Jie Zhu - Geologi och geoteknik

​Coordination and Analysis of Connected and Autonomous Vehicles in Freeway On-Ramp Merging Areas

Opponent: Professor Shimul Haque, Queensland University of Technology, Australien

Examinator: Professor Lars Rosén, Geologi och geoteknik, ACE, Chalmers

Huvudhandledare: Professor Xiaobo Qu, Geologi och geoteknik, ACE, Chalmers

 

Research

Plats: SB-H5, Sven Hultins gata 6, Chalmers och Zoom

 

​Freeway on-ramps are typical bottlenecks in the freeway network, where the merging maneuvers of ramp vehicles impose frequent disturbances on the traffic flow and cause negative impacts on traffic safety and efficiency. The emerging Connected and Autonomous Vehicles (CAVs) hold the potential for regulating the behaviors of each individual vehicle and are expected to substantially improve the traffic operation at freeway on-ramps. The aim of this research is to explore the possibilities of optimally facilitating freeway on-ramp merging through the coordination of CAVs, and to discuss the impacts of CAVs on the traffic performance at on-ramp merging.
In view of the existing research efforts and gaps in the field of CAV on-ramp merging operation, a novel CAV coordinative merging strategy is proposed by creating large gaps on the main road and directing the ramp vehicles into the gaps in the form of platoon. The combination of gap creation and platoon merging jointly facilitates the mainline and ramp traffic and targets at the optimal performance at the traffic flow level. The coordination consists of three components: (1) mainline vehicles proactively decelerate to create large merging gaps; (2) ramp vehicles form platoons before entering the main road; (3) the gaps created on the main road and the platoons formed on the ramp are coordinated with each other in terms of size, speed, and arrival time. The coordination is analytically formulated as an optimization problem, incorporating the macroscopic and microscopic traffic flow models. The model uses traffic state parameters as inputs and determines the optimal coordination plan adaptive to real-time traffic conditions.
The proposed coordination is adapted for various application contexts, including: (1) a basic strategy for single-lane freeways with full CAV penetration rate, (2) an extended strategy for mixed traffic conditions of CAVs and Human-Driven Vehicles (HDVs) where the uncertainties induced by HDVs are taken into account, and (3) an extended strategy for multi-lane freeways where the free lane-changes on the main road are considered. The benefits of the proposed strategies are demonstrated through illustrative case studies conducted on microscopic traffic simulation platforms. The results show that the introduction of CAVs, along with well-designed coordination strategies, would lead to substantial improvements in traffic operational efficiency and safety at on-ramp merging. An in-depth investigation and discussion about the coordination strategy and the impacts of CAVs are further carried out in the dissertation.
Kategori Disputation
Plats: SB-H5, lecture hall, Sven Hultins Gata 6, Samhällsbyggnad I-II och Zoom
Tid: 2022-06-10 09:00
Sluttid: 2022-06-10 12:30

Sidansvarig Publicerad: fr 06 maj 2022.