Description:CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] The Application claims the benefit of and priority to India provisional application no. 202241074589, filed on December 22, 2022, the contents of which are incorporated herein by reference in their entirety.
[0002] The Application claims the benefit of and priority to US application no. 18/338,418, filed on June 21, 2023, the contents of which are incorporated herein by reference in their entirety.
TECHNICAL FIELD
[0003] The disclosure described herein generally relates to the computation of a complexity score (CS) and the use of the CS to optimally allocate entities to routes. More particularly, the disclosure relates to the computation of a CS using vehicle-based and/or other suitable alerts and collected data, which is then combined with a performance score to provide a context-sensitive view of the performance score to assist in assigning entities, such as drivers, vehicles, etc., to respective routes.
BACKGROUND
[0004] Software as a service (or SaaS) is a way of delivering applications over the Internet—as a service. Thus, instead of installing and maintaining software, users simply access it via the Internet, providing freedom from complex software and hardware management. SaaS applications are sometimes called Web-based software, on-demand software, or hosted software. In any event, SaaS applications run on a SaaS provider’s servers. Typically, the SaaS provider manages access to the application, including security, availability, and performance.
[0005] One implementation of SaaS is with respect to online fleet management, which may be utilized for commercial vehicle fleets such those used by the transportation and shipping industry. In this context, SaaS applications leverage onboard devices installed in fleet vehicles to continuously scan the road and cabin environment, and then provide the driver with in-cabin audio and visual alerts in real time. The data collected via the onboard devices is then sent to the SaaS server(s). The fleet manager is able to receive insight via a user interface, which may be with respect to driver monitoring, road safety, driving habits, collision information, etc. In this way, the data obtained via a vehicle’s onboard devices may assist a fleet operator in the allocation of a driver or vehicle to a particular route. Other management utilities may be configured to facilitate the allocation of entities other than vehicles or drivers to routes, which may include those implemented in the context of autonomous mobile robot (AMR) route and task allocation. However, in each of these cases, the manner in which such allocations are currently performed is inadequate.
BRIEF DESCRIPTION OF THE DRAWINGS/FIGURES
[0006] The accompanying drawings, which are incorporated herein and form a part of the specification, illustrate the present disclosure and, together with the description, further serve to explain the principles and to enable a person skilled in the pertinent art to make and use the implementations as discussed herein.
[0007] FIG. 1 illustrates a vehicle in accordance with the disclosure;
[0008] FIG. 2 illustrates components of a safety system of a vehicle in accordance with the present disclosure;
[0009] FIG. 3 illustrates a block diagram indicating data received from a host of sources used to compute the complexity score (CS), in accordance with the disclosure;
[0010] FIG. 4 illustrates a map showing road segments, in accordance with the disclosure;
[0011] FIG. 5 illustrates a table summarizing the difference in various scores for drivers over segments that make up a route, in accordance with the disclosure;
[0012] FIG. 6 illustrates a block diagram of an environment that includes autonomous mobile robots (AMRs), in accordance with the disclosure;
[0013] FIG. 7 illustrates a computing device, in accordance with the disclosure; and
[0014] FIG. 8 illustrates a process flow, in accordance with the disclosure.
[0015] The present disclosure will be described with reference to the accompanying drawings. The drawing in which an element first appears is typically indicated by the leftmost digit(s) in the corresponding reference number.
DETAILED DESCRIPTION
[0016] In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present disclosure. However, it will be apparent to those skilled in the art that the implementations of the disclosure, including structures, systems, and methods, may be practiced without these specific details. The description and representation herein are the common means used by those experienced or skilled in the art to most effectively convey the substance of their work to others skilled in the art. In other instances, well-known methods, procedures, components, and circuitry have not been described in detail to avoid unnecessarily obscuring the disclosure.
, C , Claims:1. A computing device, comprising:
a memory configured to store computer-readable instructions; and
a processor configured to execute the computer-readable instructions stored in the memory to cause the computing device to:
receive data from a vehicle of a route comprising a plurality of road segments, the data comprising (i) environment-based data, and (ii) drive assist alerts;
compute, from the data, a road complexity score (RCS) for one or more of the plurality of road segments;
compute, for one or more of a plurality of entities, a qualifying allocation score for the route based upon the RCS computed for the respective one or more of the plurality of road segments; and
determine an allocation of an entity from the plurality of entities to a subsequent route based upon the respective qualifying allocation score of each of the plurality of entities.