9 research outputs found

    Coordinated Formation Control for Intelligent and Connected Vehicles in Multiple Traffic Scenarios

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    In this paper, a unified multi-vehicle formation control framework for Intelligent and Connected Vehicles (ICVs) that can apply to multiple traffic scenarios is proposed. In the one-dimensional scenario, different formation geometries are analyzed and the interlaced structure is mathematically modelized to improve driving safety while making full use of the lane capacity. The assignment problem for vehicles and target positions is solved using Hungarian Algorithm to improve the flexibility of the method in multiple scenarios. In the two-dimensional scenario, an improved virtual platoon method is proposed to transfer the complex two-dimensional passing problem to the one-dimensional formation control problem based on the idea of rotation projection. Besides, the vehicle regrouping method is proposed to connect the two scenarios. Simulation results prove that the proposed multi-vehicle formation control framework can apply to multiple typical scenarios and have better performance than existing methods

    Experimental Validation of DeeP-LCC for Dissipating Stop-and-Go Waves in Mixed Traffic

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    We present results on the experimental validation of leading cruise control (LCC) for connected and autonomous vehicles (CAVs). In a mixed traffic situation that is dominated by human-driven vehicles, LCC strategies are promising to smooth undesirable stop-and-go waves. Our experiments are carried out on a mini-scale traffic platform. We first reproduce stop-and-go traffic waves in a miniature scale, and then show that these traffic instabilities can be dissipated by one or a few CAVs that utilize Data-EnablEd Predicted Leading Cruise Control (DeeP-LCC). Rather than identifying a parametric traffic model, DeeP-LCC relies on a data-driven non-parametric behavior representation for traffic prediction and CAV control. DeeP-LCC also incorporates input and output constraints to achieve collision-free guarantees for CAVs. We experimentally demonstrate that DeeP-LCC is able to dissipate traffic waves caused by car-following behavior and significantly improve both driving safety and travel efficiency. CAVs utilizing DeeP-LCC may bring additional societal benefits by mitigating stop-and-go waves in practical traffic.Comment: 8 pages, 6 figure

    A Printed Dipole Array with Bidirectional Endfire Radiation for Tunnel Communication

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    Tunnel communication always suffers from path loss and multipath effects caused by surrounding walls. Meanwhile, the traditional leaky coaxial cables are expensive to deploy, inconvenient to operate, and difficult to maintain, leading to many problems in practical use. To solve the abovementioned problems, a low-profile printed dipole array operating at 3.5 GHz with bidirectional endfire radiation is designed based on the method of maximum power transmission efficiency (MMPTE). By setting two virtual test receiving dipoles at the two opposite endfire directions and then maximizing the power transmission efficiency between the printed dipole array to be designed and the test receiving antennas, the optimal amplitudes and phases for the array elements are obtained. Based on the optimal distributions of excitations, the simulation results show that the proposed eight-element printed dipole array can simultaneously generate two mirrored endfire beams towards opposite directions. Furthermore, the corresponding normalized cross-polarization levels are lower than āˆ’22.3 dBi both in the azimuth and elevation planes. The peak endfire gain is 10.7 dBi with maintenance of higher than 10 dBi from 3.23 GHz to 3.66 GHz, which is suitable for tunnel communication

    Formation control for connected and automated vehicles on multiā€lane roads: Relative motion planning and conflict resolution

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    Abstract Existing research has revealed that multiā€vehicle coordinated decision making and control can achieve an improvement in both traffic efficiency and driving safety. In the multiā€lane scenarios, a typical coordination method is multiā€vehicle formation control. The existing formation control methods predefine the formation switching process and have not considered or explained the collisionā€free behaviour of vehicles in detail. In this paper, a multiā€lane formation control strategy for connected and automated vehicles (CAVs) is proposed. The planning framework is biā€level, which can switch the structure of multiā€vehicle formation in different scenarios smoothly and effectively. In the upperā€level, the relative coordinate system is built to plan the collisionā€free relative paths for vehicles. In the lowerā€level, multiā€stage trajectory planning and tracking are modelled as an optimal control problem with path constraints. The case study verifies the function of the formation control method in three laneā€numberā€changing scenarios. Largeā€scale simulations in the laneā€drop bottleneck scenario are conducted under different input traffic volumes, and the numerical results indicate that the proposed formation control method reduces congestion and improves both traffic efficiency and fuel economy at high trafficĀ volumes

    Perspectives on ENCODE

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    The Encylopedia of DNA Elements (ENCODE) Project launched in 2003 with the long-term goal of developing a comprehensive map of functional elements in the human genome. These included genes, biochemical regions associated with gene regulation (for example, transcription factor binding sites, open chromatin, and histone marks) and transcript isoforms. The marks serve as sites for candidate cis-regulatory elements (cCREs) that may serve functional roles in regulating gene expression1. The project has been extended to model organisms, particularly the mouse. In the third phase of ENCODE, nearly a million and more than 300,000 cCRE annotations have been generated for human and mouse, respectively, and these have provided a valuable resource for the scientific community.11Nsciescopu

    Expanded encyclopaedias of DNA elements in the human and mouse genomes

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    AbstractThe human and mouse genomes contain instructions that specify RNAs and proteins and govern the timing, magnitude, and cellular context of their production. To better delineate these elements, phase III of the Encyclopedia of DNA Elements (ENCODE) Project has expanded analysis of the cell and tissue repertoires of RNA transcription, chromatin structure and modification, DNA methylation, chromatin looping, and occupancy by transcription factors and RNA-binding proteins. Here we summarize these efforts, which have produced 5,992 new experimental datasets, including systematic determinations across mouse fetal development. All data are available through the ENCODE data portal (https://www.encodeproject.org), including phase II ENCODE1 and Roadmap Epigenomics2 data. We have developed a registry of 926,535 human and 339,815 mouse candidate cis-regulatory elements, covering 7.9 and 3.4% of their respective genomes, by integrating selected datatypes associated with gene regulation, and constructed a web-based server (SCREEN; http://screen.encodeproject.org) to provide flexible, user-defined access to this resource. Collectively, the ENCODE data and registry provide an expansive resource for the scientific community to build a better understanding of the organization and function of the human and mouse genomes.11Nsciescopu
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