestbenefit blackspot and best treatment plan. The last examples demonstrated the practicality andfeasibility of the two models, and they could help decision-makers to govern decisions,reduce accident rate, improve road traffic safety effectively.