US-20230282105-A1 - SMART COMMUNICATION SYSTEM AT TRAFFIC INTERSECTIONS

US20230282105A1US 20230282105 A1US20230282105 A1US 20230282105A1US-20230282105-A1

Abstract

An electronic communications method includes receiving, by a device, electronic information. The electronic communications method also includes analyzing, by the device, the electronic information. The electronic communications method also includes determining, by the device, that the electronic information includes sound that is associated with an emergency vehicle. The electronic communications method also includes sending, by the device, an electronic command to change a traffic signal light from one color to another color.

Inventors

HOSSINI AMIR
FRIESEN HEATHER LYNN
AGAKHANI SARA
SIDHU PRABHPREET

Assignees

HOSSINI AMIR
FRIESEN HEATHER LYNN
AGAKHANI SARA
SIDHU PRABHPREET

Dates

Publication Date: 20230907
Application Date: 20220305
Priority Date: 20220305

Claims (6)

1 . An electronic communications method, comprising: receiving, by a device, electronic information; analyzing, by the device, the electronic information; determining, by the device, that the electronic information includes sound that is associated with an emergency vehicle; and sending, by the device, an electronic command to change a traffic signal light from one color to another color.
2 . The electronic communications method of claim 1 , wherein the electronic information includes sound from a siren.
3 . The electronic communications method of claim 1 , wherein the electronic information is received at a particular interval of time.
4 . The electronic communications method of claim 3 , wherein the particular interval of time is based on the location of a particular traffic signal.
5 . The electronic communications method of claim 3 , wherein the particular interval of time changes based on time of day.
6 . The electronic communication method of claim 1 , wherein the traffic signal light receives the noise information from surrounding traffic.

Description

BACKGROUND Vehicles enter traffic intersections on a routine basis. Traffic intersections usually have stop signs or a traffic lights/signalization system. Traffic lights generally work with a red, yellow, and green light system with a red-light indicating vehicles to stop and a green-light indicating vehicles to move through the intersection. In a normal traffic flow, vehicles will follow the requirements of the traffic light system. However, instances may occur where a vehicle may not be able to comply with the traffic light system requirement. For example, emergency vehicles, such as fire trucks, police cars, and ambulances, may be on their way to a medical or vehicle emergency and cannot stop at a red-light signal. Because of such situations, the emergency vehicle may go through the intersection with a red-light signal. As such, collisions may occur when emergency vehicles passing through a red-light signal may collide with another vehicle that is entering the same intersection and has a green-light signal. Accordingly, there is not an automated or near-instantaneous system that changes the red-light signal to a green-light based on a presence of an emergency vehicle that is entering a traffic intersection. BRIEF DESCRIPTION OF DRAWINGS FIGS. 1A-1B is a diagram of an example environment in which systems and/or methods described herein may be implemented; FIG. 2 is a diagram of a network environment; FIG. 3 is a diagram of an example computing device; FIG.4 is a diagram of an example system; FIG. 5 is an example flow diagram for sending and receiving noise information; FIG. 6 is an example flow diagram for analyzing noise information; FIGS. 7A and 7B are examples system for determining the source of a sound; FIG. 8 is an example system for determining the source of a sound; and FIG. 9 is an example system for determining the source of a sound. DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS The following detailed description refers to the accompanying drawings. The same reference numbers in different drawings may identify the same or similar elements. Systems, devices, and/or methods described herein may allow for changing a light indicator (e.g., red, yellow, green) for a traffic light system (e.g., also described as a traffic signal, traffic signals, or as traffic lights in the following description) based on the sound of a vehicle (e.g., a siren associated with an emergency vehicle) that will pass through an intersection associated with the traffic light system. The change in the traffic light system's light color may occur in a manner that does not require large amounts of stored data and can change the lights automatically. Furthermore, the systems, devices, and/or methods described herein may not require any systems or devices to be connected to the vehicle, such as an emergency vehicle (e.g., a police car, ambulance, fire truck, etc.). In embodiments, systems, devices, and/or methods described herein may include a microphone system, a raspberry Pi system, and an electronic learning system (e.g., an Artificial Intelligence (AI) system). In combination, these systems can (1) obtain sound information from a vehicle approaching an intersection via microphone connected to the raspberry Pi system, (2) send the sound information to an electronic learning system, (3) analyzing the sound information by the learning system, and (4) sending a decision to the raspberry Pi on whether to change the traffic light color based on the decision by the learning system. This signal is subsequently transmitted to the traffic light controller system (part of the traffic light system) to change or keep the light color of the traffic signal. Accordingly, the systems, devices, and/or methods described herein are robust and cost-effective, and simple to implement as there is no requirement to install any transmission devices onto the vehicles or on any nearby pavement. Furthermore, operating costs are reasonably low since the lowest tier of cloud computing services can be utilized for training the electronic learning system. In alternate embodiments, pre-trained models may be directly deployed to the raspberry Pi system without the need for cloud connectivity and/or a separate learning system. Furthermore, the systems, devices, and/or methods described herein are not impacted by weather conditions or poor visibility levels. FIGS. 1A to 1B show an example environment describing the communication system. As shown in FIG. 1A, an intersection between Road 1 and Road 2 is shown along with Car 1 travelling along Road 1. As shown in FIG. 1A, Signal 1 controls traffic flow on Road 1 and Signal 2 controls traffic flow on Road 2. At the particular moment in time shown in FIG. 1A, Signal 1 has a green-light while Signal 2 has a red-light. At a later time, as shown in FIG. 1B, an ambulance is travelling on Road 2 toward the intersection of Road 1 and Road 2. In this non-limiting example, a noise receiving system (e.g., a microphone that