Abstract: Methods and systems to dynamically and optimally sequence routes based on historical and real-time traffic conditions, and to predict anticipated traffic conditions along the dynamically generated route are disclosed. Route sequencing may be based on a set of predefined constraints, e.g., distance, time, time with traffic, or any objective cost function. The system of the present invention may be implemented in a vehicle fleet comprising one or more vehicles with one or more depots, or with no depots. An optimization server obtains real-time, historical and/or predicted future traffic, weather, hazard, and avoidance-zone data on road segments to generate a route, while staying within parameters and constraints set by an automatic machine learning process, an artificial intelligence program, or a human administrator. The platform may be coupled to sensors positioned on roads, e.g., speed radar or camera, and sensors positioned in vehicles, e.g., GPS system or on-board diagnostic sensor.

Abstract: Methods and systems to dynamically and optimally sequence routes based on historical and real-time traffic conditions, and to predict anticipated traffic conditions along the dynamically generated route are disclosed. Route sequencing may be based on a set of predefined constraints, e.g., distance, time, time with traffic, or any objective cost function. The system of the present invention may be implemented in a vehicle fleet comprising one or more vehicles with one or more depots, or with no depots. An optimization server obtains real-time, historical and/or predicted future traffic, weather, hazard, and avoidance-zone data on road segments to generate a route, while staying within parameters and constraints set by an automatic machine learning process, an artificial intelligence program, or a human administrator. The platform may be coupled to sensors positioned on roads, e.g., speed radar or camera, and sensors positioned in vehicles, e.g., GPS system or on-board diagnostic sensor.

Abstract: Methods and systems for monitoring and interacting with a collection of geospatially aware assets, or any connected geo-location enabled device, through a virtual reality interface are disclosed. A diagram may be utilized as a real-time route progress indicator to determine a route's completion status and as a destination position indicator to determine the position of a destination among all destinations of a route. The virtual reality environment may provide the benefit of, and ability to, modify the visual field, such as to fit a large number of routes, e.g., 50,000 or more, onto an area viewable in the virtual reality environment to efficiently manage large fleets, or to divide a screen into a plurality of individual screens to organize the data in a visually effective manner. The user interface may be personalized for the user, or customized for a specific business operation.

Abstract: Methods and systems directed to an autonomous bi-directional integration of telematics platforms, e.g., different APIs, through protocol transforming, standardizing, and/or integrating of machine telematics data and/or Internet-of-Things (IoT) data. The platform permits seamless merging of disparate telematics and IoT data streams and resources into a single interface, removing the need to connect to propriety systems individually, and allowing an administrator to concurrently track and manage hundreds of millions of vehicles in a centralized system. Through the process of integrating and standardizing telematics and IoT resources, a custom universal data format may be defined. Machines, vehicles, and IoT devices may establish communications and data links through the platform of the present invention, in which each machine, vehicle, and/or IoT device shares, or fuses, sensor data. To accomplish the objectives of the present invention, signal mapping from one protocol to another protocol may be employed.

Abstract: Methods and systems directed to an autonomous bi-directional integration of telematics platforms, e.g., different APIs, through protocol transforming, standardizing, and/or integrating of machine telematics data and/or Internet-of-Things (IoT) data. The platform permits seamless merging of disparate telematics and IoT data streams and resources into a single interface, removing the need to connect to propriety systems individually, and allowing an administrator to concurrently track and manage hundreds of millions of vehicles in a centralized system. Through the process of integrating and standardizing telematics and IoT resources, a custom universal data format may be defined. Machines, vehicles, and IoT devices may establish communications and data links through the platform of the present invention, in which each machine, vehicle, and/or IoT device shares, or fuses, sensor data. To accomplish the objectives of the present invention, signal mapping from one protocol to another protocol may be employed.

Abstract: Systems and methods for geocoding coordinates of users, vehicles and destinations on a map, and to identify when a transit vehicle deviates from a system generated driving route are disclosed. As the transit vehicle travels along the route, its actual path of travel may be compared to an optimal driving route generated by the system to obtain route deviation data. The route deviation data and/or road network data may be filtered to remove data noise and further analyzed to build a profile of a driver operating a transit vehicle. A digital signature identifying at least one pattern of behavior and/or operating characteristic associated with a specific driver operating a vehicle is further developed, and may be used to allow a system administrator of a vehicle fleet to filter out, or filter for, specific driver types based on driving behaviors that may be suitable for a particular operation.

Abstract: Methods and systems for monitoring and interacting with a collection of geospatially aware assets, or any connected geo-location enabled device, through a virtual reality interface are disclosed. A diagram may be utilized as a real-time route progress indicator to determine a route's completion status and as a destination position indicator to determine the position of a destination among all destinations of a route. The virtual reality environment may provide the benefit of, and ability to, modify the visual field, such as to fit a large number of routes, e.g., 50,000 or more, onto an area viewable in the virtual reality environment to efficiently manage large fleets, or to divide a screen into a plurality of individual screens to organize the data in a visually effective manner. The user interface may be personalized for the user, or customized for a specific business operation.

Abstract: Methods and systems for an autonomous supply and distribution chain management network are disclosed. A server may control and coordinate the processes involved in distributing a product from suppliers to the customers, including generation of purchase orders and payment of invoices. A defined set of interactions may occur in a particular sequence and at designated times that may permit the chain to be synchronized between a customer and a supplier. Unlike a regular supply and distribution chain, in which human beings decide vehicle or asset compatibility types, the autonomous chain of the present invention may maintain a compatibility database within the platform, as well as detailed information about each asset and how it can function interactively with the others. The invention may also allow for dynamic modification of transit operations to alter one or more destinations of the inventory while it is in transit to a new location at any time.

Abstract: Methods and systems to dynamically and optimally sequence routes based on historical and real-time traffic conditions, and to predict anticipated traffic conditions along the dynamically generated route are disclosed. Route sequencing may be based on a set of predefined constraints, e.g., distance, time, time with traffic, or any objective cost function. The system of the present invention may be implemented in a vehicle fleet comprising one or more vehicles with one or more depots, or with no depots. An optimization server obtains real-time, historical and/or predicted future traffic, weather, hazard, and avoidance-zone data on road segments to generate a route, while staying within parameters and constraints set by an automatic machine learning process, an artificial intelligence program, or a human administrator. The platform may be coupled to sensors positioned on roads, e.g., speed radar or camera, and sensors positioned in vehicles, e.g., GPS system or on-board diagnostic sensor.

Abstract: Systems and methods for geocoding coordinates of users, vehicles and destinations on a map, and to identify when a transit vehicle deviates from a system generated driving route are disclosed. As the transit vehicle travels along the route, its actual path of travel may be compared to an optimal driving route generated by the system to obtain route deviation data. The route deviation data and/or road network data may be filtered to remove data noise and further analyzed to build a profile of a driver operating a transit vehicle. A digital signature identifying at least one pattern of behavior and/or operating characteristic associated with a specific driver operating a vehicle is further developed, and may be used to allow a system administrator of a vehicle fleet to filter out, or filter for, specific driver types based on driving behaviors that may be suitable for a particular operation.

Abstract: Methods and systems to dynamically and optimally sequence routes based on historical and real-time traffic conditions, and to predict anticipated traffic conditions along the dynamically generated route are disclosed. Route sequencing may be based on a set of predefined constraints, e.g., distance, time, time with traffic, or any objective cost function. The system of the present invention may be implemented in a vehicle fleet comprising one or more vehicles with one or more depots, or with no depots. An optimization server obtains real-time, historical and/or predicted future traffic, weather, hazard, and avoidance-zone data on road segments to generate a route, while staying within parameters and constraints set by an automatic machine learning process, an artificial intelligence program, or a human administrator. The platform may be coupled to sensors positioned on roads, e.g., speed radar or camera, and sensors positioned in vehicles, e.g., GPS system or on-board diagnostic sensor.

Abstract: Methods and systems for monitoring and interacting with a collection of geospatially aware assets, or any connected geo-location enabled device, through a virtual reality interface are disclosed. A diagram may be utilized as a real-time route progress indicator to determine a route's completion status and as a destination position indicator to determine the position of a destination among all destinations of a route. The virtual reality environment may provide the benefit of, and ability to, modify the visual field, such as to fit a large number of routes, e.g., 50,000 or more, onto an area viewable in the virtual reality environment to efficiently manage large fleets, or to divide a screen into a plurality of individual screens to organize the data in a visually effective manner. The user interface may be personalized for the user, or customized for a specific business operation.