Method and apparatus for end-to-end travel time estimation using dynamic traffic data
View Patent ↗The present invention is a method and an apparatus for end-to-end travel time estimation using dynamic traffic data. In one embodiment, a method for estimating a fastest route between a first point in a transportation network and a second point in the transportation network includes receiving static data relating to static characteristics of a first zone and a second zone in the transportation network. In addition, real-time data relating to real-time traffic conditions in the first zone is also received. The static and real-time data is processed in accordance with at least one fine-grained load-generation technique to generate a first load for the first zone, and the static data is generated in accordance with at least one coarse-grained load-generation technique to generate a second load for the second zone. These first and second loads are then combined, converted to travel times, and scaled to facilitate the identification of a best or fastest route.
1. A method for estimating a fastest route between a first point in a transportation network and a second point in the transportation network, the method comprising:
receiving static data relating to static characteristics of a first zone and at least a second zone in said transportation network;
receiving real-time data relating to real-time traffic conditions in said first zone;
processing said static data and said real-time data in accordance with at least one fine-grained load-generation technique to generate a first load for said first zone, said first load comprising a number of vehicles traveling in said first zone per a unit of time; and
processing said static data in accordance with at least one coarse-grained load-generation technique to generate a second load for said second zone, said second load comprising a number of vehicles traveling in said second zone per a unit of time,
wherein said fastest route is estimated based on said first load and said second load.
2. The method of claim 1 , wherein said static data comprises at least one of: link load estimates, statistical traffic patterns, static origin-destination trip tables and static maps.
3. The method of claim 1 , wherein said real-time data comprises at least one of: current traffic condition data, real-time traffic condition data, environmental data and radio-based incident data.
4. The method of claim 1 , wherein said at least one fine-grained load-generation technique is at least one of: dynamic traffic assignment, a queuing network, simulation, a probabilistic local technique and flow propagation.
5. The method of claim 1 , wherein said at least one coarse-grained load-generation technique is at least one of: a template method, statistical traffic classification, traffic assignment, simulation and a probabilistic local technique.
6. The method of claim 1 , wherein said first zone is an urban zone or a regional zone.
7. The method of claim 1 , wherein said second zone is a rural zone or an inter-urban zone.
8. The method of claim 1 , further comprising:
combining said first load and said second load to generate network-wide loads.
9. The method of claim 8 , wherein said combining further comprises:
converting said network-wide loads to corresponding estimated travel times.
10. The method of claim 9 , further comprising:
scaling said estimated travel times in accordance with at least one relevant incident in said transportation network.
11. The method of claim 10 , wherein said at least one relevant incident is at least one of: a traffic accident in said transportation network, occurrence at a point of interest in said transportation network, construction occurring in said transportation network and a weather condition in said transportation network.
12. The method of claim 10 , further comprising:
identifying said fastest route in accordance with said scaled travel times.
13. A computer readable medium containing an executable program for estimating a fastest route between a first point in a transportation network and a second point in the transportation network, where the program performs the steps of:
receiving static data relating to static characteristics of a first zone and at least a second zone in said transportation network;
receiving real-time data relating to real-time traffic conditions in said first zone;
processing said static data and said real-time data in accordance with at least one fine-grained load-generation technique to generate a first load for said first zone, said first load comprising a number of vehicles traveling in said first zone per a unit of time; and
processing said static data in accordance with at least one coarse-grained load-generation technique to generate a second load for said second zone, said second load comprising a number of vehicles traveling in said second zone per a unit of time,
wherein said fastest route is estimated based on said first load and said second load.
14. The computer readable medium of claim 13 , wherein said static data comprises at least one of: link load estimates, statistical traffic patterns, static origin-destination trip tables and static maps.
15. The computer readable medium of claim 13 , herein said real-time data comprises at least one of: current traffic condition data, real-time traffic condition data, environmental data and radio-based incident data.
16. The computer readable medium of claim 13 , wherein said at least one fine-grained load-generation technique is at least one of: dynamic traffic assignment, a queuing network, simulation, a probabilistic local technique and flow propagation.
17. The computer readable medium of claim 13 , wherein said at least one coarse-grained load-generation technique is at least one of: a template method, statistical traffic classification, traffic assignment, simulation and a probabilistic local technique.
18. The computer readable medium of claim 13 , further comprising:
combining said first load and said second load to generate network-wide loads;
converting said network-wide loads to corresponding estimated travel times; and
scaling said estimated travel times in accordance with at least one relevant incident in said transportation network.
19. The computer readable medium of claim 18 , further comprising:
identifying said fastest route in accordance with said scaled travel times.
20. Apparatus for estimating a fastest route between a first point in a transportation network and a second point in the transportation network, the apparatus comprising:
means for receiving static data relating to static characteristics of a first zone and at least a second zone in said transportation network;
means for receiving real-time data relating to real-time traffic conditions in said first zone;
means for processing said static data and said real-time data in accordance with at least one fine-grained load-generation technique to generate a first load for said first zone, said first load comprising a number of vehicles traveling in said first zone per a unit of time; and
means for processing said static data in accordance with at least one coarse-grained load-generation technique to generate a second load for said second zone, said second load comprising a number of vehicles traveling in said second zone per a unit of time,
wherein said fastest route is estimated based on said first load and said second load.