Model of Driver’s Eye Movement and ECG Index under Tunnel Environment Based on Spatiotemporal Data

Abstract

In order to improve the driver's physiological and psychological state, the driver's mental load which is caused by sight distance, lighting, and other factors in the tunnel environment should be quantified via modeling the spatiotemporal data. e experimental schemes have been scientifically designed based on methods of traffic engineering and human factor engineering, which aims to test the driver's spatiotemporal data of eye movement and ECG (electrocardiogram) index in the tunnel environment. Firstly, the changes in the driver's spatiotemporal data are analyzed to judge the changing trend of the driver's workload in the tunnel environment. e results show that the cubic spline interpolation function model can fit the dynamic changes of average pupil diameter and heart rate (HR) growth rate well, and the goodness of fit for the model group is above 0.95. So, tunnel environment makes the driver's typical physiological indicators fluctuate in the coordinates of time and space, which can be modeled and quantified. Secondly, in order to analyze the classification of tunnel risk level, a fusion model has been built based on the functions of average pupil diameter and HR growth rate. e tunnel environmental risk level has been divided into four levels via the fusion model, which can provide a guidance for the classification of tunnel risk level. Furthermore, the fusion model allows tunnel design and construction personnel to adopt different safety design measures for different risk levels, and this method can effectively improve the economy of tunnel operating safety design.

A Fissile Ripple Spreading Algorithm to Solve Time-Dependent Vehicle Routing Problem via Coevolutionary Path Optimization

“…A mathematical model of FRSA is formulated based on the CEPO technology, which makes use of the future traffic environment to implement path optimization. Due to the effects of traffic flow, network structure, and driver characteristics, some critical factors like timedependent traffic speeds, network topology, temporal congestion area evolution, different vehicle departure times, vehicle waiting behaviour, and network size are considered in the proposed model [47][48][49]. e objective of the proposed method is to minimize the sum of the delivery costs, such as travelling time and path length.…”

Method of Setting Exit Advance Guide Signs in Highway Tunnels Based on the Driver’s Eye Movement With Markov Chains

“…The distance sign was set on either the left or right side of the tunnel wall. According to the dynamic FOV theory [19,[46][47][48], when the driving speed is 80 km/h and the human head and eyeballs remain motionless, the driver's FOV is 58°; therefore, the longitudinal distances between the left and right tunnel walls and the vehicle were 6 m and 14 m, respectively. According to the research of ergonomic visual characteristics, the area 10° above and below the visual horizon is the best visual area of the human eye in the vertical direction.…”

A comparative driving safety study of mountainous expressway individual tunnel and tunnel group based on eye gaze behavior

“…Verwey [ 6 ] found that the closer to the tunnel a driver is, the lower the number of human gazes and the scanning range will be. Qi [ 7 ] and Yang [ 8 ] tested the driver’s eye movement data in the tunnel environment. Ye [ 9 ] conducted a driving simulation test, and the pupil diameter and the sight deviation time were analyzed.…”