CN104504898A - Online map matching method based on floating car data on tunnel road section - Google Patents

Online map matching method based on floating car data on tunnel road section Download PDF

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Publication number
CN104504898A
CN104504898A CN201410752436.6A CN201410752436A CN104504898A CN 104504898 A CN104504898 A CN 104504898A CN 201410752436 A CN201410752436 A CN 201410752436A CN 104504898 A CN104504898 A CN 104504898A
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China
Prior art keywords
road
section
road section
tunnel
map matching
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CN201410752436.6A
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Chinese (zh)
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王东宇
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Priority to CN201410752436.6A priority Critical patent/CN104504898A/en
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    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0108—Measuring and analyzing of parameters relative to traffic conditions based on the source of data
    • G08G1/0112—Measuring and analyzing of parameters relative to traffic conditions based on the source of data from the vehicle, e.g. floating car data [FCD]

Abstract

The invention discloses an online map matching method based on floating car data on a tunnel road section. Road space-time accessibility and behavior model weight information based on fuzzy logic of a vehicle on the tunnel road section are introduced, and the difference of behavior models of the vehicle when traveling on tunnel road section and an auxiliary road is analyzed. The map matching process framework of the tunnel road section is established, and a computing method of connection weights is given out through the construction of a time series directed graph. The matching precision of the method exceeds 90%, and the method can be used for traffic information processing of city tunnel roads.

Description

Based on the tunnel road Online Map matching process of floating car data
Technical field
The present invention relates to tunnel road Online Map matching process, particularly based on the tunnel road Online Map matching process of floating car data.
Background technology
Along with expanding economy, the increase of automobile pollution, urban traffic jam is more and more serious.In order to realize urban transportation shunting, alleviate urban traffic blocking, building city tunnel more and more becomes the Important Action addressed this problem, and the collection of tunnel road information of vehicles is significant for the issue of whole urban traffic information.In recent years, floating car technology is developed rapidly at intelligent transportation field as the advanced technology means obtaining Traffic Information, the research that domestic and international existence is correlated with in a large number, the solution of Floating Car map match model race, comprises the first Matching Model of road, parallel direction road Identification model, node matching model and delay match model.
Curve Matching and the algorithm frame based on probability analysis model, introduce the path determining algorithm based on fuzzy logic and shortest path first; Based on a map-matching method for extensive history gps data post-processed, but the method can not meet the demand of transport information real-time release; Towards a global map matching algorithm for low sampling rate gps data, algorithm have employed space-time analysis method and generates a candidate figure, and will have the section sequence of the highest matching score as final matching results; Based on a map-matching algorithm for crossing data structure, for solving the matching problem at urban intersection place.
Existing in a large number for the research of map match mainly towards city ordinary road, based on the singularity in city tunnel section, when existing research does not consider that vehicle travels in tunnel road and auxiliary road, the otherness of traffic behavior, cannot be applicable to tunnel road map match.
Summary of the invention
For problems of the prior art, the object of the present invention is to provide a kind of driving path that can identify vehicle according to real time GPS information, differentiate whether vehicle travels the tunnel road Online Map matching process based on floating car data in tunnel road.
In order to achieve the above object, the present invention is by the following technical solutions: based on the tunnel road Online Map matching process of floating car data, step comprises:
1) accessibility of road space-time is judged;
2) select the behavior pattern of tunnel road vehicle, mate with Online Map.
When former and later two continuous candidate road section are that same section or former and later two continuous candidate road section are different sections of highway and the terminal in first section is communicated with in topology with the starting point in second section in step 1), road space-time has accessibility.
Step 2) in pair time ask in sequence digraph all connecting lines having accessibility mark and carry out connection weight assignment, W gi, Gi+1(L m, L n)=W gi(L m)+W gi+1(L n), W in formula gi, Gi+1(L m, L n) represent anchor point gicandidate road section L mto anchor point gi+1candidate road section L nconnection weight, W g(L) the coupling weight of the candidate road section L of anchor point G is represented.
After adopting technique scheme, the present invention has following beneficial effect: the driving path that can identify vehicle according to real time GPS information, differentiates whether vehicle travels in tunnel road.
Embodiment
According to specific embodiment, the present invention is further explained below.
This patent guarantees that the starting point of tunnel road point sequence to be matched and terminal are confidence point (cP), simultaneously in conjunction with the concept of maximum delay constraint dynamic time windows (MDCDTW).Utilize confidence point and maximum delay constraint dynamic time windows effectively can not only eliminate propagated error and improve matching precision, coupling real-time demand can also be met.Wherein MDCDTW comprises three parts: point sequence WP 1. etc. to be matched; 2. WP corresponding candidate road section collection wL; 3. self-defining maximum delay constraint D.
When vehicle travels at simple road network, utilize simple matching algorithm just can obtain good matching effect, and when vehicle travels when the road network of high complexity, as tunnel, overbridge, viaduct etc., only consider that single anchor point information is difficult to realize correct coupling.This patent is based on the thought in section, a kind of point sequence matching process being applicable to long-time interval floating car data for tunnel road is proposed, the driving trace information (being made up of GPS point sequence) of the method comprehensive vehicle, geometry and topology information, by the path of finding coupling weight summation maximum as final coupling section.Method is divided into two parts: 1. road space-time can reach Sui; 2. tunnel road vehicle behavior pattern.
Based on the tunnel road Online Map matching process of floating car data, step comprises:
1) accessibility of road space-time is judged;
2) select the behavior pattern of tunnel road vehicle, mate with Online Map.
When former and later two continuous candidate road section are that same section or former and later two continuous candidate road section are different sections of highway and the terminal in first section is communicated with in topology with the starting point in second section in step 1), road space-time has accessibility.
Step 2) in pair time ask in sequence digraph all connecting lines having accessibility mark and carry out connection weight assignment, W gi, Gi+1(L m, L n)=W gi(L m)+W gi+1(L n), W in formula gi, Gi+1(L m, L n) represent anchor point gicandidate road section L m
To anchor point gi+1candidate road section L nconnection weight, W g(L) the coupling weight of the candidate road section L of anchor point G is represented.
In wL, to be the necessary condition of the ingredient of optimal path be for section: a certain section that this section candidate road section adjacent with the next one is concentrated meets road space-time reachability requirements.Therefore, road space-time accessible detecting to be carried out to the section that any pair is concentrated in neighboring candidate section.And if only if when two detected sections can meet road space-time reachability requirements completely, is just that the connecting line between them gives accessibility mark, has the connection weight assignment that this mark just can carry out next step.

Claims (3)

1., based on the tunnel road Online Map matching process of floating car data, it is characterized in that step comprises:
1) accessibility of road space-time, is judged;
2), select the behavior pattern of tunnel road vehicle, mate with Online Map.
2. the tunnel road Online Map matching process based on floating car data according to claim 1, is characterized in that road space-time has accessibility when former and later two continuous candidate road section are that same section or former and later two continuous candidate road section are different sections of highway and the terminal in first section is communicated with in topology with the starting point in second section in step 1).
3. the tunnel road Online Map matching process based on floating car data according to claim 1, is characterized in that step 2) in pair time ask in sequence digraph all connecting lines having accessibility mark and carry out connection weight assignment, W gi, Gi+1(L m, L n)=W gi(L m)+W gi+1(L n), W in formula gi, Gi+1(L m, L n) represent anchor point gicandidate road section L m
To anchor point gi+1candidate road section L nconnection weight, W g(L) the coupling weight of the candidate road section L of anchor point G is represented.
CN201410752436.6A 2014-12-11 2014-12-11 Online map matching method based on floating car data on tunnel road section Pending CN104504898A (en)

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Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104900057A (en) * 2015-05-20 2015-09-09 江苏省交通规划设计院股份有限公司 City expressway main and auxiliary road floating vehicle map matching method
CN105551249A (en) * 2015-12-31 2016-05-04 王东宇 Tunnel road section online map matching method based on floating car data
CN105679038A (en) * 2016-03-29 2016-06-15 福建工程学院 Method and system for recognizing entrance of parking lot
CN108253974A (en) * 2017-12-29 2018-07-06 深圳市城市交通规划设计研究中心有限公司 Floating Car location data automatic adaptation cushion route matching system and method
CN109300304A (en) * 2017-07-24 2019-02-01 神州优车（平潭）电子商务有限公司 Method and apparatus for determining history road conditions
CN113514072A (en) * 2021-09-14 2021-10-19 自然资源部第三地理信息制图院 Road matching method oriented to navigation data and large-scale drawing data

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CN101673466A (en) * 2009-09-25 2010-03-17 北京航空航天大学 Information processing method of float car under control of traffic signals
CN102741656A (en) * 2010-02-24 2012-10-17 歌乐株式会社 Navigation device with function of estimating position within tunnel
CN103149576A (en) * 2013-01-29 2013-06-12 武汉大学 Map matching method of floating car data
CN103218915A (en) * 2013-03-05 2013-07-24 中山大学 Experience route generation method based on probe vehicle data

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EP1006367A2 (en) * 1998-12-05 2000-06-07 Alcatel Satellite aided map matching method
US20040073364A1 (en) * 2002-10-11 2004-04-15 Jung Mun Ho Method for estimating location of moving object in navigation system
CN1959759A (en) * 2006-11-17 2007-05-09 上海城市综合交通规划科技咨询有限公司 Traffic analysis method based on fluctuated data of vehicles
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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104900057A (en) * 2015-05-20 2015-09-09 江苏省交通规划设计院股份有限公司 City expressway main and auxiliary road floating vehicle map matching method
CN105551249A (en) * 2015-12-31 2016-05-04 王东宇 Tunnel road section online map matching method based on floating car data
CN105679038A (en) * 2016-03-29 2016-06-15 福建工程学院 Method and system for recognizing entrance of parking lot
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CN108253974A (en) * 2017-12-29 2018-07-06 深圳市城市交通规划设计研究中心有限公司 Floating Car location data automatic adaptation cushion route matching system and method
CN108253974B (en) * 2017-12-29 2019-09-10 深圳市城市交通规划设计研究中心有限公司 Floating Car location data automatic adaptation cushion route matching system and method
CN113514072A (en) * 2021-09-14 2021-10-19 自然资源部第三地理信息制图院 Road matching method oriented to navigation data and large-scale drawing data

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Application publication date: 20150408