Vehicle to Infrastructure (V2I) and Vehicle to Vehicle (V2V) passenger and freight vehicle applications to enhance safety and efficiency in coastal evacuations
| 项目名称： | Vehicle to Infrastructure (V2I) and Vehicle to Vehicle (V2V) passenger and freight vehicle applications to enhance safety and efficiency in coastal evacuations |
| 摘要： | Cooperative Forward Collision Warning alerts drivers of risk of frontal collisions, including head-on and rear-end collisions with vehicles ahead [1]. This system, which uses cameras and radars to detect collision threats, is a valuable V2I and V2V technology that can enhance both system efficiency and safety. It has been theorized that such technologies could be particularly valuable to enhance transportation system resilience in coastal regions, both for evacuations and for response and recovery. During evacuations transportation network efficiency is vital to reduce the evacuation time and minimize potential loss of life. Prior research has quantified the benefits of Connected and Automated Vehicle (CAV) technology supported by V2I and V2V communications ([4]; [5]). Unfortunately, this prior work was limited in that it used microsimulation analysis and associated assumptions, ignoring driver behavioral factors. The research proposed in this study seeks to address this limitation by using a driving simulator to assess and understanding how drivers interact with V2V and V2I advisories during emergency evacuation scenarios. The study will employ a full-scale driving simulation to create environments within which drivers’ acceptance/responses to V2V warnings and V2I warnings will be observed. Multiple scenarios that include a range of adverse weather (e.g., heavy rain, wind etc.) and warning types (e.g., V2V and V2I) will be examined. As there are also many factors (such as gender, age, warning types, etc.) which also influence driver behavior, a factorial design will be employed to create test scenarios with interaction between multiple stimulus conditions. Driver performance indicators will include acceleration and deceleration, average speed, braking behavior, lane change maneuver, time-to-collision etc. in routine and emergency conditions |
| 状态： | Active |
| 资金： | 138778 |
| 资助组织： | Office of the Assistant Secretary for Research and Technology |
| 管理组织： | Maritime Transportation Research and Education Center |
| 执行机构： | Louisiana State University |
| 主要研究人员： | Hassan, Hany |
| 开始时间： | 20220801 |
| 预计完成日期： | 20230630 |
| 主题领域： | Data and Information Technology；Highways；Safety and Human Factors；Vehicles and Equipment |
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