公开(公告)号：US09449505B2

公开(公告)日：2016-09-20

申请号：US13795610

申请日：2013-03-12

Applicant: DENSO IT LABORATORY, INC.

Inventor： Osamu Masutani

IPC: G08G1/00 ,  G08G1/01

CPC classification number: G08G1/00 ,  G08G1/0112 ,  G08G1/0133 ,  G08G1/0141 ,  G08G1/0145

Abstract: Provided is a traffic congestion prediction method which is able to perform a prediction process using floating information with higher accuracy. The traffic congestion prediction method includes: a step of receiving information by a prediction device; a step of predicting a route of each floating car based on the current position information and destination information received; a step of calculating, for the each floating car, a first passing time group which is a set of respective passing times at a plurality of predetermined spots on the route predicted; a step of calculating the number of existing floating cars per link based on the first passing time group, if any of a plurality of floating cars exists on the link at a predetermined time; and a step of calculating a second passing time group by use of the number of existing floating cars and a predetermined calculation technique.

Abstract translation: 提供了能够以更高精度执行使用浮动信息的预测处理的交通拥堵预测方法。 交通拥堵预测方法包括：通过预测装置接收信息的步骤; 基于接收到的当前位置信息和目的地信息来预测每个浮动车辆的路线的步骤; 对于每个浮动车计算作为预测路线上的多个预定点处的各个通过时间的集合的第一通过时间组的步骤; 如果在预定时间内在链路上存在多个浮动车辆中的任何一个，则基于第一通过时间组计算每个链路的现有浮动车辆的数量的步骤; 以及通过使用现有浮动车辆的数量和预定的计算技术来计算第二通过时间组的步骤。

公开(公告)号：US20130253812A1

公开(公告)日：2013-09-26

申请号：US13795610

申请日：2013-03-12

Applicant: DENSO IT LABORATORY, INC.

Inventor： Osamu Masutani

IPC: G08G1/00

CPC classification number: G08G1/00 ,  G08G1/0112 ,  G08G1/0133 ,  G08G1/0141 ,  G08G1/0145

Abstract: Provided is a traffic congestion prediction method which is able to perform a prediction process using floating information with higher accuracy. The traffic congestion prediction method includes: a step of receiving information by a prediction device; a step of predicting a route of each floating car based on the current position information and destination information received; a step of calculating, for the each floating car, a first passing time group which is a set of respective passing times at a plurality of predetermined spots on the route predicted; a step of calculating the number of existing floating cars per link based on the first passing time group, if any of a plurality of floating cars exists on the link at a predetermined time; and a step of calculating a second passing time group by use of the number of existing floating cars and a predetermined calculation technique.

Abstract translation: 提供了能够以更高精度执行使用浮动信息的预测处理的交通拥堵预测方法。 交通拥堵预测方法包括：通过预测装置接收信息的步骤; 基于接收到的当前位置信息和目的地信息来预测每个浮动车辆的路线的步骤; 对于每个浮动车计算作为预测路线上的多个预定点处的各个通过时间的集合的第一通过时间组的步骤; 如果在预定时间内在链路上存在多个浮动车辆中的任何一个，则基于第一通过时间组计算每个链路的现有浮动车辆的数量的步骤; 以及通过使用现有浮动车辆的数量和预定的计算技术来计算第二通过时间组的步骤。

公开(公告)号：US08825352B2

公开(公告)日：2014-09-02

申请号：US13799892

申请日：2013-03-13

Applicant: Denso IT Laboratory, Inc. ,  Denso Corporation

Inventor： Osamu Masutani

IPC: G08G1/00 ,  G06F17/30

CPC classification number: G08G1/00 ,  G08G1/0104 ,  G08G1/0112 ,  G08G1/0129 ,  G08G1/0141

Abstract: A traffic data prediction device includes an original link traffic data storage unit (103) for storing traffic data per original link as a predetermined road link, an extended link generation unit (104) for generating an extended link from the original links, and an extended link traffic data prediction unit (108) for predicting traffic data per extended link generated in the extended link generation unit (104) by use of traffic data per original link. The extended link generation unit (104) decides the original links for generating the extended link based on data indicating a predictive accuracy of traffic data in a combined link combining the selected original links, and generates the extended link made of the decided original links as elements.

Abstract translation: 交通数据预测装置包括：原始链路业务量数据存储单元，用于存储作为预定道路链路的原始链路的业务数据;扩展链路生成单元，用于从原始链路生成扩展链路;扩展链路生成单元， 链路业务数据预测单元（108），用于通过使用每原始链路的业务数据来预测在扩展链路生成单元（104）中生成的每个扩展链路的业务数据。 扩展链路生成单元（104）基于表示组合所选择的原始链路的组合链路中的业务数据的预测精度的数据来决定用于生成扩展链路的原始链路，并且生成由所决定的原始链路作为要素的扩展链路 。