Ecological control strategy for cooperative autonomous vehicle in mixed traffic considering linear stability. Issue 3 (18th November 2021)

• Record Type: Journal Article
• Authors: Lu, Chaoru; Liu, Chenhui
• Is Part Of: Journal of intelligent and connected vehicles. Volume 4:Issue 3(2021)
• Page Start: 115
• Page End: 124
• Publication Date: 2021-11-18
• Subjects: Adaptive cruise control -- Connected and autonomous vehicle (CAV) -- Linear stability; Intelligent transportation systems -- Periodicals; Automobiles -- Safety measures -- Periodicals; Autonomous vehicles -- Periodicals; Motor vehicles -- Technological innovations -- Periodicals; 629.2042
• DOI: 10.1108/JICV-08-2021-0012
• Languages: English
• ISSNs: 2399-9802

Abstract

Abstract : Purpose: This paper aims to present a cooperative adaptive cruise control, called stable smart driving model (SSDM), for connected and autonomous vehicles (CAVs) in mixed traffic streams with human-driven vehicles. Design/methodology/approach: Considering the linear stability, SSDM is able to provide smooth deceleration and acceleration in the vehicle platoons with or without cut-in. Besides, the calibrated Virginia tech microscopic energy and emission model is applied in this study to investigate the impact of CAVs on the fuel consumption of the vehicle platoon and traffic flows. Under the cut-in condition, the SSDM outperforms ecological SDM and SDM in terms of stability considering different desired time headways. Moreover, single-lane vehicle dynamics are simulated for human-driven vehicles and CAVs. Findings: The result shows that CAVs can reduce platoon-level fuel consumption. SSDM can save the platoon-level fuel consumption up to 15%, outperforming other existing control strategies. Considering the single-lane highway with merging, the higher market penetration of SSDM-equipped CAVs leads to less fuel consumption. Originality/value: The proposed rule-based control method considered linear stability to generate smoother deceleration and acceleration curves. The research results can help to develop environmental-friendly control strategies and lay the foundation for the new methods.