Driver Reaction Time in an Internet of Vehicles Environment

摘要

To explore the characteristics of driver reaction time in an Internet of vehicles (IOV) environment, a vehicle-to-vehicle platform was established to perform real-world driving tests. The characteristics of the following driver's reaction time in an IOV were analyzed based on a Gaussian mixture model (GMM). By comparing fitted distribution models of the reaction times with the actual testing data in both traditional and networked vehicle environments, it was found that the GMM was superior to the normal distribution model and lognormal model in the IOV environment. The simple reaction time was reduced by 7.94%, the complex reaction time was reduced by 25.79%, and single lane basic traffic capacity was improved by 15.39% in the IOV environment. Furthermore, the population standard deviation of the driver's reaction time was reduced by 32.99% and grew more concentrated. The effects of speed on reaction time were not significant in the IOV environment.