A Multi-class Lane-changing Advisory System for Freeway Merging Sections. Issue 2 (2021)

• Record Type: Journal Article
• Authors: Sharma, Salil; Papamichail, Ioannis; Nadi, Ali; van Lint, Hans; Tavasszy, Lóránt; Snelder, Maaike
• Is Part Of: IFAC-PapersOnLine. Volume 54:Issue 2(2021)
• Page Start: 93
• Page End: 98
• Publication Date: 2021
• Subjects: lane-changing advisory -- LQR control method -- merging section -- multi-class -- traffic congestion -- cooperative intelligent transportation system; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2021.06.014
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: Cooperative intelligent transportation systems (C-ITS) support the exchange of information between vehicles and infrastructure (V2I or I2V). This paper presents an in-vehicle C-ITS application to improve traffic efficiency around a merging section. This application balances the distribution of traffic over the available lanes of a freeway, by issuing targeted lane-changing advice to a selection of vehicles. We add to existing research by embedding multiple vehicle classes in the lane-changing advisory framework. We use a multi-class multi-lane macroscopic traffic flow model to design a feedback-feedforward control law that is based on a linear quadratic regulator (LQR). The performance of the proposed system is evaluated using a microscopic traffic simulator. The results indicate that the lane-changing advisory system is able to suppress Shockwaves in traffic flow and can significantly alleviate congestion. Besides bringing substantial travel time benefits around merging sections of up to nearly 21%, the system dramatically reduces the variance of travel time losses in the system.