Autonomous vehicle and method of controlling the same

• US 10,782,701 B2
• Filed: 07/29/2016
• Issued: 09/22/2020
• Est. Priority Date: 07/30/2015
• Status: Active Grant

• Current Assignee: Samsung Electronics Co. Ltd.
• Original Assignee: Samsung Electronics Co. Ltd.
• Inventors: Cronin, John, Wilson, Dylan Jonathan
• Primary Examiner(s): Camby, Richard M
• Application Number:
  US15/744,330
• Publication Number:
  US 20180203455A1
• Time in Patent Office: 1,516 Days
• Field of Search: None
• CPC Class Codes: B60W 2050/146 Display means
• CPC Class Codes: B60W 2420/403 Image sensing, e.g. optical camera
• CPC Class Codes: B60W 2530/209 Fuel quantity remaining in tank
• CPC Class Codes: B60W 2540/221 Physiology, e.g. weight, heartbeat, health or special needs
• CPC Class Codes: B60W 2540/229 Attention level, e.g. attentive to driving, reading or sleeping
• CPC Class Codes: B60W 2540/26 Incapacity
• CPC Class Codes: B60W 2552/00 Input parameters relating to infrastructure
• CPC Class Codes: B60W 2555/20 Ambient conditions, e.g. wind or rain
• CPC Class Codes: B60W 2555/60 Traffic rules, e.g. speed limits or right of way
• CPC Class Codes: B60W 2556/45 External transmission of data to or from the vehicle
• CPC Class Codes: B60W 2556/50 of positioning data, e.g. GPS [Global Positioning System] data
• CPC Class Codes: B60W 50/14 Means for informing the driver, warning the driver or prompting a driver intervention
• CPC Class Codes: B60W 60/0011 involving control alternatives for a single driving scenario, e.g. planning several paths to avoid obstacles
• CPC Class Codes: B60W 60/0021 specially adapted for travel time
• CPC Class Codes: B60W 60/0053 from vehicle to occupant
• CPC Class Codes: B60W 60/0059 Estimation of the risk associated with autonomous or manual driving, e.g. situation too complex, sensor failure or driver incapacity
• CPC Class Codes: G01C 21/3415 Dynamic re-routing, e.g. recalculating the route when the user deviates from calculated route or after detecting real-time traffic data or accidents
• CPC Class Codes: G01C 21/3461 Preferred or disfavoured areas, e.g. dangerous zones, toll or emission zones, intersections, manoeuvre types, segments such as motorways, toll roads, ferries
• CPC Class Codes: G01C 21/3492 employing speed data or traffic data, e.g. real-time or historical traffic control systems for road vehicles involving transmission of navigation instructions to the vehicle G08G1/0968
• CPC Class Codes: G05D 1/0217 in accordance with energy consumption, time reduction or distance reduction criteria
• CPC Class Codes: G05D 1/0246 : using a video camera in combination with image processing means
• CPC Class Codes: G05D 1/0276 : using signals provided by a source external to the vehicle involving a plurality of vehicles G05D1/0287; automatically controlling vehicle speed responsive to externally generated signals B60K31/0058

Abstract

Provided is a method including monitoring an event occurring on a path along which an autonomous vehicle is currently travelling by using information obtained while the autonomous vehicle is travelling and determining whether to travel along a detour path when the event is detected. In particular, the method includes determining whether to travel along the detour path according to a cost incurred when the autonomous vehicle travels along the detour path.

Claims

1. An autonomous vehicle comprising:

an interface configured to monitor an event occurring on a first path while the autonomous vehicle travels along the first path in an autonomous driving mode; and

a processor configured to obtain a second path when the event is detected, and determine whether to travel along the second path in the autonomous driving mode by comparing a first cost expected when the autonomous vehicle travels along the first path with a second cost expected when the autonomous vehicle travels along the second path,

wherein when a difference between the first cost and the second cost is greater than a threshold value, the processor determines that the autonomous vehicle is to travel, in a manual driving mode, in an event area in which the event is detected.

2. The autonomous vehicle of claim 1, wherein the processor is configured to determine that, when the difference between the first cost and the second cost is equal to or less than the threshold value, the autonomous vehicle is to travel along the second path in the autonomous driving mode.

3. The autonomous vehicle of claim 1, wherein when the difference between the first cost and the second is greater than the threshold value, the processor provides a notice indicating that the autonomous driving mode is to be stopped, and when a response to the notice is received, the processor determines that the autonomous vehicle is to travel, in the manual driving mode, in the event area in which the event is detected.

4. The autonomous vehicle of claim 3, wherein when the response to the notice is not received, the processor controls the autonomous vehicle that is travelling to stop.

5. The autonomous vehicle of claim 3, wherein when the response to the notice is not received, the processor determines that the autonomous vehicle is to travel along the second path in the autonomous driving mode.

6. The autonomous vehicle of claim 1, wherein when the difference between the first cost and the second cost is greater than the threshold value, the processor controls the autonomous vehicle that is travelling to stop.

7. The autonomous vehicle of claim 1, wherein the event indicates that the event area in which the autonomous vehicle is determined to travel in the manual driving mode is on the first path.

8. The autonomous vehicle of claim 1, wherein the interface monitors the event by using a road sign on the first path obtained by a camera included in the autonomous vehicle.

9. The autonomous vehicle of claim 1, wherein the interface monitors the event by using travel environment information about the first path received from an external device.

10. The autonomous vehicle of claim 1, wherein the processor obtains the second path that is one of a plurality of detour paths according to priorities of the plurality of detour paths that replace the first path.

11. The autonomous vehicle of claim 1, wherein when the difference between the first cost comprising a first travel time or a first travel distance expected when the autonomous vehicle travels along the first path and the second cost comprising a second travel time or a second travel distance expected when the autonomous vehicle travels along the second path is equal to or less than the threshold value, the processor determines that the autonomous vehicle is to travel along the second path in the autonomous driving mode.

12. The autonomous vehicle of claim 1, wherein when the difference between the first cost and the second cost is equal to or less than the threshold value and a travel distance expected when the autonomous vehicle travels along the second path is less than a drivable distance, the processor determines that the autonomous vehicle is to travel along the second path in the autonomous driving mode.

13. The autonomous vehicle of claim 1, wherein the processor obtains schedule information of a rider of the autonomous vehicle, and when the difference between the first cost and the second cost is equal to or less than the threshold value and an arrival time expected when the autonomous vehicle travels along the second path is before a time of the schedule information, determines that the autonomous vehicle is to travel along the second path in the autonomous driving mode.

14. The autonomous vehicle of claim 1, wherein the processor obtains rider state information indicating whether a rider of the autonomous vehicle is able to drive the autonomous vehicle, and determines whether to travel along the second path in the autonomous driving mode by further considering the rider state information.

15. A method of controlling an autonomous vehicle, the method comprising:

monitoring an event occurring on a first path while the autonomous vehicle travels along the first path in an autonomous driving mode;

obtaining a second path when the event is detected; and

determining whether to travel along the second path in the autonomous driving mode by comparing a first cost expected when the autonomous vehicle travels along the first path with a second cost expected when the autonomous vehicle travels along the second path,

wherein the determining whether to travel along the second path in the autonomous driving mode comprises, when a difference between the first cost and the second cost is greater than a threshold value, determining that the autonomous vehicle is to travel, in a manual driving mode, in an event area in which the event is detected.

16. The method of claim 15, wherein the determining whether to travel along the second path in the autonomous driving mode comprises, when the difference between the first cost and the second cost is equal to or less than the threshold value, determining that the autonomous vehicle is to travel along the second path in the autonomous driving mode.

17. A non-transitory computer-readable recording medium having embodied thereon a program for executing the method of any of claim 15.