Technology acceptance comparison between on-road dynamic message sign and on-board human machine interface for connected vehicle-based variable speed limit in fog area

Connected vehicle-based variable speed limit (CV-VSL) systems in fog area use multi-source detection data to indicate drivers to make uniform change in speed when low visibility conditions suddenly occur. The purpose of the speed limit is to make the driver's driving behavior more consistent, so as to improve traffic safety and relieve traffic congestion. The on-road dynamic message sign (DMS) and on-board human–machine interface (HMI) are two types of warning technologies for CV-VSL systems. This study aims to analyze drivers’ acceptance of the two types of warning technologies in fog area and its influencing factors.

This study developed DMS and on-board HMI for the CV-VSL system in fog area on a driving simulator. The DMS and on-board HMI provided the driver with weather and speed limit information. In all, 38 participants participated in the experiment and completed questionnaires on drivers’ basic information, perceived usefulness and ease of use of the CV-VSL systems. Technology acceptance model (TAM) was developed to evaluate the drivers’ acceptance of CV-VSL systems. A variance analysis method was used to study the influencing factors of drivers’ acceptance including drivers’ characteristics, technology types and fog density.

The results showed that drivers’ acceptance of on-road DMS was significantly higher than that of on-board HMI. The fog density had no significant effect on drivers’ acceptance of on-road DMS or on-board HMI. Drivers’ gender, age, driving year and driving personality were associated with the acceptance of the two CV-VSL technologies differently. This study is beneficial to the functional improvement of on-road DMS, on-board HMI and their market prospects.

Previous studies have been conducted to evaluate the effectiveness of CV-VSL systems. However, there were rare studies focused on the drivers’ attitude toward using which was also called as acceptance of the CV-VSL systems. Therefore, this research calculated the drivers’ acceptance of two normally used CV-VSL systems including on-road DMS and on-board HMI using TAM. Furthermore, variance analysis was conducted to explore whether the factors such as drivers’ characteristics (gender, age, driving year and driving personality), technology types and fog density affected the drivers’ acceptance of the CV-VSL systems.