CAREER: Socially-Aware Control of Autonomy: Reshaping Urban Mobility in Traffic Networks with Mixed Vehicle Autonomy

职业：具有社会意识的自主控制：通过混合车辆自主重塑交通网络中的城市交通

基本信息

批准号：
2145134
负责人：
Negar Mehr
金额：
$ 50万
依托单位：
University of Illinois at Urbana-Champaign
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2022
资助国家：
美国
起止时间：
2022-02-15 至 2027-01-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2145134&HistoricalAwards=false
关键词：
CAREER Socially Aware Control Autonomy

项目摘要

As cities grow everywhere, and urban roadways become overburdened, efficient strategies are required for improving urban mobility. With the emergence of autonomous cars, there is an opportunity to reclaim urban mobility provided that a proactive control and planning approach is taken. In this project, our goal is to develop fundamental theory and domain-driven techniques for leveraging the opportunities that autonomous cars provide to achieve mobility-efficient smart cities. We consider mixed-autonomy traffic networks which are road networks that are shared by human-driven and autonomous cars. We will develop a set of algorithms for socially-aware control of autonomous cars in these systems. More precisely, we develop control algorithms that take into account the social implications of the co-existence of human-driven and autonomous cars and guarantee overall societal good. Our project enables the transformation from the current reality to the brighter future, in which autonomous cars harmoniously interact with the road and network traffic control systems to increase mobility. To unlock the mobility potentials of autonomous cars, a key control challenge is to account for how humans adapt and respond to autonomous cars’ actions such as routing decisions. We focus on travelers’ routing decisions and develop design and control algorithms that induce efficient routing decisions. We use routing games for modeling travelers’ route choices over traffic networks and tackle research challenges associated with controlling the core components of a mixed-autonomy network. (i) We will develop algorithms for altruistic control of autonomous cars’ routing decisions, that is, autonomous cars that are routed in the favor of society. (ii) We will develop pricing algorithms that affect humans' routing decisions such that the network is steered towards desirable states. (iii) Finally, we will develop planning strategies for network topology design and capacity regulation that induce efficient routing decisions by travelers. Our proposed control strategies will also be validated through extensive real-world experiments and traffic simulations.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.

随着世界各地的城市发展，城市道路变得过于负担，改善城市流动性需要有效的策略。随着自动驾驶汽车的出现，只要采取积极的控制和计划方法，就有机会回收城市流动性。在这个项目中，我们的目标是开发基本理论和领域驱动的技术，以利用自动驾驶汽车提供的机会来实现行动效率高效的智能城市。我们考虑混合自主交通网络，这些网络是由人类驱动和自动驾驶汽车共享的道路网络。我们将开发一套算法，用于在这些系统中对自动驾驶汽车的社会意识控制。更确切地说，我们开发了控制算法，这些算法考虑了人类驱动和自动驾驶汽车并存的社会含义，并保证了整体的社会益处。我们的项目使从当前的现实转变为更明亮的未来，在这种情况下，自动驾驶汽车与道路和网络交通控制系统和谐相互作用以提高行动性。为了释放自动驾驶汽车的移动性潜力，关键的控制挑战是说明人类如何适应和应对自动驾驶汽车的行动，例如路由决策。我们专注于旅行者的路由决策，并开发设计和控制诱导有效路由决策的设计和控制算法。我们使用路由游戏来建模旅客对交通网络的路线选择，并应对控制混合自治网络的核心组件相关的研究挑战。（i）我们将开发对自动驾驶决定的利他控制算法，即对社会有利的自动驾驶汽车。（ii）我们将开发出影响人类路线决定的定价算法，以使网络转向理想的国家。（iii）最后，我们将制定针对网络拓扑设计和容量调节的计划策略，从而导致旅行者有效的路由决策。我们提出的控制策略还将通过广泛的现实实验和交通模拟来验证。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响审查标准，认为通过评估被认为是珍贵的支持。