Drivers'fixation transfer characteristics in urban tunnels

To improve the safety performance of urban tunnels,the fixation transfer characteristics of drivers with different driving experience levels in urban tunnels were investigated.First,a real vehicle test was performed in an urban tunnel,and the eye movement data of 10 drivers with different driving experience levels were collected using a Dikablis eye-tracking system.Second,the driver fixation range was divided into eight areas of visual interest by using the K-means clustering method,and the fixations in different sections of the tunnel were comparatively analyzed.Finally,on the basis of the divided areas of visual interest,fixation transfer rules and the stationary distribution characteristics of drivers with different driving experience levels on different sections of the tunnel were discussed using Markov theory.Results indicate that drivers'probability of repeated fixation is greater and that the efficiency of visual search is lower at internal sections of tunnels than in external sections.Drivers obtain information mainly from the straight upper front and straight lower front areas,and the probabilities of fixation points in these two areas at the threshold and exit sections are significantly higher than those in other sections.Relative to experienced drivers,novice drivers allocate little attention to the straight upper front area and rear-view mirrors.Hence,they have weak fixation when looking forward,and they lack experience in obtaining information on rear-approaching vehicles and controlling speed.

Dynamical Interaction Between Information and Disease Spreading in Populations of Moving Agents

Considering dynamical disease spreading network consisting of moving individuals,a new double-layer network is constructed,one where the information dissemination process takes place and the other where the dynamics of disease spreading evolves.On the basis of Markov chains theory,a new model characterizing the coupled dynamics between information dissemination and disease spreading in populations of moving agents is established and corresponding state probability equations are formulated to describe the probability in each state of every node at each moment.Monte Carlo simulations are performed to characterize the interaction process between information and disease spreading and investigate factors that influence spreading dynamics.Simulation results show that the increasing of information transmission rate can reduce the scale of disease spreading in some degree.Shortening infection period and strengthening consciousness for self-protection by decreasing individual’s scope of activity both can effectively reduce the final refractory density for the disease but have less effect on the information dissemination.In addition,the increasing of vaccination rate or decreasing of long-range travel can also reduce the scale of disease spreading.