Urban Transportation Operation and Management in a Connected and Autonomous vehicle Environment

互联和自动驾驶车辆环境中的城市交通运营和管理

• 批准号: RGPIN-2020-03942
• 负责人: Kattan, Lina
• 金额: $ 7.21万
• 依托单位: University of Calgary
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=739578
• 关键词: Urban; Transportation; Operation; Management; Connected

Once perceived as fiction, connected and autonomous vehicles (CAVs) can now "see", "talk", and drive themselves, and are transforming our cities' transportation systems. Depending on how they are deployed, CAVs will create tremendous opportunities, challenges and research needs. For instance, personal and transit autonomous vehicles will be equipped with advanced sensing technologies to navigate without any human interaction, influencing the driving behaviour in their vicinity. Connected vehicles, with their vehicle-to-vehicle, vehicle-to-infrastructure and vehicle-to-devices communication capabilities, will exchange vital information to enable cooperative decisions to achieve system-wide goals. My proposed research program builds upon activities undertaken during the previous Discovery Grant (DG) and Discovery Accelerator Supplement (DAS) to develop coherent theoretical and methodological platforms to harness the potentials of emerging technologies while anticipating and mitigating their negative externalities. My long-term vision is to bridge gaps between theory, methodology and real-world applications to advance the deployment of emerging transportation technologies in Canada, while contributing to economic diversification, environmental stewardship and equity in resource allocation. Over the next five years, my research program will develop a holistic framework where CAV-enabled technologies, policies and real-time traffic and transit control schemes all work in concert to achieve the overall objectives of improved efficiency, fairness, reliability and reduction of negative externalities. The inclusion of fairness concepts, which has not yet been attempted, is highly novel and unique to my research. The short-term objectives to be achieved are as follows: 1. Design the next generation of traffic control schemes that leverage the potentials of CAVs; 2. Devise new forms of travel demand policies to shape CAV deployment to meet societal goals; 3. Design novel CAV-enabled transit control to improve transit reliability and rider experience; 4. Estimate/predict the induced changes in travel patterns stemming from CAVs; and 5. Evaluate the resulting network performance in terms of throughput, reliability and resilience. Our vision is to provide ground-breaking solutions for urban transportation by developing novel concepts, policies, models, methodologies and algorithms. Our scientific approach capitalizes on traffic flow theory, advanced traffic management, transit control, network modelling and simulation, mathematical modelling and programming, bi-level game theory, agent-based modelling, data-driven insights, and machine learning. This research has important implications for the Canadian economy and is vital for the multi-disciplinary training of HQP. Our trainees will form the next generation of transportation policymakers, researchers, academics, and engineers who will be the leaders and champions for driving the Smart Cities initiative.

一旦被视为小说，互联和自动驾驶汽车（骑士）现在就可以“看到”，“谈话”，自我驱动，并正在改变我们的城市运输系统。根据它们的部署方式，骑士将创造巨大的机会，挑战和研究需求。例如，个人和过境自动驾驶汽车将配备高级传感技术，可以在没有任何人类互动的情况下导航，从而影响其附近的驾驶行为。连接的车辆及其车辆到车辆，车辆到基础设施以及车辆对设备的通信功能，将交换重要信息，以实现合作决策以实现全系统的目标。我提出的研究计划基于在先前的发现赠款（DG）（DG）和Discovery Accelerator补充剂（DAS）开发一致的理论和方法论平台上进行的活动，以利用新兴技术的潜力，同时预料和减轻其负面外部性。我的长期愿景是弥合理论，方法论和现实世界应用之间的差距，以促进加拿大新兴运输技术的部署，同时促进经济多样化，环境管理和资源分配中的公平性。在接下来的五年中，我的研究计划将开发一个整体框架，在该框架中，基于CAV的技术，政策和实时交通和过境控制方案都协同起作用，以实现提高效率，公平性，可靠性，可靠性和负面外部性的总体目标。尚未尝试的公平概念的包含是我的研究非常新颖，并且是独一无二的。要实现的短期目标如下：1。设计利用骑士潜力的下一代交通控制计划； 2。设计新形式的旅行需求政策，以塑造CAV部署以实现社会目标； 3。设计新颖的CAV启用过境控制，以提高过境可靠性和骑手体验； 4。估计/预测骑士引起的旅行模式的诱发变化；和5。根据吞吐量，可靠性和弹性评估所得的网络性能。我们的愿景是通过开发新颖的概念，政策，模型，方法和算法来为城市运输提供开创性的解决方案。我们的科学方法利用交通流量理论，高级交通管理，交通控制，网络建模和仿真，数学建模和编程，双层游戏理论，基于代理的建模，数据驱动的见解和机器学习。这项研究对加拿大经济具有重要意义，对于HQP的多学科培训至关重要。我们的学员将组成下一代运输决策者，研究人员，学者和工程师，他们将成为推动智慧城市倡议的领导者和拥护者。