Space Based Longitudinal Car Following Safety Field Model for Vehicles and its Auxiliary Decision-Making and Traffic System Self-Regulation Methods

Abstract

Using the car following model safety distance and mathematical methods, based on the concept of driving risk field, space occupation, and human factor initiative, a complete new traffic safety field model has been successfully established. It also has the ability to self adjust based on speed, and explores the quantitative reflection of road risk based on the safety distance that represents various complex traffic environment factors, as well as the adaptive ability of the model to this safety distance and its complex traffic environment. Use Matlab to simulate, validate, and improve the model. This model can assist human drivers in driving vehicles, optimize transportation systems, enhance their adaptive and self regulating capabilities, guide the movement of connected autonomous vehicles, and ensure safety to a certain extent in the event of unexpected network interruptions. Therefore, this model has great application prospects, especially in the current context of the development of intelligent transportation systems and autonomous driving in the transportation field. This longitudinal model can also be extended to various directions and all things, reflecting the traffic environment in detail. In other words, leveraging the widely applicable properties of the potential field model can also generate stronger effectiveness.