Next Generation of Smart Traffic Signals
| 项目名称： | Next Generation of Smart Traffic Signals |
| 摘要： | Although adaptive signal control has demonstrated economic and customer satisfaction benefits--reducing travel time, delays, and stops--and has been used abroad for more than three decades, most jurisdictions in the United States still use fixed-length, time-of-day traffic control systems. A major barrier to wider adoption of "smart" traffic control systems has been cost: initial investments in signal control hardware, communication networks, and comprehensive traffic studies, as well as the cost of periodic updates to adjust systems to changing traffic conditions. Both conventional and adaptive systems require periodic traffic studies and recalibration. Improvements in technologies associated with adaptive traffic control have paved the way for a next generation of adaptive systems that may spur broader implementation. Hardware memory and processors, including add-on processor boards for legacy hardware, now offer more powerful computing resources at a reasonable cost. Detector technology is also presenting new possibilities, including small, wireless, individual detectors. Finally, the presence of high-bandwidth communications networks in more locales creates new communications possibilities for transportation agencies. This Exploratory Advanced Research (EAR) project supports the development of the next-generation architecture and algorithms--RHODESNG--that can harness the power of these technologies. The goal of this EAR project is an intelligent system that continuously adapts its operations to changing traffic conditions via high-speed communications with vehicles and infrastructure. This system uses self-adaptive algorithms to integrate the position, speed, and queue data received from vehicles and infrastructure sensors and transmitters, accurately perform high-speed computations, make predictions, and continuously adjust its critical parameters based on incoming data--a strategy of monitor, learn, predict, and respond optimally. In addition, data collected through the system can be used for regional and other planning functions. |
| 状态： | Completed |
| 资金： | 0.00 |
| 资助组织： | Federal Highway Administration |
| 执行机构： | Arizona State University, Phoenix |
| 开始时间： | 20070926 |
| 实际结束时间： | 20090926 |
| 主题领域： | Highways；Operations and Traffic Management |
相关文献
- Next Generation Traffic Management Centers
- Trip-Generation Rates for Smart Growth Land Use Projects
- Next Generation Scenario Planning Guidebook
- MADONNA: A Multi-Attribute Decision-Making Optiizer for Next-Generation Network-Upgrade and Assessment--Workshop and Professional Development for all VDOT Districts
- Testing Methods for the Next Generation of Concrete
- Validation and Calibration of Smart-Growth Land-Use Projects Trip-Generation Rates Spreadsheet
检索历史
应用推荐
