Title :
Improving traffic operations using real-time optimal lane selection with connected vehicle technology
Author :
Qiu Jin ; Guoyuan Wu ; Boriboonsomsin, Kanok ; Barth, Matthew
Author_Institution :
Electr. Eng. Dept., Univ. of California, Riverside, Riverside, CA, USA
Abstract :
To better regulate traffic flow and reduce the potential impacts due to uncoordinated lane changes, we proposed a real-time optimal lane selection (OLS) algorithm by using the information available from connected vehicle (CV) technology. Such information includes the location, speed, lane and desired driving speed of individual vehicle agents (VA) on a localized roadway. Microscopic traffic simulation studies show that the proposed algorithm can result in both mobility and environmental benefits for the entire traffic system. Specifically, the application of the OLS algorithm reduces the average travel time by up to 3.8% and the fuel consumption by around 2.2%. In addition, the reduction in emissions of criteria pollutants, such as CO, HC, NOx and PM2.5 ranges from 1% to 19%, depending on the congestion level of the roadway segment. Potential extensions of the proposed OLS algorithm are discussed at the end of this paper.
Keywords :
multi-agent systems; road traffic; road vehicles; traffic engineering computing; CV technology; OLS algorithm; VA; connected vehicle technology; individual vehicle agents; localized roadway; microscopic traffic simulation; real-time optimal lane selection; roadway segmentation; traffic flow; traffic operations; uncoordinated lane changes; Energy consumption; Microscopy; Optimization; Real-time systems; Road transportation; Traffic control; Vehicles; Lane selection; connected vehicles; optimization;
Conference_Titel :
Intelligent Vehicles Symposium Proceedings, 2014 IEEE
Conference_Location :
Dearborn, MI
DOI :
10.1109/IVS.2014.6856515