EAGER: Connected and Automated Vehicle Assessment Platform Using a Crowdsourced Cyber-Physical Reality

这一早期概念实验研究补助金(AGER)项目将产生一个创新的评估平台，用于评估互联和自动化车辆(CAV)对个人(包括司机、乘客和行人)的影响。自21世纪初问世以来，CAV技术一直被认为将彻底改变车辆的控制方式，可能会对交通系统的安全和效率产生重大影响。现有的CAV评价方法严重依赖于计算机模拟，不足以捕捉对人类的影响，因为人类会对CAV产生各种认知和行为反应。缺少这一环节，骑兵就不能部署在路上。通过整合机器人、3-D打印、无线网络、交通传感和众包技术，将通过这个迫切的项目构建的评估平台将改革现有的依赖模拟的评估范式。将该平台与CAV相结合，可以在CAV的设计、开发和评估之间建立一个正反馈循环，从而使其能够在道路上部署。这项研究主要集中于评估CAV对以下个人的影响：1)骑车乘客，2)骑车附近的司机，或3)骑车周围的行人。为了无缝地捕捉他们的认知(如安全意识、舒适度)和行为反应(如转向动作、加速或减速活动)，该项目开发了一个新颖的评估平台，利用众包的网络物理现实来实现对Cavs的高保真评估。使用视觉和力反馈，可以通过网络物理现实来评估司机、乘客和行人的人类参与。这个迫切的项目将解决一些技术挑战，包括：1)如何确保平台的交通动态能够很好地反映真实世界的情况；2)如何通过虚拟现实将人类测试者与微型环境无缝连接；3)如何设计实验场景来研究CAV技术中的各种潜在问题。该项目将通过整合机器人、3D打印、交通工程和众包技术来应对挑战。该平台将通过将从所提出的平台收集的量化测量与理论预测的量化测量以及从真实世界的交通中采样的量化测量进行比较来验证。预计在项目结束时，将广泛进行和传播所建平台的演示。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This EArly-concept Grant for Experimental Research (EAGER) project will produce an innovative assessment platform for the evaluation of the impacts of Connected and Automated Vehicles (CAVs) on individuals including drivers, passengers and pedestrians. Since its inception in the early 2000s, CAV technology has been expected to revolutionize the way a vehicle is controlled, potentially having significant implications on safety and efficiency of transportation systems. Existing evaluation approaches for CAVs heavily rely on computer simulations, which are insufficient for capturing the impact on human beings who will have various cognitive and behavioral reactions in response to CAVs. Missing this link, CAVs cannot be deployed on the road. By integrating robotics, 3-D printing, wireless network, traffic sensing and crowdsourcing technologies, the assessment platform that will be built through this EAGER project will reform the existing evaluation paradigm relying on simulations. Combining this platform with CAVs can create a positive feedback loop between design, development, and assessment of CAVs and thus enable its on-road deployment. This research primarily focuses on the assessment of CAV impacts on the individuals who are 1) passengers of CAVs, 2) drivers in the vicinity of CAVs, or 3) pedestrians around CAVs. To seamlessly capture their cognitive (e.g., safety awareness, degree of comfort) and behavioral reactions (e.g., steering maneuvers, accelerating or decelerating activities), this project develops a novel assessment platform utilizing a crowdsourced cyber-physical reality to realize the high-fidelity evaluations of CAVs. Using visual and force feedback, human involvement as drivers, passengers, and pedestrians could be assessed through cyber-physical reality. This EAGER project will address a number of technical challenges including: 1) how to assure that the platform's traffic dynamics would well represent the real-world situations; 2) how to seamlessly connect the human testers with miniature environment through virtual reality; and 3) how to design experimental scenarios to investigate a wide variety of potential problems in CAV technologies. The project will tackle the challenges by integrating robotics, 3D-printing, traffic engineering, and crowdsource technologies. The platform will be validated by comparing the quantitative measures collected from the proposed platform with those predicted by theories and sampled from real world traffic. It is also expected that demonstrations of the built platform will be widely conducted and disseminated at the end of the project.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.