US 2017/0323249 A1 · COMPLEX DYNAMIC ROUTE SEQUENCING FOR MULTI-VEHICLE FLEETS USING TRAFFIC AND REAL-WORLD CONSTRAINTS

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.

Claims20

Dependent claims

A machine-implemented method, comprising:

receiving for a segment of a road at least one of a traffic data, a weather data, a hazard data and an avoidance zone data,
wherein the at least one of a traffic data, a weather data, a hazard data, and an avoidance zone data comprise at least one of a real-time data, a historical data, and a predictive data,
wherein the historical data matches with a current circumstance;
predicting a current traffic condition and a future traffic condition based on the at least one of a traffic data, a weather data, a hazard data, and an avoidance zone data;
sequencing one or more driving routes comprising a plurality of user vehicles and a plurality of destinations based on one of a shortest travel time, a shortest distance, a shortest distance based on the current traffic condition and the future traffic condition, and an objective cost function,
wherein the driving route obeys one or more predetermined constraints,
wherein the driving route is based on a future time that the driving route will be implemented;
and
generating one or more driving directions based on the sequenced one or more driving routes.

6 more elements

A machine-implemented method, comprising:

receiving for a segment of a road at least one of a traffic data, a weather data, a hazard data and an avoidance zone data;
predicting a current traffic condition and a future traffic condition based on the at least one of a traffic data, a weather data, a hazard data, and an avoidance zone data;
sequencing one or more driving routes comprising a plurality of user vehicles and a plurality of destinations based on one of a shortest travel time, shortest distance, and shortest distance based on the current traffic condition and the future traffic condition, and an objective cost function;
generating a driving direction based on the sequenced driving route;
and
repeating the steps of receiving data, predicting the current traffic condition and the future traffic condition, sequencing the driving route and generating the driving direction at a predetermined time interval, or as real-time data change, or as one or more constraints are modified, or based on one or more configured triggers.

3 more elements

Dependencies are inferred from the claim text.

Complex dynamic route sequencing for multi-vehicle fleets using traffic and real-world constraints

Life of this patent

Complex dynamic route sequencing for multi-vehicle fleets using traffic and real-world constraints

Life of this patent

Abstract

Claims20