Method for predicting traffic space mean speed and traffic flow rate, and method and apparatus for controlling isolated traffic light signaling system through predicted traffic flow rate
First Claim
1. A method for predicting a spatial mean speed and a traffic flow rate, comprising the steps of:
- defining a measurement section on a road;
acquiring an image of a vehicle stream within said measurement section;
obtaining spatial vehicle pattern from said image;
calculating a traffic density and a correction coefficient for a distribution pattern of vehicle flow based upon said spatial vehicle pattern; and
predicting a spatial mean speed of a group of vehicles traveling on the road and a traffic flow rate on the road based on said traffic density and said correction coefficient, wherein said correction coefficient is equal to a value obtained by dividing a first difference between a current entropy and a minimum possible entropy by a second difference between said minimum possible entropy and a maximum possible entropy, said current entropy being calculated based on a space headway of vehicles within the measurement section when the image is acquired, said minimum possible entropy being a function of a number of said vehicles within the measurement section and being calculated on an assumption that said number of said vehicles are evenly distributed within the measurement section, and said maximum available entropy being a function of said number of said vehicles and being calculated on an assumption that said number of said vehicles are located within a single jammed group in the measurement section.
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Abstract
A method for predicting a traffic flow rate at a point on a road to control a traffic light signaling system measures a traffic density on the road to predict a traffic flow rate by utilizing the fact that a velocity of a vehicle on the road is restricted by an interval between successive vehicles, since the traffic density is locally increased when the vehicle interval is not uniform and therefore the spatial mean speed is lowered. This method offers higher accuracy by utilizing a correction coefficient obtained from an actual vehicle distribution, for instance, a coefficient derived from entropy. An apparatus for controlling a traffic light signaling system installed on a point of a road by utilizing this predicting method, thereby smoothing a traffic condition, includes video cameras for picking up images of a traffic condition at an upper stream of an intersection, an A/D converter for converting an analog video output signal into a digital video signal, two sets of image memories for storing digital image data about two scenes imaged by the video cameras at a proper time interval, an image processing unit for extracting moving objects from the images, a data process/control unit for calculating a total number of vehicles within a predetermined area and each space headway, whereby a vehicle distribution pattern is recognized an a correction coefficient is calculated, and an input/output unit for interfacing with the traffic light signaling system installed on the road.
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Citations
9 Claims
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1. A method for predicting a spatial mean speed and a traffic flow rate, comprising the steps of:
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defining a measurement section on a road; acquiring an image of a vehicle stream within said measurement section; obtaining spatial vehicle pattern from said image; calculating a traffic density and a correction coefficient for a distribution pattern of vehicle flow based upon said spatial vehicle pattern; and predicting a spatial mean speed of a group of vehicles traveling on the road and a traffic flow rate on the road based on said traffic density and said correction coefficient, wherein said correction coefficient is equal to a value obtained by dividing a first difference between a current entropy and a minimum possible entropy by a second difference between said minimum possible entropy and a maximum possible entropy, said current entropy being calculated based on a space headway of vehicles within the measurement section when the image is acquired, said minimum possible entropy being a function of a number of said vehicles within the measurement section and being calculated on an assumption that said number of said vehicles are evenly distributed within the measurement section, and said maximum available entropy being a function of said number of said vehicles and being calculated on an assumption that said number of said vehicles are located within a single jammed group in the measurement section. - View Dependent Claims (4, 5)
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2. A traffic light controlling method comprising the steps of:
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defining a measurement section in a vehicle stream of a road which approaches a traffic light provided on the road, said traffic light having a green light with a green light turn-ON minimum time and a green light turn-ON maximum time which are predetermined for said traffic light; when the green light of the traffic light is turned ON, acquiring a first image of a portion of said vehicle stream which lies within the measurement section, calculating a number of traveling vehicles from said first image, and modifying said green light turn-ON minimum time based upon the number of traveling vehicles; after said green light turn-ON minimum time, acquiring a second image of said portion of said vehicle stream which lies within the measurement section, obtaining a spatial vehicle stream pattern from said first and second images, calculating a traffic density and a vehicle stream distribution from said spatial vehicle stream pattern, calculating a correction coefficient based on said traffic density and said vehicle stream distribution, predicting a traffic flow rate of the road based upon said traffic density and said correction coefficient, and, in accordance with said traffic flow rate, (i) turning the green light OFF when said traffic flow rate is smaller than a predetermined threshold value, and (ii) keeping the green light turned ON when said traffic flow rate is greater than said predetermined threshold value; and turning OFF the green light when said green light turn-ON maximum time has passed, wherein said correction coefficient is equal to a value obtained by dividing a first difference between current entropy and a minimum possible entropy by a second difference between said minimum possible entropy and a maximum possible entropy, said current entropy being calculated based on a space headway of vehicles within the measurement section, said minimum possible entropy being a function of a number of vehicles within the measurement section and being calculated on an assumption that said number of vehicles are evenly distributed within the measurement section, said maximum possible entropy being a function of said number of vehicles and being calculated on an assumption that said number of vehicles are located within a single jammed group within the measurement section. - View Dependent Claims (6, 7)
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3. A traffic light controlling apparatus for controlling a traffic light signaling system provided on an intersection, comprising:
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a video camera for imaging a traffic condition in a vehicle stream approaching said intersection to sequentially produce a first analog video signal related to a first screen and a second analog video signal related to a second screen after a predetermined time interval; an A/D converter for converting said first analog video signal and said second analog video signal into a first digital image signal and a second digital image signal; a first image memory for storing therein said first digital image signal; a second image memory for storing therein said second digital image signal; image processing means for image-processing said first digital image signal inputted from said first image memory and said second digital image signal inputted from said second image memory to extract at least one traveling vehicle within a measurement section in the image and for producing a third digital image signal representative of said at least one traveling vehicle; input/output means coupled to said traffic light signaling system, for receiving data of a traffic light condition of said traffic light signaling system; and data process/control means for receiving said data of said traffic light condition from said input/output means and said third digital image signal from said image processing means, for calculating a total number of traveling vehicles within said measurement section and intervals between front ends of adjacent ones of said vehicles in accordance with said data of said traffic light condition and said third digital image signal, for calculating a correction coefficient and a traffic density based upon said total number and said intervals, thereby deriving a predicted traffic flow rate, and for producing a control signal used to control said traffic light signaling system based on said total number of traveling vehicles and said predicted traffic flow rate, said input/output means transferring said control signal to said traffic light signaling system, wherein said correction coefficient is equal to a value obtained by dividing a first difference between a current entropy and a minimum possible entropy by a second difference between said minimum possible entropy and a maximum possible entropy, said current entropy being calculated based on said intervals, said minimum possible entropy being a function of said total number of traveling vehicles and being based on an assumption that said total number of traveling vehicles are evenly distributed within the measurement section, and said maximum possible entropy being a function of said total number of traveling vehicles and being calculated on an assumption that said total number of traveling vehicles are located within a single jammed group within the measurement section. - View Dependent Claims (8, 9)
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Specification