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    SYSTEMS AND METHODS FOR MOBILITY SERVICE DEMAND PREDICTION
    1.
    发明申请
    SYSTEMS AND METHODS FOR MOBILITY SERVICE DEMAND PREDICTION 有权

    公开(公告)号：US20220366441A1

    公开(公告)日：2022-11-17

    申请号：US17321579

    申请日：2021-05-17

    申请人： Ford Global Technologies, LLC

    发明人： James Fishelson ,  Richard Twumasi-Boakye ,  Xiaolin Cai ,  Andrea Broaddus ,  Dhanush Harihar ,  Mohammed Fayaj navaz ,  Jon Coleman ,  Amit Bhagwan ,  Archak Mittal

    IPC分类号： G06Q30/02 ,  G06F30/20

    摘要： Systems and methods for mobility service demand prediction are disclosed herein. An example method includes determining trips of an existing transportation mode for a geo fenced area that are poorly served. The trips that are poorly served can include any one or more of the trips with a moderately high trip density, a moderately high ratio of transit-private vehicle trips, and/or a moderately high ratio of transit-time to private vehicle travel times. The method can include modeling trips of a new transportation service for a geofenced area, determining, based on the modeling, when the trips of the new transportation service have at least one improved travel parameter relative the trips that are poorly served, as well as generating a mobility service demand prediction that is indicates how likely users are to adopt new transportation service in view of the existing transportation mode.

    SIMULATION-BASED CORRIDOR DESIGN FOR CONNECTED AUTONOMOUS VEHICLES
    7.
    发明申请
    SIMULATION-BASED CORRIDOR DESIGN FOR CONNECTED AUTONOMOUS VEHICLES 有权

    公开(公告)号：US20220382926A1

    公开(公告)日：2022-12-01

    申请号：US17334115

    申请日：2021-05-28

    申请人： Ford Global Technologies, LLC

    发明人： Archak Mittal ,  James Fishelson ,  Richard Twumasi-Boakye ,  Yifan Chen ,  Xiaolin Cai ,  Eric H. Wingfield

    IPC分类号： G06F30/13 ,  G06F30/20

    摘要： A method for generating an infrastructure management plan is described. The method may include determining, via a Regional Traffic Simulation (RTS) model, an opportunity area for connected and automated vehicle (CAV) integrated traffic flow. Generating a regional key performance indicator associated with the opportunity area and modeling a regional KPI associated with local traffic in the opportunity area using a Local Traffic Simulation (LTS) model. The method may further include determining a local KPI associated with the opportunity area, generating a tentative traffic solution associated with the opportunity area, connecting the LTS model to the RTS model using an outer feedback loop, and determining a ripple effect of the tentative traffic solution via the RTS model. The method concludes with generating the infrastructure management plan comprising the change to the LTS model responsive to confirming an improvement to the regional KPI and the local KPI.

    SYSTEMS AND METHODS TO CLASSIFY A ROAD BASED ON A LEVEL OF SUPPPORT OFFERED BY THE ROAD FOR AUTONOMOUS DRIVING OPERATIONS
    8.
    发明申请
    SYSTEMS AND METHODS TO CLASSIFY A ROAD BASED ON A LEVEL OF SUPPPORT OFFERED BY THE ROAD FOR AUTONOMOUS DRIVING OPERATIONS 有权

    公开(公告)号：US20220363287A1

    公开(公告)日：2022-11-17

    申请号：US17321577

    申请日：2021-05-17

    申请人： Ford Global Technologies, LLC

    发明人： Richard Twumasi-Boakye ,  Xiaolin Cai ,  Shan Chy Chueh ,  James Fishelson ,  Archak Mittal ,  Andrea Broaddus

    IPC分类号： B60W60/00

    摘要： The disclosure generally pertains to systems and methods to classify a road based on a level of support offered by the road for autonomous driving operations. An example method may involve a computer receiving sensor data from a vehicle, the sensor data containing information about a current functional condition of a road. The computer may predict a future functional condition of the road by using a deterioration model to evaluate the sensor data. The computer may then determine a level of support offered by the road for autonomous driving operations based on the future functional condition of the road, and assign a classification to the road based on the level of support offered by the road for autonomous driving operations. The level of support offered by the road for autonomous driving operations may also be based on items such as road markings, traffic signs, traffic signals, and/or infrastructure elements.