Abstract: The invention provides a roadside computing system (RCS), or an edge computing system, for an autonomous vehicle. The RCS comprises a hierarchy of roadside unit (RSU) and an onboard unit (OBU) in an individual vehicle. The RSU comprises a data processing module and a communication module, and is capable of generating guidance information and targeted instructions for individual vehicle. The data processing module of the RSU comprises two processors: an External Object Calculating Module (EOCM) and an AI processing unit. Thus, the RCS utilizes roadside edge computing power and AI models to support autonomous driving for the vehicle. The OBU comprises a data processing module, a communication module, and a vehicle control module, and is capable of generating vehicle-specific targeted instruction for the vehicle based on guidance information and targeted instructions received from RSUs, and controlling the vehicle based on vehicle-specific targeted instruction.

Abstract: The invention presents a cloud-based model deployment and control system (CMDCS) for providing automated driving services. The CMDCS comprises a cloud-based platform, an onboard unit (OBU), and a Vehicle-to-System component. The cloud-based platform comprises a localization-enhancement subsystem and a cloud computing module. The CMDCS is configured to collect detectable data and undetectable data from vehicles, road, and cloud. Then, the CMDCS deploys a set of end-to-end AI models and methods for automated driving services, comprising sensing, prediction, planning, and control services. The AI models and methods are trained and optimized to process collected data for providing operating parameters for vehicles. Then, the vehicles can be effectively and efficiently controlled and operated by the CMDCS. In addition, the CMDCS is configured to generate and provide detailed time-sensitive vehicle specific control instructions.

Abstract: Provided herein is an artificial intelligence-based mobile roadside intelligent unit (MRIU) for providing, supplementing, and/or enhancing the control and operation of autonomous vehicles in normal and long-tail scenarios. The MRIU comprises a computing module configured to provide supplemental computation capability for autonomous driving. The MRIU comprises a communication module to communicate and exchange data with a vehicle or a cloud. The MRIU provides prediction, decision-making, and/or control functions for autonomous driving. The MRIU provides edge computing capability for autonomous vehicles to train and operate artificial intelligence-based intelligent driving models in a distributed fashion. Specifically, an edge computing unit conducts data fusion and data feature extraction, provides prediction, formulates control strategies, generates vehicle control instructions, and/or distributes vehicle control information and/or instructions for an autonomous vehicle.

Abstract: This invention presents a function allocation system for an autonomous vehicle (AV). During the operations of the AV, some or all of its automated driving capabilities or functions could be downgraded due to long-tail events or malfunctioning. The roadside intelligent infrastructure, or the cloud platform, could supplement some or all of AV's automated driving functions, including sensing, prediction and decision-making, and/or control functions. The function allocation system dynamically allocates these functions between AV and intelligent infrastructure, achieving a higher system intelligence level S than the downgraded vehicle intelligence level V. In addition, a function allocation system could dynamically allocate sensing, prediction and decision-making, and/or control functions between AV and a cloud platform. This invention also presents a function integration system or a fusion system for an AV.

Abstract: The invention provides a vehicle AI computing system (VACS) that supports autonomous driving through an Onboard Unit (OBU) for vehicle-based computing and distributed computing based on vehicle road-cloud. The vehicle-based computing can effectively complete various computational tasks by using onboard computing resources. The distributed computing allows the vehicle to work in collaboration with roadside units (RSUs) and/or the cloud to effectively complete various computational tasks. The VACS features an OBU with a sensing module, a communication module, and a data processing module that integrates data from vehicle sensors, RSUs, and the cloud. The OBU also includes a vehicle control module that helps control the vehicle based on the data of RSU and cloud. The VACS leverages high performance computation resources to implement end to end driving tasks including sensing, prediction, planning and decision making, and control.

Abstract: A filter element for coupling adsorption and regeneration of volatile organic compounds and a purification device are provided. The filter element includes a filter element body, a photocatalytic mechanism and adsorption-filtration body(s). The adsorption-filtration body(s) may be of a hollow columnar structure where the photocatalytic mechanism is located. VOCs are quickly adsorbed by the adsorption-filtration body(s), then thermal desorption regeneration is performed on the adsorption-filtration body(s) during a time interval of stopping discharging of the exhaust gas, and a photocatalysis technology is used to cyclically purify the thermally desorbed VOCs, which achieves the synergy of high-density and purification in the two technologies. Furthermore, it takes full advantages of high adsorption, filtration and purification efficiency, low photolysis catalysis costs, and easy operation and maintenance of the on-site regeneration.

Abstract: This technology described herein provides embodiments of a cloud-based mobility service system for a Connected Automated Vehicle Highway (CAVH). In some embodiments, the technology provides a cloud-based mobility service system to provide the services and functionalities of different components of a CAVH system including, for example, user, vehicle, infrastructure, system, roadside, and CAVH traffic control layers. Detailed cloud-based data interfaces and services are described for each component, e.g., regarding their data needs to and from the cloud system. Cloud functionalities including the communication, computational, and analytic needs are described for each system component. The CAVH cloud services also provide integrated CAVH functionalities including planning, control, sensing, prediction, and analytics at macroscopic, mesoscopic, and microscopic levels of CAVH systems.

Abstract: Provided herein is technology relating to automated driving and particularly, but not exclusively, to a mobile intelligent road infrastructure technology configured to serve automated driving systems by providing, supplementing, and/or enhancing autonomous driving functions for connected automated vehicles under common and unusual driving scenarios.

Abstract: The technology described herein provides Automated Driving System (ADS) methods and systems for coordinating and/or fusing intelligence and functions between Connected Automated Vehicles (CAV) and ADS infrastructure to provide target levels of automated driving. The technology provides systems and methods for function allocation comprising sensing allocation, prediction and decision-making allocation, and control allocation. The ADS operates across various intelligence levels, identified during vehicle operation. The function allocation system dynamically allocates essential functions based on the intelligence levels of both vehicles and infrastructures, ensuring that ADS achieves a system intelligence that surpasses that of individual components. This methodical function distribution enables ADS to manage both vehicles and infrastructures in a manner that enhances vehicular operations and control.

Abstract: Provided are new classes of reconfigurable, multistable metasurfaces using the physics of colloids confined within nematic liquid crystals (NLCs). The colloids are physically moved from one stable location to another as defined by NLC-colloid interactions by external switching fields. These colloids can be scatterers within reconfigurable metasurfaces with electromagnetic (EM) responses that change with colloid location. because the colloids are moved between stable loci, these metasurfaces are also multistable, and require energy input only when changing colloid position. Furthermore, because the colloids can be returned to their original positions by simply reversing the switching field, all changes in EM responses are entirely reversible.

Abstract: Provided are compositions that include a nematic colloid, the nematic colloid comprising a nematic liquid crystal and a key colloid; and a lock colloid, the lock colloid optionally having at least two arms extending therefrom, the lock colloid being configured for assembly with the key colloid of the nematic colloid, the assembly optionally being mediated by a dipole interaction between the colloid and the lock colloid, by a disinclination line of the nematic colloid, or any combination thereof. Also provided are related methods. The disclosed compositions and methods can be used to, e.g., assemble chain and lattice structures from the key colloids by exploiting disinclination lines and dipole defects of the components of the compositions.

Abstract: The present invention relates to a formulation comprising a PD-L1/LAG-3 bispecific antibody, and particularly to a pharmaceutical formulation comprising a PD-L1/LAG-3 bispecific antibody, a buffer, a stabilizer, a surfactant and a chelating agent. Furthermore, the present invention further relates to therapeutic or prophylactic use of these formulations.

Abstract: Provided are compositions that include a nematic colloid, the nematic colloid comprising a nematic liquid crystal and a key colloid; and a lock colloid, the lock colloid optionally having at least two arms extending therefrom, the lock colloid being configured for assembly with the key colloid of the nematic colloid, the assembly optionally being mediated by a dipole interaction between the colloid and the lock colloid, by a disinclination line of the nematic colloid, or any combination thereof. Also provided are related methods. The disclosed compositions and methods can be used to, e.g., assemble chain and lattice structures from the key colloids by exploiting disinclination lines and dipole defects of the components of the compositions.

Abstract: The present invention relates to formulations comprising an anti-LAG-3 antibody, and in particular to pharmaceutical formulations comprising an antibody specifically binding to LAG-3 molecules, a buffer, a stabilizer and a surfactant. Furthermore, the present invention also relates to therapeutic or prophylactic use of these formulations.