Demand-Side Management of Auto Traffic
| 项目名称： | Demand-Side Management of Auto Traffic |
| 摘要： | Fueled by burgeoning e-commerce, urban parcel delivery has emerged as a high growth market that is undergoing rapid technological change, particularly in the business-to-consumer segment. New classes of vehicles such as drones, droids, and autonomous ground vehicles, combined with new delivery models featuring crowdsourcing, parcel lockers , and mobile lockers will enable a significant shift away from the conventional model of a dedicated delivery person operating a van. In order to attain the full potential of these changes to reduce costs and increase convenience, it is necessary to develop a complementary set of demand management strategies that will enable the next-generation parcel delivery system to mitigate current traffic congestion problems and avoid creating new ones. The aims of this project are (1) to quantify the current and anticipated future contributions of urban parcel delivery to urban congestion and related problems, such as traffic accidents; (2) to identify opportunities for incentivizing consumers and delivery services to modify their behaviors in order to reduce the congestion impacts of urban parcel delivery. To accomplish these objectives, a model of urban congestion that is sensitive to parcel delivery activities will be developed and integrated with models of consumer and service provider choice. The modeling system will be used to assess the congestion reduction benefits of a range of policies geared toward encouraging consumers and service providers to adopt behaviors that reduce the congestion caused by urban delivery. |
| 状态： | Active |
| 资金： | 269479 |
| 资助组织： | Office of the Assistant Secretary for Research and Technology |
| 项目负责人： | Li, Xiaopeng |
| 执行机构： | University of California Berkeley<==>National Institute for Congestion Reduction |
| 开始时间： | 20200901 |
| 预计完成日期： | 20210930 |
| 主题领域： | Freight Transportation；Highways；Operations and Traffic Management；Planning and Forecasting |
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