SYSTEMS AND METHODS FOR OPTIMIZING TRANSPORTATION RESOURCES

• US 20130179205A1
• Filed: 01/10/2012
• Published: 07/11/2013
• Est. Priority Date: 01/10/2012
• Status: Abandoned Application

• Current Assignee: Eduard Slinin
• Original Assignee: Eduard Slinin
• Inventors: SLININ, Eduard
• Application Number:
  US13/347,120
• Publication Number:
  US 20130179205A1
• Time in Patent Office: Days
• US Class Current: 705/7.13
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/08 Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
• CPC Class Codes: G06Q 50/40 Business processes related to the transportation industry shipping G06Q10/083

Abstract

Systems and methods for optimizing transportation resources. The systems and methods include receiving, by a processor, a plurality of requests to pick up at a pick up location and drop off at a destination at least one item per request, storing the requests in a memory, and determining, by the processor, requests to be grouped in a vehicle to maximize at least one of vehicle and driver resources.

Claims

1. A method for optimizing transportation resources, comprising the steps of:

receiving, by a processor, a plurality of requests to pick up at a pick up location and drop off at a destination at least one item per request;

storing the requests in a memory;

determining, by the processor, requests to be grouped in a vehicle to maximize at least one of vehicle and driver resources;

reading client restrictions from the memory; and

excluding requests based on the client restrictions,

wherein each request includes a pick up time, the pick up location, a drop off time, the drop off destination, and a number of items and/or passengers,

wherein each request includes a pick up time and a drop off time and the grouping, by the processor, further comprises;

determining, by the processor, requests within a threshold pick up distance from each other;

determining, by the processor, requests within the threshold distance having pick up times within a threshold time window;

determining, by the processor, a travel time required to travel to the pick up locations and drop off destinations of the requests within the threshold distance and within the threshold time window;

determining, by the processor, an actual time by adding the travel time to an estimated start time;

determining, by the processor, requests having drop off times later than the actual time; and

routing, by the processor, requests having drop off times later than the actual time.

3. The method of claim 1, further comprising:

determining, by the processor, price zones of the pick up location and the drop off destination; and

calculating, by the processor, a price for the request based on the determined price zones.

4. The method of claim 1, further comprising converting, by the processor, the pick up location and drop off destination to Global Positioning System (GPS) coordinates.

6. The method of claim 1, wherein each request includes a number of passengers to be picked up and dropped off, the method further comprising:

determining, by the processor, a total number of passengers of the routed; and

excluding, by the processor, a request if the total number of passengers exceeds a vehicle capacity.

8. The method of claim 1, further comprising:

determining a number of grouped requests;

determining if the number of grouped requests exceeds a threshold; and

finalizing a group when the number of grouped requests is greater than the threshold.

9. The method of claim 1, wherein the maximizing of the vehicle resources is based on at least one of a travel time of a group of requests and a travel distance of a group of requests.

10. The method of claim 1, wherein the maximizing of the driver resources is based on at least one of a number of requests, a travel time of a group of requests, a travel distance of a group of requests, a total driving time of a driver, and a total driving distance of a driver.

11. The method of claim 1, further comprising:

determining if at least two requests have been previously grouped; and

grouping previously grouped requests.

12. The method of claim 1, wherein each request includes a number of passengers to be picked up and dropped off, wherein the grouping further comprises:

displaying pick up locations and drop off destinations of the requests on a map;

determining requests to be grouped based on the displayed pick up locations and drop off destinations;

assigning a vehicle type capable of transporting the total number of passengers; and

excluding requests based on client restrictions.

13. The method of claim 1, further comprising:

receiving, by the processor, a status update; and

updating, by the processor, the group based on the status update.

14. The method of claim 1, further comprising routing, by the processor, a delivery route for a plurality of requests.

15. The method of claim 14, wherein the routing is based on minimizing a travel time required to complete the plurality of requests.

16. The method of claim 14, wherein the routing is based on minimizing a travel distance required to complete the plurality of requests.

17. The method of claim 14, wherein the routing further comprises:

a) selecting from the plurality of requests a first request having an earliest drop off time;

b) determining a next request having a pick up time within a predetermined time window of a drop off time of a previous request;

c) routing the requests; and

d) repeating steps b and c until all requests have been routed.

18. The method of claim 17, further comprising excluding requests that are determined to exceed preset parameters.

19. The method of claim 16, wherein the routing further comprises:

a) selecting from the plurality of requests a first request having a closest drop off destination;

b) determining a next request having a pick up location within a predetermined distance from a drop off destination of a previous request;

c) routing the requests; and

d) repeating steps b and c until all requests have been routed.

20. The method of claim 19, further comprising excluding requests that are determined to exceed preset parameters.

21. The method of claim 14, wherein the routing further comprises:

a) determining a GPS location of an affiliate;

b) determining pick up locations of requests within a predetermined distance from the GPS location;

c) dispatching the determined requests to the affiliate; and

c) repeating steps a, b and c until all requests have been routed.

2. (canceled)

5. (canceled)

7. (canceled)

22. A system for optimizing transportation resources, comprising:

a processor configured to receive a plurality of requests to pick up at a pick up location and drop off at a destination at least one item per request and determine requests to be grouped in a vehicle to maximize at least one of vehicle and driver resources; and

a memory configured to store the requests, the determined groups, vehicle information and driver information,

wherein each request includes a pick up time, the pick up location, a drop off time, the drop off destination, and a number of items and/or passengers, and

wherein the processor is further configured to determine requests within a threshold pick up distance from each other, determine requests within the threshold distance having pick up times within a threshold time window, determine a travel time required to travel to the pick up locations and drop off destinations of the requests within the threshold distance and within the threshold time window, determine an actual time by adding the travel time to an estimated start time, determine requests having drop off times later than the actual time, and routing requests having drop off times later than the actual time.

24. The system of claim 22, wherein the processor is further configured to determine price zones of the pick up location and the drop off destination and calculate a price for the request based on the determined price zones.

25. The system of claim 22, wherein the processor is further configured to convert the pick up location and drop off destination to Global Positioning System (GPS) coordinates.

27. The system of claim 22, wherein each request includes a number of passengers to be picked up and dropped off, and wherein the processor is further configured to determine a total number of passengers of the routed requests, and excluding a request if the total number of passengers exceeds a vehicle capacity.

28. The system of claim 27, wherein the processor is further configured to read client restrictions from the memory and to exclude requests based on the client restrictions.

29. The system of claim 22, wherein the processor is further configured to determine a number of grouped requests, determine if the number of grouped requests exceeds a threshold, and finalize a group when the number of grouped requests is greater than the threshold.

30. The system of claim 22, wherein the maximizing of the vehicle resources is based on at least one of a travel time of a group of requests and a travel distance of a group of requests.

31. The system of claim 22, wherein the maximizing of the driver resources is based on at least one of a number of requests, a travel time of a group of requests, a travel distance of a group of requests, a total driving time of a driver, and a total driving distance of a driver.

32. The system of claim 22, wherein the processor is further configured to determine if at least two requests have been previously grouped, and grouping previously grouped requests.

33. The system of claim 22, wherein each request includes a number of passengers to be picked up and dropped off, and wherein the processor is further configured to display pick up locations and drop off destinations of the requests on a map, determine requests to be grouped based on the displayed pick up locations and drop off destinations, assign a vehicle type capable of transporting the total number of passengers, and exclude requests that prohibit transportation in the assigned vehicle type.

34. The system of claim 22, wherein the processor is further configured to receive a status update, and update the group based on the status update.

35. The system of claim 22, wherein the processor is further configured to route a delivery route for a plurality of requests.

36. The system of claim 35, wherein the routing is based on minimizing a travel time required to complete the plurality of requests.

37. The system of claim 35, wherein the routing is based on minimizing a travel distance required to complete the plurality of requests.

38. The system of claim 37, wherein the processor is further configured to:

a) select from the plurality of requests a first request having an earliest drop off time;

b) determine a next request having a pick up time within a predetermined time window of a drop off time of a previous request,

c) route the requests, and

d) repeat steps b and c until all requests have been routed.

39. The system of claim 38, wherein the processor is further configured to exclude requests that are determined to exceed preset parameters.

40. The system of claim 35, wherein the processor is further configured to:

a) select from the plurality of requests a first request having a closest drop off destination;

b) determine a next request having a pick up location within a predetermined distance from a drop off destination of a previous request,

c) route the requests, and

d) repeat steps b and c until all requests have been routed.

41. The system of claim 40, wherein the processor is further configured to exclude requests that are determined to exceed preset parameters.

42. The system of claim 35, wherein the processor is further configured to:

a) determine a GPS location of an affiliate;

b) determine pick up locations of requests within a predetermined distance from the GPS location;

c) dispatch the determined requests to the affiliate; and

d) repeat steps a, b and c until all requests have been routed.

23. (canceled)

26. (canceled)

43. (canceled)

44. (canceled)