| CPC G05D 1/0219 (2013.01) [G05D 1/0088 (2013.01); G05D 1/0214 (2013.01)] | 23 Claims |

|
1. A systematic intelligent system (SIS), comprising a system intelligent unit (SIU) configured to serve roadside intelligent units (RIUs) and vehicle intelligent units (VIUs), wherein said SIU comprises:
(a) a storage unit comprising a storage device with a historical database that records historical data generated during trips and/or records historical data describing historical traffic conditions, historical road conditions, and/or historical information describing the route on other similar trips; and
(b) a computing unit comprising a distribution manager and computing devices, wherein the distribution manager supplements computing resources of VIUs and RIUs; allocates tasks to VIUs and RIUs; and optimizes computing resources of RIUs and VIUs by allocating tasks and computing resources to RIUs and VIUs;
wherein the SIS connects, manages, and controls a number of different automated driving systems (ADSes) that are provided by different manufacturers and/or a number of different ADSes that are provided by different ADS service providers;
wherein the SIS manages control of a vehicle comprising a VIU by a plurality of different ADSes and thereby facilitates automated driving of the vehicle;
wherein said distribution manager is configured to optimize RIU resources;
wherein said distribution manager is configured to allocate resources from an idle RIU having spare resources to an RIU having insufficient resources;
wherein each ADS of said plurality of ADSes comprises one or more of an RIU, a traffic control center, and/or a cloud component;
wherein the SIS is configured to provide a pre-trip service, said pre-trip service is configured to train a model describing a trip, and said model is trained using historical data generated during previous trips to provide a trained model;
wherein said trained model provides an optimized allocation of resources and functions among the SIU, the RIU, and the VIU; and
wherein said pre-trip service is configured to perform a calibration and optimization function that calibrates and optimizes parameters of a profile model for a trip.
|