V2X Based Traffic Light Assistant for Increased Efficiency of Hybrid &amp; Electric Vehicles

Jones, Stephen; Huss, Arno; Kural, Emre; Massoner, Alexander; Parrilla, Alejandro Ferreira; Allouchery, Laurent

doi:10.51202/9783181022894-167

Cited by 5 publications

(1 citation statement)

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“…[12][13][14] For example, signal phase and timing (SPaT, one of the V2I) information can give speed recommendations to the drivers, guiding them to pass the traffic lights during their green phase. [15][16][17][18] Studies 4,19 used V2X and V2I information to predict the velocity periodically and used it for energy management; Work 20 developed a real-time capable controller that integrated traffic prediction, vehicle dynamics, and powertrain operation optimization for connected automated vehicles with different powertrain types.…”

Section: Introductionmentioning

confidence: 99%

Communication‐based predictive energy management strategy for a hybrid powertrain

Deng

Adelberger

2021

Optim Control Appl Methods

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Predictive information can significantly improve energy efficiency in a hybrid powertrain, especially for a long drive. Ideally the prediction of a sufficiently long horizon can bring the maximum benefit, however during this horizon the traffic can change, making it impossible to continue the chosen optimal strategy. Due to the limited vision of vehicles' sensors, it is difficult to acquire information far away. Against this background, this article proposes a predictive optimal control strategy in the connected environment. It combines real-world vehicle-to-everything (V2X) information and cloud communication to allow for swift reaction and loss mitigation. More specifically, V2X information is used to detect impending changes on the route and the cloud is used to map these changes onto new constraints on the operation of the HEV. Instead of using "static" V2X information directly, a more realistic prediction method considering the dynamic of traffic is developed. Besides, an update strategy is adopted to timely cope with uncertainties. The performance of the approach is shown by a case study based on real driving cycles in Austria. The results show that the proposed structure is able to improve the performance (mainly fuel efficiency) up to 6.9%.

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Section: Introductionmentioning

confidence: 99%

Communication‐based predictive energy management strategy for a hybrid powertrain

Deng

Adelberger

2021

Optim Control Appl Methods

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DEIS: Dependability Engineering Innovation for Industrial CPS

Armengaud

Macher

Massoner

et al. 2017

Advanced Microsystems for Automotive Applications 2017

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The open and cooperative nature of Cyber-Physical Systems (CPS) poses new challenges in assuring dependability. The DEIS project (Dependability Engineering Innovation for automotive CPS. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 732242, see http://www.deis-project.eu addresses these challenges by developing technologies that form a science of dependable system integration. In the core of these technologies lies the concept of a Digital Dependability Identity (DDI) of a component or system. DDIs are modular, composable, and executable in the field facilitating (a) efficient synthesis of component and system dependability information over the supply chain and (b) effective evaluation of this information in-the-field for safe and secure composition of highly distributed and autonomous CPS. The paper outlines the DDI concept and opportunities for application in four industrial use cases

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Traffic lights system based on RFID for autonomous driving vehicle

Ali

Hussein

2017

2017 Annual Conference on New Trends in Information &Amp; Communications Technology Applications (NTICT)

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V2X Based Traffic Light Assistant for Increased Efficiency of Hybrid & Electric Vehicles

Cited by 5 publications

References 0 publications

Communication‐based predictive energy management strategy for a hybrid powertrain

Communication‐based predictive energy management strategy for a hybrid powertrain

DEIS: Dependability Engineering Innovation for Industrial CPS

Traffic lights system based on RFID for autonomous driving vehicle

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