Savari, Inc.

Abstract:

This provides
methods and systems for V2X applications, such as forward collision warning,
electronic emergency brake light, left turn assist, work zone warning, signal
phase timing, and others, mainly relying on a GNSS positioning solution
transmitted via the Dedicated Short-Range Communications (DSRC) to/from the
roadside units and onboard units in other V2X-enabled vehicles. However, the
positioning solution from a GNSS may be deteriorated by noise and/or bias due
to various error sources, e.g., time delay, atmospheric effect, ephemeris
effect, and multipath effect. This offers a novel quality filter that can
detect noise and the onset of drift in GNSS signals by evaluating up to four
metrics that compare the qualities of kinematic variables, speed, heading angle
change, curvature, and lateral displacement, obtained directly or derived from
GNSS and onboard vehicle sensors. This is used for autonomous cars and vehicle
safety, with various examples/variations.

Claim 1: 

A method for positioning quality filter for a global navigation system for a vehicle, said method comprising:

a central computer receiving global positioning system location data;

said central computer receiving sensors data from vehicle sensors;

said sensors data from said vehicle sensors comprises data from a vehicle speed sensor, a vehicle direction sensor, and a vehicle yaw rate sensor on said vehicle;

said central computer calculating a first metric value based on said sensors data from said vehicle sensors, based on said vehicle speed, said vehicle direction, and said vehicle yaw rate;

a processor receiving a first threshold;

said processor comparing said first metric value with said first threshold;

after determining that said first metric value is larger than or equal to said first threshold, said processor receiving a second threshold;

a) said central computer calculating a second metric value;

b) said processor comparing said second metric value with said second threshold;

c) after determining that said second metric value is smaller than said second threshold, said processor receiving a third threshold;

a. said central computer calculating a third metric value;

b. said processor comparing said third metric value with said third threshold;

c. after determining that said third metric value is larger than or equal to said third threshold, said processor receiving a fourth threshold;

a. said central computer calculating a fourth metric value;

b. said processor comparing said fourth metric value with said fourth threshold;

c. after determining that said fourth metric value is smaller than said fourth threshold, said processor setting said global navigation system value as valid;

said central computer validating said global positioning system location data 9 using said global navigation system value, for safety, operation, or navigation of said vehicle;

said central computer sending a notice to a vehicle warning device;

said central computer correcting a navigation of said vehicle;

said central computer adjusting direction of said vehicle.

Abstract:

In one example, we describe a method and infrastructure for DSRC V2X (vehicle to
infrastructure plus vehicle) system. In one example, some of connected vehicle
applications require data from infrastructure road side equipment (RSE).
Examples of such applications are road intersection safety application which
mostly requires map and traffic signal phase data to perform the appropriate
threat assessment. The examples given cover different dimensions of the above
issue: (1) It provides methods of RSE of interest selection based solely on the
derived relative geometric data between the host vehicle and the RSE’s, in
addition to some of the host vehicle data, such as heading. (2) It provides
methods of RSE of interest selection when detailed map data is communicated or
when some generic map data is available. (3) It provides methods of RSE of
interest selection when other vehicles data is available. Other variations and
cases are also given.

Claim 1: 

A method for selecting road side equipment for controlling vehicles in a highway or street, said method comprising:
a central computer receiving a total value which indicates number of road side equipment pieces that a first vehicle is able to receive data from;
said central computer determining a type of data a first road side equipment piece transmits or supports;
said central computer receiving a location of said first road side equipment piece from an input device;
a certification device or module examining security validation of a certificate for said first road side equipment piece;
said central computer receiving a location of said first vehicle;
said central computer receiving dynamics information about said first vehicle;
said central computer receiving a location of a second vehicle near said first vehicle from a location determination device or module;
said central computer analyzing said total value which indicates number of road side equipment pieces that said first vehicle is able to receive data from, said type of data said first road side equipment piece transmits or supports, said location of said first road side equipment piece, said security validation of said certificate for said first road side equipment piece, said location of said first vehicle, said dynamics information about said first vehicle, and said location of said second vehicle near said first vehicle; and
said central computer selecting said first road side equipment piece based on said analyzing step.

Abstract

In one example, we
describe a method and infrastructure for DSRC V2X (vehicle to infrastructure
plus vehicle) system. This can cover a communication circle up to 800 m, and in
some cases 1000 m, and as a result, in congested traffic areas, the onboard unit
is communicating with high number of units and may end up saturating its
processing capability very quickly. In one example, the task is to provide
different levels of node filtering algorithms to intelligently select the node
data to be processed. This results in optimally using the available processing
power by only processing the data of the desired nodes. This method is based on
combination of range, velocity, heading, direction, transmitted power, received
power threshold, and map database, if available. This also reduces the V2X
communication congestion problem resulted in high number of one-to-many nodes
communication.

Claim 1: 
A method for node adaptive filtering and congestion control for automated vehicles in highways, said method comprising:

a region boundary module defining a dynamic region of interest for a host vehicle, wherein said dynamic region of interest has a range, wherein said range is a function of absolute or relative position and absolute or relative velocity of said host vehicle and a remote vehicle;

a position determination device indicating a latitude coordinate and a longitudinal coordinate for said host vehicle;

said position determination device indicating a latitude coordinate and a longitudinal coordinate for said remote vehicle;

a processor calculating a delta latitude value based on said range;

said processor calculating a delta longitudinal value based on said delta latitude value and said host vehicle’s latitude coordinate;

said processor calculating a first difference, wherein said first difference is absolute value of difference between said host vehicle’s latitude coordinate and said remote vehicle’s latitude coordinate;

said processor calculating a second difference, wherein said second difference is absolute value of difference between said host vehicle’s longitudinal coordinate and said remote vehicle’s longitudinal coordinate;

a comparison module comparing said first difference with said delta latitude value; and

said comparison module comparing said second difference with said delta longitudinal value.