GM Cruise Holdings LLC (San Francisco, CA)
After seeing lightning, parents often instruct their children to measure the distance between a thunderstorm and the location of the storm. A count of “Mississippi” is approximately one second. That means that any child who hears thunder and sees lightning will have counted the time between the moment the lightning (or light) reached their location and the time that the thunder reached their location. The distance of an event in miles can be calculated by multiplying the total number of seconds counted by five. The sound travels about one mile per second.
It can be difficult to pinpoint the precise location of events where an object emits light or sound. For instance, “Mississippi”, which is merely a number representing the time needed to count, might not be accurate. Second the sound travels at 4.7 minutes per mile. Thus, even with accurate time measurement, the above estimate will always be a bit off by around 5%.
Although a child might see lightning during an event and be able to count, an observer may not be able to calculate the distance of an explosion or fireworks that have been illegally launched. The viewer might not anticipate the explosion or fireworks and this may hinder the ability of the observer to count.
Therefore, pinpointing the place of the event can be difficult.
Another example is that some technologies use triangulation with at least three sensors of same type to pinpoint the exact location of an event. Three microphones are able to detect the sound of a bang for example. A processor will be able to determine how sound waves hit various microphones at different levels and times , and determine the source of the bang was originating from. It may not be capable of determining the source of the sound using this method of analysis.
Furthermore, in one instance as to how event determination affects autonomous vehicles (“AVs”) in the present, AVs are able to pull over towards the right side of the road when the audio or visual sensors in the AV detect emergency lighting or sirens that are activated by an emergency vehicle.However the emergency vehicle could be far from the AV so that it is not required to stop. The behavior of an AV could be improved by accurately locating the emergency vehicle currently using its emergency lights or siren.
The above scenarios deal with distance, but they do not contemplate directionality of the event.
To handle the situation above, a plurality of sensor arrays can be mounted on a frame, such as a roof of a car. When one or more sensors in a first sensor array detects a physical property of an event (e.g., a camera detects a flash of light), a processor records a current time as a time-based first timestamp. If the first array of sensors employs 360.degree. The processor can then determine the directionality of an event using the identification of a sensor in the first array of sensors that initially detected it. A sensor or several sensors in another array of sensor arrays may be adjusted to detect the direction of an event in some implementations. When one or more sensors of the second sensor array senses a second physical aspect of the event (e.g. when a microphone detects the sound of a boom) the current time is recorded as a second timestamp.
The event’s first and second physical properties are related. A conclusion can be drawn from the first and second physical properties. In other words, it’s possible to discern the direction, distance, or where the event occurred by modeling how the first physical property as well as the second physical property are propagated from the event to the sensor array space.
A processor can determine the time interval between the first and the second one. The processor also can determine the physical and identity of the event. The processor can also determine a speed difference between the rates of transmission of both physical properties throughout space. The processor is able to calculate the distance between events using the physical properties of the first and second, such as by multiplying speed by the time difference.
The processor is able determine a geolocation of the event, in relation to the location of the chassis upon which the first and second sensor arrays are placed, the directionality of the event and a distance of the event. For instance, if the location of the chassis is specified in an approximately Cartesian system (such as the global positioning system coordinates) the processor could identify the Cartesian coordinates of the event by considering the distance as a hypertenuse of the right triangle, that is based upon theCartesian system, where the hypotenuse extends to the direction of events’ direction.
Phrased differently, the processor can determine an X-displacement based on the geolocation of the chassis through finding the product of (i) the distance of the event and (ii) the sine of the directionality. The processor can calculate aY displacement using the geolocation of a chassis by finding (i) distance to the event and (ii) the sine of directionality.
The processor will determine the location of the event after modifiing the geolocation using the determined X/Y-displacement. The environment provides background information and details about the likely source of an event. The processor is able to take actions based on the incident’s location or the setting in which it is occurring. This could include making an emergency or not-so-urgent number for the first responders, or directing an AV to the side.
The methods described herein could be particularly advantageous for accurately determining the exact location of an event which involves sound and light emission from some or all of the objects or by occurrence of an event. This benefit is particularly evident when object or objects are blocked visually. A light sensor array is able to detect or partially detect EMVs (Emergency Medical Vehicles), for example.
Many physical properties can be sensed by different sensors, so an event described in the different implementations could have multiple distinct characteristics. An object referred to by the different implementations may emit various physical properties that may be sensed by different types of sensors. One or more processors or circuitry can perform detection (e.g., classification or identification) of the physical property based on signals or data generated by sensors. A circuitry or processor could detect if the sensor’s data or signals indicate that the property exists. The sensor can detect the physical property if the sensor generates signals that indicate its presence. You can deduce or deduce information about an event using the detections of different physical properties, if you possess a model or understanding of them.Click here to view the patent on USPTO website.
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2. Utilize these terms to locate relevant Cooperative Patent Classifications at the Classification Text Search Tool. To find the most appropriate classification for your invention, go through the classification’s class Schemes (class schedules). Consider substituting the words you’re using to describe your invention if you do not get any results from the Classification Text Search with synonyms such as the terms you used in step 1.
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