ADAS Enhanced by 5G Connectivity
| 项目名称： | ADAS Enhanced by 5G Connectivity |
| 摘要： | Advanced driver assistance systems (ADAS) are a key technology for improved traffic safety. Long before fully automated vehicles arrive in significant numbers, ADAS will see high penetration and substantially reduce accident rates. Toyota and Honda have both committed to focusing on �hands on the wheel, eyes on the road� ADAS long before (perhaps up to a decade) introducing higher levels of automation to consumers. This is a philosophy that resonates with the PI and co-investigator of this project. Connectivity between vehicles, and between vehicles and infrastructure, makes ADAS more effective by enabling vehicles to �see� around corners and through other vehicles. But connectivity via dedicated short range communication (DSRC), the 802.11-based standard that will likely be mandated by 2020, can become congested when a large number of vehicles, cyclists, and pedestrians congregate near intersections in urban areas. Moreover, DSRC does not offer the bandwidth for sharing of raw, or lightly-processed, sensor data between vehicles or from infrastructure to vehicles. In fact, in all likelihood, DSRC message traffic will be limited to the basic safety message, a low-rate, low-latency message that communicates a vehicle�s or cyclist�s or pedestrian�s current position and velocity to others in the vicinity. And even this message will become unreliable if too many DSRC transmitters find themselves fighting for slots in which to transmit, such as will occur in urban areas with heavy foot and vehicular traffic. This project aims to study how emerging 5G technology can be used to �supercharge� ADAS by releasing it from the limitations of DSRC. How can ADAS benefit from the sub-10-ms latency, the 100 Mbps per-user download data rate, and the high connection density that 5G promises? |
| 状态： | Completed |
| 资助组织： | Office of the Assistant Secretary for Research and Technology |
| 项目负责人： | Bhat, Chandra |
| 执行机构： | Data-Supported Transportation Operations and Planning Center |
| 主要研究人员： | Humphreys, Todd |
| 开始时间： | 20170930 |
| 预计完成日期： | 20180930 |
| 实际结束时间： | 0 |
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