Planning a Shared Autonomous Vehicle Mobility Pilot for Linking Affordable Housing and Jobs

居住在城市负担得起的住房地区的中低收入居民，由于交通选择有限，包括缺乏公共交通系统，在获得工作或其他有机会的地点方面往往面临问题。由于根本问题通常是运营公共交通或其他类似出行选择的高昂成本，因此不可行，因此运营一支叫车和拼车自动驾驶车队是一个可行的解决方案，这些车辆还可以在像当前的新冠肺炎疫情这样的大流行病期间用于运送食物和补给。这种在过境沙漠中部署顺风车共享自动驾驶车辆(SAV)的方法将为居民提供按需、快速和负担得起的连接到工作地点的选择，使他们能够更快、更可靠地获得工作、服务和便利设施，否则在合理的出行时间内不会那么容易到达。该项目的更广泛影响是造福社会，并促进预期的社会结果，即改善智能城市中低收入社区的就业机会。该团队将从SAV的技术角度以及这项技术可以与社区合作并由社区塑造的社会科学维度来满足这些需求。该项目将来自多个学科的研究人员与社区合作伙伴聚集在一起，规划一个负担得起的创新移动解决方案，更好地将居民与工作、关键服务和便利设施连接起来。该项目计划的研究试点部署是在俄亥俄州马里斯维尔市使用SUV，为该市居民提供快速且负担得起的连接到他们工作地点的选择。SUV将是全电动汽车，采用最优路线算法，将减少出行时间和能源消耗。项目组将确定与马里斯维尔经济适用房对应的需求位置和与工作对应的目的地位置，确定SAV运营的地理围栏区域，计划与现有交通系统的集成以增加行程，分析现有交通数据，为选定的地理围栏区域构建SAV运营模拟环境，并利用该环境规划研究试点部署。项目组还将确定试点操作的供应商和方法。这个第一阶段规划项目的规划工作将被汇编成第二阶段的提案，并将包括第二阶段研究试点的计划以及如何评估它的成功。该项目是为响应公民创新挑战而资助的。A.社区和机动性：提供更好的机动性选项，以解决住房可负担性和工作之间的空间不匹配问题，这是NSF和能源部汽车技术办公室的合作项目。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。

Low-mid income residents living in affordable housing areas of a city are often faced with problems in accessing jobs or other locations of opportunity due to limited mobility choices including the lack of a public transportation system. Since the underlying problem is usually the high and therefore unfeasible cost of operating public transportation or other similar mobility options, operation of a fleet of ride hailing and ride-sharing autonomous vehicles that can also be used for the delivery of food and supplies during a pandemic like the current Covid-19 outbreak is proposed as a feasible solution. This approach of deploying ride Shared Autonomous Vehicles (SAV) in a transit desert will give residents an on-demand, fast and affordable option of connecting to their job locations, allowing them to have faster and reliable access to work, services and amenities that are otherwise not so easily accessible in reasonable travel periods. The broader impact of this project is to benefit society and advance the desired societal outcome of improving access to jobs from low-mid income neighborhoods in a smart city. The team will be addressing these needs from both the technological perspective of SAVs as well as from the social science dimension of this technology can both work with the community and be shaped by it.This project brings together researchers from several disciplines with community partners to plan an affordable, innovative mobility solution that better connects residents to work, critical services, and amenities. The research pilot deployment that will be planned in this project is the use of SAVs in the City of Marysville, Ohio to give its residents a fast and affordable option of connecting to their job locations. The SAVs will be fully electric vehicles with an optimal routing algorithm that will reduce their trip time and energy footprint. The project team will identify demand locations corresponding to affordable housing in Marysville and destination locations corresponding to jobs, determine the geo-fenced area of SAV operation, plan integration with the existing transportation systems for increasing trip range, analyze existing traffic data, build an SAV operation simulation environment for the chosen geo-fenced area and use it to plan a research pilot deployment. The project team will also identify vendors and methods for operation of the pilot. The planning work of this Stage 1 planning project will be compiled into a Stage 2 proposal and will include the plan for the Stage 2 research pilot and how it will be evaluated for success. This project is funded in response to CIVIC Innovation Challenge Track A. Communities and Mobility: Offering Better Mobility Options to Solve the Spatial Mismatch Between Housing Affordability and Jobs which is a collaboration between NSF and Department of Energy Vehicle Technology Office.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.