Traffic-Volume Prediction Device and Method

• US 20150179064A1
• Filed: 08/08/2012
• Published: 06/25/2015
• Est. Priority Date: 08/08/2012
• Status: Active Grant

• Current Assignee: Hitachi, Ltd.
• Original Assignee: Hitachi, Ltd.
• Inventors: Hiruta, Tomoaki, Kato, Manabu, Okude, Mariko
• Granted Patent: US 9,240,124 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G08G 1/0112 from the vehicle, e.g. floating car data [FCD]
• CPC Class Codes: G08G 1/0129 for creating historical data or processing based on historical data
• CPC Class Codes: G08G 1/0141 for traffic information dissemination

Abstract

Because a route selection model for traffic demand prediction of selecting a route from among travel routes in probe data cannot include other routes than the travel route in the probe data, it is not possible to predict a traffic volume on the route that has not been traveled. A traffic-volume prediction device according to the invention includes a simple-network creation device (130) that makes a simple network connecting principal intersections extracted from travelling loci in the collected probe data, a model creation device (140) that determines a utility between the principal intersections based on the data of the travelling loci and calculates a selection probability for each principal intersection based on the utility, and a traffic-volume assignment device (160) that distributes a traffic volume to the routes between the principal intersections according to the selection probability and thereby uses it as the traffic volume for each route candidate to be a traffic demand prediction object.

Claims

1. A traffic-volume prediction device that predicts a traffic volume between points using travelling locus data of a vehicle collected in advance, comprising:

a network creation device that extracts principal intersections based on a proportion of a maximum ramification number to a number passing through a traveling locus between intersections on a travel route in the travelling locus data and creates a simple network connecting the principal intersections one another,

a model creation device that calculates a utility of a route between the principal intersections based on a property value between the principal intersections and estimates a parameter of a route selection model for evaluating a selection probability at each principal intersection based on the utility, and

a traffic-volume assignment device that calculates the selection probability of selecting the route between the principal intersections based on the estimated parameter of the route selection model and distributes the traffic volume to the route for predicting the traffic demand based on the selection probability.

2. The traffic-volume prediction device according to claim 1,

wherein the model creation device uses at least one of a travel time and a travel distance between the principal intersections obtained from the travelling locus data as the property value of the route between a principal intersection on the simple network and a plurality of principal intersections connected thereto.

3. The traffic-volume prediction device according to claim 1,

wherein the traffic-volume assignment device performs a simulation in which the same number of vehicles as the traffic volume assumed from the origin point to the destination point run on the simple network at random based on the selection probability of the principal intersection, and the quantity of vehicles running between the principal intersections is assumed as a predicted traffic volume between the principal intersection or between roads.

4. The traffic-volume prediction device according to claim 3,

wherein the traffic-volume prediction device obtains information including a site of occurrence of an event and influence of the site of occurrence on the traffic, and

the traffic-volume assignment device updates the selection probability between a plurality of principal intersections by applying the influence on the traffic to the utility function for the principal intersections corresponding to the route passing through the site of occurrence of the event among the plurality of principal intersections, and distributes the traffic volume based on the updated selection probability.

5. A traffic-volume prediction method of predicting a traffic volume between points using travelling locus data of a vehicle collected in advance, comprising the steps of:

network creation processing of extracting principal intersections based on a proportion of a maximum ramification number to a number passing through a traveling locus between intersections on a travel route in the travelling locus data and creating a simple network connecting the principal intersections one another,

model creation processing of calculating a utility of a route between the principal intersections based on a property value between the principal intersections based on the travelling locus data and estimating a parameter of a route selection model for evaluating a selection probability at each principal intersection based on the utility, and

traffic-volume assignment processing of calculating the selection probability of selecting the route between the principal intersections based on the parameter of the route selection model estimated at the model creation processing and distributing the traffic volume to the route for predicting the traffic demand based on the selection probability.

6. The traffic-volume prediction method according to claim 5,

wherein the model creation processing uses at least one of a travel time and a travel distance between the principal intersections obtained from the travelling locus data as the property value of the route between a principal intersection on the simple network and a plurality of principal intersections connected thereto.

7. The traffic-volume prediction method according to claim 5,

wherein the traffic-volume assignment processing performs a simulation in which the same number of vehicles as the traffic volume assumed from the origin point to the destination point run on the simple network at random based on the selection probability of the principal intersection, and assumes the quantity of vehicles running between the principal intersections as a predicted traffic volume between the principal intersection or between roads.

8. The traffic-volume prediction method according to claim 7,

wherein in the traffic-volume prediction method, information is obtained including a site of occurrence of an event and influence of the site of occurrence to the traffic, and

the traffic-volume assignment processing updates the selection probability between a plurality of principal intersections by applying the influence on the traffic to the utility function for the principal intersections corresponding to the route passing through the site of occurrence of the event among the plurality of principal intersections, and distributes the traffic volume based on the updated selection probability.