Driving Risk Assessment Based on High-frequency, High-resolution Telematics Data
| 项目名称： | Driving Risk Assessment Based on High-frequency, High-resolution Telematics Data |
| 摘要： | The emerging connected vehicle and Automated Driving System (ADS) as well as widely available advanced in-vehicle telematics data collection/transmitting systems produce gigantic amount of high-frequency, high-resolution driving data. These telematics data provide comprehensive information on driving style, driving environment, road condition, and vehicle condition. The telematics data has been used for a number of safety areas such as insurance pricing, teenage driving risk evaluation, and fleet safety management. The surge of ride-hailing service in the last decade provides a novel alternative mode for travelers. The ride-hailing drivers are a unique driver population with substantial operational responsibilities and the safety management is critical for the drivers. The smartphone ride-hailing app can conveniently collect kinematic information from sensors on smartphones, thus make the telematics data available for the entire driver population. Parallel to this proposed study, the research team has evaluated telematics feature in prediction crash risk for millions of ride-hailing drivers. This project will address the following main safety research questions using high-frequency, high resolution telematics data: 1) characterize the high-frequency kinematic signatures for safety critical events as well as during normal operations; 2) develop models to predict high risk drivers based on the kinematics signatures. 3) develop models to distinguish and predict crashes from normal driving scenarios based on the high frequency data. The project will contribute to connected vehicles and ADS real-time safety monitoring, NDS data analysis, hail-driving driver safety prediction, as well as fleet and driver safety management programs. |
| 状态： | Active |
| 资金： | $150,000 |
| 资助组织： | Office of the Assistant Secretary for Research and Technology |
| 项目负责人： | Glenn, Eric Zachary |
| 执行机构： | Virginia Tech Transportation Institute |
| 开始时间： | 20191215 |
| 预计完成日期： | 20210830 |
| 主题领域： | Safety and Human Factors |
相关文献
- High-Resolution Micro Traffic Data from Roadside LiDAR Sensors for Connected-Vehicles and New Traffic Applications
- Modeling Naturalistic Driving Environment with High-Resolution Trajectory Data
- Investigating Relationship Between Driving Patterns and Traffic Safety Using Smartphones Based Mobile Sensor Data
- Exploration and Evaluation of High-Resolution Imagery for Environmental Assessment
- Adaption of Drone Measurement Techniques to Roundabouts and Innovative Intersections
- Embracing Emerging Internet-based Traffic Big Data in Smart City Applications to Improve Transportation Systems Efficiency, Safety, and Equity
检索历史
应用推荐
