CONNECT: Collaboration and Optimization via Neighboring Networks for Efficient City Transportation

California has long grappled with a transportation crisis that has had far-reaching consequences. This crisis has had a significant impact on both the economy, as goods movement is severely affected, and residents, who face hindered mobility and compromised safety. Two pressing issues at the heart of this transportation crisis are congestion and traffic safety. It is a common occurrence that congestion leads to traffic accidents, which, in turn, exacerbate congestion further. Given the dynamic nature of traffic, effective solutions for traffic management must be capable of real-time monitoring, analysis, and intervention. The main objective of this project is to address the transportation challenges by implementing efficient and intelligent traffic management that operates in real time. To achieve this, the proposed project will leverage an ad-hoc network composed of neighboring vehicles and roadside infrastructure. Through collaboration and optimization, this network will effectively manage traffic. The exchange of information between vehicles, vehicles and roadside infrastructure, and roadside infrastructure units within the ad-hoc network will play a crucial role in maintaining basic traffic safety. Furthermore, the roadside infrastructure units will also share information with regional and city transportation stations/centers to obtain more comprehensive travel suggestions.

Principal Investigator: 
Tairan Liu
PI Contact Information: 

Tairan.Liu@csulb.edu

CSU, Long Beach

Dates: 
March 2023 to March 2024
Impacts/Benefits of Implementation: 

This research is expected to have several impacts and benefits. 

  • Improved traffic flow: The proposed research leverages advanced technologies such as sensors, real-time data analysis, and predictive modeling to optimize traffic flow. This can result in reduced congestion, shorter travel times, and smoother transportation operations.
  • Enhanced safety: Intelligent transportation systems incorporate features like collision detection, automated emergency braking, and intelligent signaling, which can significantly improve road safety. These systems can help prevent accidents, minimize human error, and provide early warnings for potential hazards.
  • Reduced emissions and environmental impact: By optimizing traffic flow and reducing congestion, intelligent transportation systems can lead to a decrease in vehicle idling time and fuel consumption. This, in turn, reduces carbon emissions, air pollution, and the overall environmental impact of transportation.
Project Number: 
2322

-

CSUTC
MCEEST
MCTM
NTFC
NTSC

Contact Us

SJSU Research Foundation   210 N. 4th Street, 4th Floor, San Jose, CA 95112    Phone: 408-924-7560   Email: mineta-institute@sjsu.edu