Fuel-saving path planning navigation system and fuel-saving path planning method thereof

• US 8,762,050 B2
• Filed: 09/07/2011
• Issued: 06/24/2014
• Est. Priority Date: 09/07/2011
• Status: Active Grant

• Current Assignee: National Tsing Hua University
• Original Assignee: National Tsing Hua University
• Inventors: Chen, Wen-Tsuen, Chen, Po-Yu, Guo, Yi-Min
• Primary Examiner(s): Tran, Khoi
• Assistant Examiner(s): MOTT, ADAM R
• Application Number:
  US13/227,095
• Publication Number:
  US 20130060469A1
• Time in Patent Office: 1,021 Days
• Field of Search: 701/408, 701/409, 701/410, 701/411, 701/412, 701/414, 701/415, 701/416, 701/423, 701/424, 701/425, 701/527
• US Class Current: 701/414
• CPC Class Codes: G01C 21/3469 Fuel consumption; Energy use; Emission aspects

Abstract

A fuel-saving path planning navigation system and a fuel-saving path planning method thereof. A plurality of sensors monitors a plurality of roads respectively and periodically report traffic information to a server. The server comprises a storing module and a processing module. The storing module stores the traffic information as history information. The processing module estimates how many vehicles on a road based upon the history information, calculates fuel consumption of each possible planned path including current fuel consumption based on real-time traffic and future fuel consumption based on the historical information, and plans a most fuel-efficient path. Also, the processing module recalculates fuel consumption of remaining path and changes the remaining path while fuel cost of a new path better 10% than the remaining path.

Claims

1. A fuel-saving path planning navigation system, comprising:

a plurality of sensors monitoring a plurality of roads respectively and periodically reporting traffic information to a server, wherein the plurality of sensors detect average speed of vehicles on the plurality of roads, and the plurality of sensors report the traffic information with different cycles according to peak and off-peak periods;

in the peak period, a first detection cycle is assigned to the plurality of sensors;

in the off-peak period, a second detection cycle, which is longer than the first detection cycle, is assigned to the plurality of sensors;

the server comprising;

a storing module storing the traffic information as history information, which includes the average speed of vehicles;

a processing module estimating how many vehicles on one of the plurality of roads based upon the history information, calculating fuel consumption of each possible planned path including current fuel consumption based on real-time traffic and future fuel consumption based on the historical information, and planning a most fuel-efficient path based on a following relation;

F_x=ρ

×

F_x,N+(1−

ρ

)×

F_x,H;

wherein F_x is a fuel consumption of a road x, ρ

is a real number between 0 and 1, F_x,N is a real time fuel consumption of the road x, and F_{x, H}is a fuel consumption from the history information of the road x;

wherein the processing module further determines whether to planning a new most fuel-efficient path based on the real-time traffic while driving on the most fuel-efficient path;

wherein the most fuel-efficient path is kept if the fuel consumption of the new most fuel-efficient path is not 10% better than the most fuel-efficient path.

2. The fuel-saving path planning navigation system as claimed in claim 1, wherein the sensors keep monitoring and reporting the traffic information to the server, and the processing module recalculates fuel consumption of remaining path and changes the remaining path while fuel cost of a new path better 10% than the remaining path.

3. The fuel-saving path planning navigation system as claimed in claim 1, wherein the traffic information includes a section identity, a velocity of the road x and a reporting time.

4. The fuel-saving path planning navigation system as claimed in claim 1, wherein the processing module estimating how many vehicles on a road further based upon a traffic flow theory and a following relation is satisfied:

D=C×

e^bVx;

wherein D is car density of the road x, V_x is an average velocity of the road x, and C and b are variables related to the history information.

5. The fuel-saving path planning navigation system as claimed in claim 4, wherein the processing module further calculates fuel cost based on a fuel cost function and a following relation of the fuel cost function is satisfied:

6. The fuel-saving path planning navigation system as claimed in claim 5, wherein the processing module further computes a weighted number of vehicles K_x and a following relation is satisfied:

7. The fuel-saving path planning navigation system as claimed in claim 6, wherein the processing module further uses K_x to calculate a speed of the road x and L_x is a length of the road x and a following relation is satisfied:

8. The fuel-saving path planning navigation system as claimed in claim 7, wherein the processing module further uses V_x,H to calculate the future fuel consumption of the road x at a time t and L_x is the length of the road x and a following relation is satisfied:

9. A fuel-saving path planning method, comprising following steps:

monitoring a plurality of roads respectively and periodically reporting traffic information to a server by a plurality of sensors, wherein the plurality of sensors detect average speed of vehicles on the plurality of roads, and the plurality of sensors report the traffic information with different cycles according to peak and off-peak periods;

in the peak period, a first detection cycle is assigned to the plurality of sensors;

in the off-peak period, a second detection cycle, which is longer than the first detection cycle, is assigned to the plurality of sensors;

storing the traffic information as history information, which includes the average speed of vehicles, to a storing module;

estimating how many vehicles on one of the plurality of roads based upon the history information by a processing module;

calculating fuel consumption of each possible planned path including current fuel consumption based on real-time traffic and future fuel consumption based on the historical information by the processing module; and

planning a most fuel-efficient path by the processing module based on a following relation;

F_x=ρ

×

F_x,N+(1−

ρ

)×

F_x,H;

wherein F_x is a fuel consumption of a road x, ρ

is a real number between 0 and 1, F_x,N is a real time fuel consumption of the road x, and F_{x, H} is a fuel consumption from the history information of the road x;

determining whether to planning a new most fuel-efficient path based on the real-time traffic while driving on the most fuel-efficient path, wherein the most fuel-efficient path is kept if the fuel consumption of the new most fuel-efficient path is not 10% better than the most fuel-efficient path.

10. The fuel-saving path planning method as claimed in claim 9, further comprising the following step:

using the sensors to keep monitoring and reporting the traffic information to the server; and

recalculating fuel consumption of remaining path and changing the remaining path by the processing module while fuel cost of a new path better 10% than the remaining path.

11. The fuel-saving path planning method as claimed in claim 9, wherein the traffic information includes a section identity, a velocity of the road x and a reporting time.

12. The fuel-saving path planning method as claimed in claim 9, wherein the processing module estimates how many vehicles on a road further based upon a traffic flow theory and a following relation is satisfied:

D=C×

e^bVx;

wherein D is car density of the road x, V_x is an average velocity of the road x, and C and b are variables related to the history information.

13. The fuel-saving path planning method as claimed in claim 12, wherein the processing module further calculates fuel cost based on a fuel function and a following relation of the fuel cost function is satisfied:

14. The fuel-saving path planning method as claimed in claim 13, wherein the processing module further computes a weighted number of vehicles K_x and a following relation is satisfied:

15. The fuel-saving path planning method as claimed in claim 14, wherein the processing module further uses K_x to calculate a speed of the road x and L_x is a length of the road x and a following relation is satisfied:

16. The fuel-saving path planning method as claimed in claim 15, wherein the processing module further uses V_x,H to calculate the future fuel consumption of the road x at a time t and L_x is the length of the road x and a following relation is satisfied: