Research and design of simulation and verification system of intelligent expressway based on ETC big data

Electronic toll collection (ETC) system records a large number of travel trajectories of vehicles on expressways, and it has a great potential application value. However, the current simulation system mainly focuses on simulating the characteristics of traffic flow while ignoring the real-time flow conditions of the road is difficult to calculate and display quantitatively, and the overall optimization cost is also notably substantial. Currently, there is a lack of a simulation system tailored for the ETC environment, which addresses the challenge of real-time traffic flow computation and holistic optimization, fulfilling the requisites of pertinent research. According to the topological structure inherent to an actual provincial road network on expressways, this paper devises a framework for a simulation system that conforms to the current ETC environment. We solved the critical problem of generating simulation data in the simulation system by establishing a Feature Extraction Algorithm for spatio-temporal features derived from ETC transaction data (Edata). Then we put forward Traffic Control Strategy Algorithm in ETC simulation system, which can provide decision indicators for simulating the control of traffic flow of the expressway. At the same time, we optimized the improved Multi-Task Scheduling Algorithm (ETC_MTS) based on the application scenario of real-time parallelism of multi-task on expressways, which provides better execution performance compared with the current mainstream algorithms such as Shortest Job First Scheduling Algorithm (SJFS), Priority Scheduling Algorithm (Priority), First Come First Serve Scheduling Algorithm (FCFS) and Round Robin Scheduling Algorithm (RR).