Advanced threat warning for autonomous vehicles

Patent metadata

Field	Value
Publication number	US-10580296-B2
Application number	US-201716461200-A
Country	US
Kind code	B2
Filing date	Dec 6, 2017
Priority date	Dec 6, 2016
Publication date	Mar 3, 2020
Grant date	Mar 3, 2020

Abstract

Methods, apparatuses, systems, and non-transitory computer readable storage media for generating risk indicators are described. The disclosed technology includes determining a vehicle route of a vehicle and external object routes of external objects. The vehicle route is determined using vehicle route data including a vehicle location and a vehicle destination. The external object routes are determined using external object route data including external object locations and external object destinations. Based on a comparison of the vehicle route data and the external object route data, external object routes that satisfy a proximity criterion are determined. Risk data for the vehicle is generated based on a vehicle state of the vehicle and external object states of the external objects corresponding to the external object routes that satisfy the proximity criterion. In response to determining that the risk data satisfies a risk criterion, at least one risk indicator is generated.

First claim

What is claimed is:

1. A method for generating risk indicators, the method comprising:
determining a vehicle route of a vehicle using vehicle route data including a current vehicle location, a current vehicle destination, and historical vehicle route data;
determining external object routes of external objects using external object route data including current external object locations, current external object destinations, and historical external object route data;
comparing the vehicle route data to the external object route data to determine external object routes that satisfy a proximity criterion, the external object routes that satisfy the proximity criterion being within a predefined proximity of the vehicle route during a predefined time period that is determined using past time periods associated with the vehicle;
generating risk data for the vehicle based on a vehicle state of the vehicle and external object states of the external objects corresponding to the external object routes that satisfy the proximity criterion, the risk data including any of proximity information, severity information, and probability information associated with an adverse event; and
in response to determining that the risk data satisfies a risk criterion, generating at least one risk indicator including a risk type.

2. The method of claim 1 , further comprising:
generating traffic flow data based on the external object route data including velocities, densities, and relative locations of external objects corresponding to the external object routes that satisfy the proximity criterion; and
in response to determining that the traffic flow data satisfies a traffic flow criterion, generating external object indicators of the external objects corresponding to the external object routes that satisfy the proximity criterion.

3. The method of claim 1 , further comprising:
receiving sensor data from sensors of any of the vehicle and the external objects, wherein any of the vehicle state and the external object states are based on the sensor data.

4. The method of claim 1 , further comprising:
generating traffic control device data based on a state of one or more traffic control devices located along the vehicle route; and
in response to determining, based on the traffic control device data, that at least one of the one or more traffic control devices is malfunctioning, determining a malfunction type of the one or more traffic control devices, the risk data including the malfunction type.

5. The method of claim 1 , further comprising:
determining a route condition using route condition data of the vehicle route and the external object routes;
modifying the risk data using the route condition data; and
generating route condition indicators, using the route condition data, for the vehicle route and the external object routes that satisfy the proximity criterion.

6. The method of claim 5 , wherein the route condition data includes any of vehicle stoppage data, construction activity data, lane closure data, road surface condition data, pedestrian activity data, and traffic signal timing data.

7. The method of claim 1 , further comprising:
determining, based on the external object route data, a time period during which a congestion event is occurring in a predetermined area including a portion of the vehicle route; and
in response to determining that a time the vehicle will enter the predetermined area corresponds to the time period during which the congestion event is occurring, generating one or more congestion indicators for external objects within the portion of the vehicle route.

8. A risk indicator apparatus comprising:
a memory; and
a processor configured to execute instructions stored in the memory to:
determine a vehicle route of a vehicle using vehicle route data including a current vehicle location, a current vehicle destination, and historical vehicle route data;
determine external object routes of external objects using external object route data including current external object locations, current external object destinations, and historical external object route data;
compare the vehicle route data to the external object route data to determine external object routes that satisfy a proximity criterion, the external object routes that satisfy the proximity criterion being within a predefined proximity of the vehicle route during a predefined time period that is determined using past time periods associated with the vehicle;
generate risk data for the vehicle based on a vehicle state of the vehicle and external object states of the external objects corresponding to the external object routes that satisfy the proximity criterion, the risk data including any of proximity information, severity information, and probability information associated with an adverse event; and
in response to determining that the risk data satisfies a risk criterion, generate at least one risk indicator including a risk type.

9. The risk indicator apparatus of claim 8 , wherein the processor is further configured to execute instructions stored in the memory to:
generate traffic flow data based on the external object route data including velocities, densities, and relative locations of external objects corresponding to the external object routes that satisfy the proximity criterion; and
in response to determining that the traffic flow data satisfies a traffic flow criterion, generate external object indicators of the external objects corresponding to the external object routes that satisfy the proximity criterion.

10. The risk indicator apparatus of claim 8 , wherein the processor is further configured to execute instructions stored in the memory to:
receive sensor data from sensors of any of the vehicle and the external objects, wherein any of the vehicle state and the external object states is based on the sensor data.

11. The risk indicator apparatus of claim 8 , wherein the processor is further configured to execute instructions stored in the memory to:
generate traffic control device data based on a state of one or more traffic control devices located along the vehicle route; and
in response to determining, based on the traffic control device data, that at least one of the one or more traffic control devices is malfunctioning, determine a malfunction type of the one or more traffic control devices, the risk data including the malfunction type.

12. The risk indicator apparatus of claim 8 , wherein the processor is further configured to execute instructions stored in the memory to:
determine a route condition using route condition data of the vehicle route and the external object routes;
modify the risk data using the route condition data; and
generate route condition indicators, using the route condition data, for the vehicle route and the external object routes that satisfy the proximity criterion.

13. The risk indicator apparatus of claim 12 , wherein the route condition data includes any of vehicle stoppage data, construction activity data, lane closure data, road surface condition data, pedestrian activity data, and traffic signal timing data.

14. The risk indicator apparatus of claim 8 , wherein the processor is further configured to execute instructions stored in the memory to:
determine, based on the external object route data, a time period during which a congestion event is occurring in a predetermined area including a portion of the vehicle route; and
in response to determining that a time the vehicle will enter the predetermined area corresponds to the time period during which the congestion event is occurring, generate one

Assignees

• Nissan North America Inc
• Nasa

Inventors

• Pedersen Liam
• Sierhuis Maarten
• Utz Hans
• Penna Mauro Della
• Fong Terrence
• Allan Mark
• Bualat Maria
• Schafer Eric

Classifications

• B60W30/0956 Primary

  the prediction being responsive to traffic or environmental parameters · CPC title

• G08G1/096791

  where the origin of the information is another vehicle · CPC title

• G08G1/096708

  where the received information might be used to generate an automatic action on the vehicle control · CPC title

• G01C21/3691

  Retrieval, searching and output of information related to real-time traffic, weather, or environmental conditions (arrangements for giving variable traffic instructions G08G1/09) · CPC title

• G01C21/3697

  Output of additional, non-guidance related information, e.g. low fuel level (G01C21/3679 takes precedence) · CPC title