A cloud-based visualization tookit to support short-term driving behavioral pattern analysis in a V2X environment

Keywords: Connected Vehicle, V2X, visualization, transportation
Abstract Type: Paper Abstract

Abstract

The emerging connected vehicle (CV) technology is not only enabling the development and deployment of new applications related to road safety and management, but also dramatically reduce the number of fatalities and injuries due to accidents on roads and highways. For example, many CV applications have been developed in recent years, including the dedicated short-range communication (DSRC), vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and infrastructure-to-vehicle (I2V) technologies. Therefore, with the large amount of geospatial data collected through the CV technology, there is an opportunity to study driving behaviors and fully exploit the traffic-related data to guide safety operations and planning. This study aims to exploit the potential of using CVs data to build a visualization toolkit to support short-term driving behavioral pattern analysis in a V2X environment. This toolkit can support the analysis and visualization of CV data by (1) addressing the interaction of vehicles with partial trajectories; (2) integrating multi-source data based on contextual information; (3) providing visualization and analysis functions to address the deficiencies modeling with simulated data and support multi-scale analysis.