A Cruise Control Method for Connected Vehicle Systems Considering Side Vehicles Merging Behavior

Zhang, Tao; Zou, Yuan; Zhang, Xudong; Guo, Ningyuan; Wang, Wenwei

doi:10.1109/access.2018.2890134

Cited by 18 publications

(10 citation statements)

References 39 publications

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“…The brake command is converted into an air brake pressure signal, then sent to the electronic vacuum booster to control the brake cylinder and generate the brake pressure. We have performed an acceleration control analysis of this experimental vehicle in the literature [36]. The communication delay and drive delay are considered in the speed control strategy, and it is proved that the linear controller can accurately realize the preset speed curve.…”

Section: A Test Vehiclementioning

confidence: 99%

Predictive Eco-Driving Application Considering Real-World Traffic Flow

Zhang

Zou

et al. 2020

IEEE Access

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Eco-approach and departure (EAD) systems in connected vehicles are capable of providing the speed recommendations to drivers so that vehicles can pass through successive intersections at the appropriate instants to save time and energy. However, most of existing control strategies and global optimization algorithms for EAD systems have extremely high requirements for computational resources, which make EAD systems not easy to popularize and apply to real vehicles. To overcome this problem, this paper designs a traffic flow prediction model based on deep learning regression machine, and establishes a dynamic effective red-light duration model based on traffic flow queuing effect. To facilitate real-time update of the optimal speed, a constrained optimization model is proposed as an approximation approach, which can obtain similar optimal results to that of the pseudo-spectral method while greatly reducing calculating time. The effectiveness of the proposed control algorithm for EAD system on passing intersections and energy saving has been validated on the real vehicle under real-world traffic environment. Compared with the uninformed driver, the proposed EAD system saves 2% time and 4.6% energy on average in case that driver is informed and 8% time and 12.1% energy in case of autonomous driving.

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Section: A Test Vehiclementioning

confidence: 99%

Predictive Eco-Driving Application Considering Real-World Traffic Flow

Zhang

Zou

et al. 2020

IEEE Access

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“…In order to deal with above challenges, more flexible design for the vehicular platoon becomes an emerging trend. Connected cruise control (CCC), as a potential solution, has been proposed to hold a smooth traffic flow with flexible connectivity structure and communication topology [31,32].…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, the design of more flexible vehicle platoon system based on wireless communication technology has become as an emerging trend [27,29]. The CCC system, guarantee a stable traffic flow through flexible communication topologies and connection structures, has become a potential solution for future development [31,32]. In this paper, we investigate the CCC system as a case study by implementing the proposed architecture.…”

Section: Introductionmentioning

confidence: 99%

Fog-Based Distributed Networked Control for Connected Autonomous Vehicles

Wang

Guo

Gao

et al. 2020

Wireless Communications and Mobile Computing

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With the rapid developments of wireless communication and increasing number of connected vehicles, Vehicular Ad Hoc Networks (VANETs) enable cyberinteractions in the physical transportation system. Future networks require real-time control capability to support delay-sensitive application such as connected autonomous vehicles. In recent years, fog computing becomes an emerging technology to deal with the insufficiency in traditional cloud computing. In this paper, a fog-based distributed network control design is proposed toward connected and automated vehicle application. The proposed architecture combines VANETs with the new fog paradigm to enhance the connectivity and collaboration among distributed vehicles. A case study of connected cruise control (CCC) is introduced to demonstrate the efficiency of the proposed architecture and control design. Finally, we discuss some future research directions and open issues to be addressed.

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“…In this way, vehicles can be connected to the intelligent transportation system, exchange and share massive data of current traffic status and vehicle operating data [1]. These data can be used to improve the overall vehicular performance, in terms of mobility, safety, and fuel economy [2][3] By using V2I or V2V communication, traffic jams or unnecessary stop-and-go behavior and emergency acceleration behavior at signalized intersections in the main road are reduced to shrink energy consumption, which is the important research contents of driving in current urban road ecology [4][5]. In general, the main idea of eco-driving for electric vehicle (EV) on urban roads is to find the optimal speed trajectory for specific journey conditions from the perspective of reducing battery energy consumption [6].…”

Section: Introductionmentioning

confidence: 99%