CAREER: A Combined Experimental and Theoretical Study of Human-Connected Automated Vehicle Interactions
职业:人联网自动车辆交互的实验与理论相结合的研究
基本信息
- 批准号:2047937
- 负责人:
- 金额:$ 52.84万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2021
- 资助国家:美国
- 起止时间:2021-04-01 至 2026-03-31
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
This Faculty Early Career Development (CAREER) grant will contribute to the national economy and welfare by enhancing the transportation system efficiency and safety. This will be achieved through introducing a novel congestion management strategy based on vehicle automation and communications technology. The current automated vehicle development efforts mainly focus on the safety of isolated vehicles with little consideration of the impacts of design on human drivers and on transportation system efficiency. Such design approaches, in many cases, can potentially result in additional congestion and unforeseen safety issues for human drivers. Through careful characterization of the interactions between human drivers and connected automated vehicles (CAVs), this CAREER project will lead to new paradigms for congestion management and will result in more efficient utilization of our roadway system and a significant reduction in congestion throughout the transportation system. This grant will also result in the development of an online intelligent tutoring system that offers a systematic approach to teach students the skills and expertise required to function within highly diverse and dynamic work environments of the future. This customizable educational platform can be adopted by other disciplines and other universities across the nation. The findings of this study will be disseminated to a wide range of audiences through round table discussions, stakeholder meetings, and webinars.The research objective of this CAREER grant is to test the hypothesis that humans exhibit a different decision-making logic when interacting with CAVs in comparison with when interacting with other humans. This hypothesis will be evaluated using extensive field tests and data collection from human driver behavior in response to various CAV maneuvers. This project will also explore the potential for the evolution of human behavior in response to CAVs over time and will introduce robust models to capture such changes in human behavior. Utilizing the findings from the field experiments, this project will lead to the introduction of decentralized CAV-based traffic shaping methodologies that can maintain a desired traffic state by utilizing CAVs to influence the behavior of human drivers.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.
该教师早期职业发展(CAREER)补助金将通过提高运输系统的效率和安全性,为国民经济和福利做出贡献。这将通过引入基于车辆自动化和通信技术的新的拥堵管理策略来实现。目前的自动驾驶汽车开发工作主要集中在孤立车辆的安全性上,很少考虑设计对人类驾驶员和运输系统效率的影响。在许多情况下,这种设计方法可能会导致额外的拥堵和人类驾驶员无法预见的安全问题。通过仔细描述人类驾驶员和联网自动驾驶汽车(CAV)之间的交互,该CAREER项目将为拥堵管理带来新的范例,并将更有效地利用我们的道路系统,并显著减少整个交通系统的拥堵。这笔赠款还将导致开发一个在线智能辅导系统,该系统提供了一种系统的方法来教授学生在未来高度多样化和动态的工作环境中发挥作用所需的技能和专业知识。这个可定制的教育平台可以被全国其他学科和其他大学采用。本研究的结果将通过圆桌讨论、利益相关者会议和网络研讨会向广泛的受众传播。这项CAREER资助的研究目标是测试人类与CAV互动时与与其他人类互动时表现出不同的决策逻辑这一假设。这个假设将使用广泛的现场测试和数据收集从人类驾驶员的行为,以响应各种CAV机动进行评估。该项目还将探索随着时间的推移,人类行为对CAV的反应的演变潜力,并将引入强大的模型来捕捉人类行为的这种变化。该项目将利用现场实验的结果,引入基于CAV的分散式交通整形方法,通过利用CAV影响人类驾驶员的行为来维持理想的交通状态。该奖项反映了NSF的法定使命,通过使用基金会的智力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
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Alireza Talebpour其他文献
Privacy Risk of Connected Vehicles in Relation to Vehicle Tracking when Transmitting Basic Safety Message Type 1 Data
传输基本安全消息类型 1 数据时与车辆跟踪相关的联网车辆的隐私风险
- DOI:
10.1177/0361198119875433 - 发表时间:
2019 - 期刊:
- 影响因子:1.7
- 作者:
Mohammadreza Khajeh Hosseini;Alireza Talebpour;S. Shakkottai - 通讯作者:
S. Shakkottai
Lane-Changing Trajectory Optimization to Minimize Traffic Flow Disturbance in a Connected Automated Driving Environment
变道轨迹优化可最大限度地减少互联自动驾驶环境中的交通流干扰
- DOI:
- 发表时间:
2019 - 期刊:
- 影响因子:0
- 作者:
Gihyeob An;Alireza Talebpour - 通讯作者:
Alireza Talebpour
A Comfort-Based Vehicle Routing Methodology for Autonomous Vehicles
基于舒适度的自动驾驶车辆路线方法
- DOI:
10.1109/itsc57777.2023.10421831 - 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Chun;Gihyeob An;Jun Han Bae;Alireza Talebpour - 通讯作者:
Alireza Talebpour
Reverse engineering the way humans rank textures
- DOI:
10.1007/s10044-006-0054-6 - 发表时间:
2006-12-05 - 期刊:
- 影响因子:2.000
- 作者:
Maria Petrou;Alireza Talebpour;Alexander Kadyrov - 通讯作者:
Alexander Kadyrov
Modeling driver behavior in a connected environment: Integration of microscopic traffic simulation and telecommunication systems
- DOI:
- 发表时间:
2015 - 期刊:
- 影响因子:0
- 作者:
Alireza Talebpour - 通讯作者:
Alireza Talebpour
Alireza Talebpour的其他文献
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