CAREER: Improving Bicycling Safety by Developing a Research Framework for Studying Driver-Bicyclist Interactions

职业：通过开发研究驾驶员与骑车人互动的研究框架来提高骑车安全

• 批准号: 2142757
• 负责人: Fred Feng
• 金额: $ 54.9万
• 依托单位: Regents of the University of Michigan - Dearborn
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-05-01 至 2027-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2142757&HistoricalAwards=false
• 关键词: CAREER; Improving; Bicycling; Safety; Developing

This Faculty Early Career Development (CAREER) award supports research to advance the safety of environmentally sustainable, active, and equitable mobility modes by exploring ways to improve bicycling safety. Bicycling has long been an important mobility mode for its environmental, health, and economic benefits. Nonetheless, bicycling is still largely underutilized in the U.S. The perceived danger of bicycling in motorized traffic has deterred many from considering it as a viable mobility option. This NSF grant will fill the knowledge gap to better understand how drivers and bicyclists interact with each other in the context of real-world roadway designs, and the key factors that shape their behaviors. The outcome of this research will support engineers and practitioners, city planners, and policymakers and legislators by providing data-driven insights to design safer road infrastructures, bicycle facilities, traffic laws and regulations, training and education programs, and safety technologies. The research activities are integrated with educational activities to foster local K-12 students' interests in STEM fields and train the next generation of scientists and engineers to work towards the urban future in which sustainable and active mobility will play a key role. The outreach to the local communities and dissemination of the online free educational materials on bicycling safety will promote active mobility modes to the general public nationwide.The main research questions of this project are (a) how do drivers and bicyclists interact with each other in the context of roadways designs, (b) what are the key factors and underlying mechanisms for driver-bicyclist crashes and conflicts, and (c) how can researchers systematically generate data-driven insights in active mobility safety research? To this end, this grant will develop a bicycling safety research framework that incorporates a variety of complementary methodologies and technologies, including (1) observational studies in real-world natural settings from complementary perspectives using naturalistic driving, cycling, and drone data; (2) laboratory experiments in a safe, controlled, and replicable environment using high-fidelity virtual reality cycling and driving simulators; (3) crash data analysis of bicyclist fatalities and injuries; and (4) computational modeling and simulation. A number of common and dangerous driver-bicyclist interaction types will be examined, including overtaking bicyclists and intersection-related conflicts. A wide range of factors involving driver and vehicle, bicyclist, and road infrastructure will be examined for their effects on bicycling safety measured by surrogate safety measures. This research also integrates many tools including big data, causal inference, human factors, virtual reality, lidar sensing, and computational human modeling. In addition, an open-source data repository of driver-bicyclist interactions will be developed to support the broader transportation research community.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该学院早期职业发展（CAREER）奖支持研究，通过探索提高骑自行车安全性的方法来促进环境可持续，积极和公平的移动模式的安全性。骑自行车长期以来一直是一种重要的交通方式，因为它具有环境，健康和经济效益。尽管如此，在美国骑自行车仍然在很大程度上未得到充分利用。在机动交通中骑自行车的危险性阻止了许多人将其视为一种可行的机动选择。这项NSF拨款将填补知识空白，以更好地了解驾驶员和骑自行车的人如何在现实世界的道路设计背景下相互作用，以及塑造他们行为的关键因素。这项研究的成果将通过提供数据驱动的见解来设计更安全的道路基础设施、自行车设施、交通法规、培训和教育计划以及安全技术，从而为工程师和从业人员、城市规划者、政策制定者和立法者提供支持。研究活动与教育活动相结合，以培养当地K-12学生对STEM领域的兴趣，并培养下一代科学家和工程师，以实现可持续和积极的流动性将发挥关键作用的城市未来。该项目的主要研究问题是：（a）在道路设计的背景下，驾驶员和骑自行车的人如何相互作用;（B）驾驶员-骑自行车的人碰撞和冲突的关键因素和潜在机制是什么;（b）驾驶员-骑自行车的人碰撞和冲突的关键因素和潜在机制是什么;（c）驾驶员-骑自行车的人碰撞和冲突的关键因素和潜在机制是什么;（d）驾驶员-骑自行车的人碰撞和冲突的关键因素和潜在机制是什么。以及（c）研究人员如何在主动移动安全研究中系统地产生数据驱动的见解？为此，该基金将开发一个自行车安全研究框架，该框架将结合各种互补的方法和技术，包括（1）使用自然驾驶，自行车和无人机数据从互补的角度在现实世界的自然环境中进行观察研究;（2）使用高保真虚拟现实自行车和驾驶模拟器在安全，受控和可复制的环境中进行实验室实验;（3）自行车死亡和受伤的碰撞数据分析;（4）计算建模和仿真。一些常见的和危险的驾驶员骑自行车的互动类型将被检查，包括超车骑自行车和交叉口相关的冲突。广泛的因素，涉及驾驶员和车辆，骑自行车的人，和道路基础设施将检查其对骑自行车安全的替代安全措施测量的影响。这项研究还集成了许多工具，包括大数据，因果推理，人为因素，虚拟现实，激光雷达传感和计算人体建模。此外，还将开发一个关于驾驶员与自行车者互动的开源数据库，以支持更广泛的交通研究社区。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

An Automatic Method to Extract Events of Drivers Overtaking Cyclists from Trajectory Data Captured by Drones

一种从无人机捕获的轨迹数据中提取驾驶员超越骑车人事件的自动方法

• DOI: 10.25368/2022.503
• 发表时间: 2022
• 期刊: The 10th International Cycling Safety Conference 2022
• 作者: Munnamgi, H. Vasanth;Feng, Fred
• 通讯作者: Feng, Fred