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Incentive Systems for New Mobility Services

项目名称：	Incentive Systems for New Mobility Services
摘要：	With rapid population growth and urban development, traffic congestion has become an inescapable issue, especially in large cities. Many congestion reduction strategies have been proposed in the past, ranging from roadway extension, transportation systems management and operations, to demand management. In particular, as a demand management approach, congestion pricing and incentive offering schemes have been used as reinforcements for traffic control. Despite extensive research on congestion pricing mechanisms, almost all studies focus on traditional mobility systems and little has been done for future mobility services. With recent technological advancements, the shape of mobility services is drastically changing. Traditionally, the driver is the car owner and is the ultimate decision-maker on the origin, destination, routing, and the time of travel. In contrast, future mobility systems consist of different organizations and companies that completely (or partially) influence the behavior of individual human (or AI-based) drivers. Such organizations include car-sharing services (e.g. Zipcar, Turo), ride-hailing services (e.g. Uber, Lyft), crowdsourcing delivery systems (e.g. Amazon Flex, Instacart, Doordash), navigation applications (e.g. Google maps and Waze), and even companies producing autonomous cars with built-in navigation systems (e.g. Tesla), to name just a few. In this research, investigators will study and develop mechanisms for offering incentives to organizations and companies to change the behavior of individual drivers in their organization (or individuals using their organization’s services). Such mechanisms can be more effective than traditional individual-level incentive offering mechanisms since each organization can control a large pool of individual drivers; thus moving the traffic flow toward the optimal “system-level” performance. In addition, such an “organization-level” incentive offering enjoys more flexibility than the individual “driver-level” incentive mechanisms. For example, the time of travel or the choice of routing can be influenced significantly by providing incentives to organizations rather than to individual drivers. Even when congestion in certain areas is inevitable, incentives can be offered to organizations to use vehicles with less of a carbon footprint (such as electric cars) in congested areas to reduce the total carbon emission of the system. The researchers' approach is real-time and relies on historical data as well as demand estimates provided by organizations to continually predict traffic flow of the network; and provides incentives to organizations to reduce their carbon footprint by changing the behavior of individual drivers in their organization. Finally, researchers will evaluate the performance of their method using data from the Los Angeles area as well as the models developed during this research. The Los Angeles region is ideally suited for being the validation area as one of the most congested cities in the US. Additionally, researchers at USC have developed the Archived Data Management System (ADMS) that collects, archives, and integrates a variety of transportation datasets from Los Angeles, Orange, San Bernardino, Riverside, and Ventura Counties. ADMS includes access to real-time traffic datasets from i) 9500 highway and arterial loop detectors providing data approximately every 1 minute, and ii) 2500 bus and train global positioning system (GPS) location (AVL) data using operating throughout Los Angeles County. Investigators will use this data to evaluate the performance of the proposed algorithm. As a byproduct of this research, researchers will also study the effectiveness of this “organization-level” method compared to individual-level incentive offering mechanisms.
状态：	Programmed
资金：	100000
资助组织：	Office of the Assistant Secretary for Research and Technology<==>National Center for Sustainable Transportation
项目负责人：	Iacobucci, Lauren
执行机构：	National Center for Sustainable Transportation<==>METRANS Transportation Center
开始时间：	20210101
预计完成日期：	20211231
主题领域：	Data and Information Technology；Highways；Operations and Traffic Management；Passenger Transportation；Planning and Forecasting；Vehicles and Equipment