论文标题
改善城市流动性：使用人工智能和新技术连接供求
Improving Urban Mobility: using artificial intelligence and new technologies to connect supply and demand
论文作者
论文摘要
随着我们社会中流动性的需求似乎增加了，以城市流动为中心的各种问题令人担忧的是，这个星球上的大多数城市居民。例如，如何以有效的（但压力较小）的方式从A到B？这些问题和关注点即使在19日期大流行期间也没有改变。相反，作为当前立场，避免公共交通工具的人只会导致车辆交通的增加。智能运输系统（ITS）旨在调查如何将信息和通信技术用于与运输有关的问题。这可能意味着监视和管理基础架构（例如，交通路口，交通信号等）。但是，目前，它也针对需求管理。在这个全景中，人工智能起着重要的作用，尤其是在机器学习方面的进步转化为使用计算视觉，连接和自动驾驶汽车，基于代理的模拟等。在目前的工作中，对我们小组开发的几项作品进行了调查，以整体的角度讨论，即，它们不仅涵盖了供应方（在其作品中通常发现），而且还涵盖了需求方面，并且在新颖的角度来看，两者的整合。
As the demand for mobility in our society seems to increase, the various issues centered on urban mobility are among those that worry most city inhabitants in this planet. For instance, how to go from A to B in an efficient (but also less stressful) way? These questions and concerns have not changed even during the covid-19 pandemic; on the contrary, as the current stand, people who are avoiding public transportation are only contributing to an increase in the vehicular traffic. The are of intelligent transportation systems (ITS) aims at investigating how to employ information and communication technologies to problems related to transportation. This may mean monitoring and managing the infrastructure (e.g., traffic roads, traffic signals, etc.). However, currently, ITS is also targeting the management of demand. In this panorama, artificial intelligence plays an important role, especially with the advances in machine learning that translates in the use of computational vision, connected and autonomous vehicles, agent-based simulation, among others. In the present work, a survey of several works developed by our group are discussed in a holistic perspective, i.e., they cover not only the supply side (as commonly found in ITS works), but also the demand side, and, in an novel perspective, the integration of both.
