基于出租车GPS地理位置的打车推荐算法
Zhi-Qiang You & Lu Yu
2013/11/16
移动互联的数字化生活
打车推荐算法框架
GPS与数字地图匹配
近几年的相关研究及展望
手机
谷歌眼镜
智能手表
全能型穿戴设备
Jing Yuan*, Yu Zheng, Liuhang Zhang, Xing Xie, Guangzhong Sun, Where to Find My Next Passenger? ,
13th ACM International Conference on Ubiquitous Computing (UbiComp 2011), Beijing, China, Sep. 2011.
Jing Yuan*, Yu Zheng, Liuhang Zhang, Xing Xie, Guangzhong Sun, Where to Find My Next Passenger? ,
13th ACM International Conference on Ubiquitous Computing (UbiComp 2011), Beijing, China, Sep. 2011.
Jing Yuan*, Yu Zheng, Liuhang Zhang, Xing Xie, Guangzhong Sun, Where to Find My Next Passenger? ,
13th ACM International Conference on Ubiquitous Computing (UbiComp 2011), Beijing, China, Sep. 2011.
Online Taxi Recommendation
Jing Yuan*, Yu Zheng, Liuhang Zhang, Xing Xie, Guangzhong Sun, Where to Find My Next Passenger? ,
13th ACM International Conference on Ubiquitous Computing (UbiComp 2011), Beijing, China, Sep. 2011.
Online Taxi Recommendation
Jing Yuan*, Yu Zheng, Liuhang Zhang, Xing Xie, Guangzhong Sun, Where to Find My Next Passenger? ,
13th ACM International Conference on Ubiquitous Computing (UbiComp 2011), Beijing, China, Sep. 2011.
Online Taxi Recommendation
Jing Yuan*, Yu Zheng, Liuhang Zhang, Xing Xie, Guangzhong Sun, Where to Find My Next Passenger? ,
13th ACM International Conference on Ubiquitous Computing (UbiComp 2011), Beijing, China, Sep. 2011.
Online Taxi Recommendation
Jing Yuan*, Yu Zheng, Liuhang Zhang, Xing Xie, Guangzhong Sun, Where to Find My Next Passenger? ,
13th ACM International Conference on Ubiquitous Computing (UbiComp 2011), Beijing, China, Sep. 2011.
Online Taxi Recommendation
Jing Yuan*, Yu Zheng, Liuhang Zhang, Xing Xie, Guangzhong Sun, Where to Find My Next Passenger? ,
13th ACM International Conference on Ubiquitous Computing (UbiComp 2011), Beijing, China, Sep. 2011.
Online Taxi Recommendation
Jing Yuan*, Yu Zheng, Liuhang Zhang, Xing Xie, Guangzhong Sun, Where to Find My Next Passenger? ,
13th ACM International Conference on Ubiquitous Computing (UbiComp 2011), Beijing, China, Sep. 2011.
Online Taxi Recommendation
Jing Yuan*, Yu Zheng, Liuhang Zhang, Xing Xie, Guangzhong Sun, Where to Find My Next Passenger? ,
13th ACM International Conference on Ubiquitous Computing (UbiComp 2011), Beijing, China, Sep. 2011.
Online Passenger Recommendation
Jing Yuan*, Yu Zheng, Liuhang Zhang, Xing Xie, Guangzhong Sun, Where to Find My Next Passenger? ,
13th ACM International Conference on Ubiquitous Computing (UbiComp 2011), Beijing, China, Sep. 2011.
Online Passenger Recommendation
Jing Yuan*, Yu Zheng, Liuhang Zhang, Xing Xie, Guangzhong Sun, Where to Find My Next Passenger? ,
13th ACM International Conference on Ubiquitous Computing (UbiComp 2011), Beijing, China, Sep. 2011.
Online Passenger Recommendation
Jing Yuan*, Yu Zheng, Liuhang Zhang, Xing Xie, Guangzhong Sun, Where to Find My Next Passenger? ,
13th ACM International Conference on Ubiquitous Computing (UbiComp 2011), Beijing, China, Sep. 2011.
Online Passenger Recommendation
Jing Yuan*, Yu Zheng, Liuhang Zhang, Xing Xie, Guangzhong Sun, Where to Find My Next Passenger? ,
13th ACM International Conference on Ubiquitous Computing (UbiComp 2011), Beijing, China, Sep. 2011.
Online Passenger Recommendation
Jing Yuan*, Yu Zheng, Liuhang Zhang, Xing Xie, Guangzhong Sun, Where to Find My Next Passenger? ,
13th ACM International Conference on Ubiquitous Computing (UbiComp 2011), Beijing, China, Sep. 2011.
Online Passenger Recommendation
Jing Yuan*, Yu Zheng, Liuhang Zhang, Xing Xie, Guangzhong Sun, Where to Find My Next Passenger? ,
13th ACM International Conference on Ubiquitous Computing (UbiComp 2011), Beijing, China, Sep. 2011.
Map-Matching (GPS地图匹配算法)
Map-matching is the process of aligning a sequence of
observed user positions with road network on a digital
map.
Moving Object management
Fundamental
pre-processing
Step
for
Traffic flow analysis
Driving directions
Yin Lou et al. Map-Matching for Low-Sampling-Rate GPS Trajectories. (ACM SIGSPATIAL GIS 2009).
Yuan J, Zheng Y, Zhang C, et al. An interactive-voting based map matching algorithm[C]//Mobile Data Management,
2010 Eleventh International Conference on. IEEE, 2010: 43-52.
Two Situations
1.High Sampling Points(typically one point every 10-30s)
The incremental algorithm
Traditional
Algorithms
Average-Frechet-Distance
based global map-matching
Algorithm
Work Well !
2.Low Sampling Points(one point every 2-5 minutes)
Uncertainty
goes up
With such sampling rate,the
distance between two points may
reach over 1300m even a
vehicle’s speed is only 40km/h
Incremental and
AFD algos
Perform bad !
Under such circumstance , Yin propose a novel global
map-matching algorithm called ST-Matching for
low-sampling-rate GPS trajectories!
Smile again!
BTW
1.Local / imcremental methods
The
approaches
which address the
map-matching problems
can be generally classified into
2. global methods
three classes
3.Statistical models
Now , you must be clear:
ST-Matching algorithm
1. be created to address the low-sampling-rate GPS Trajectory matching
problem.
2. belongs to the global algorithm class.
3. aim to improve the accuracy of map-matching under low-sampling-rate
GPS situation.
DataSets
Taxi GPS Points
Road network
Now the problem of map-matching is defined as:
Given a raw GPS trajectory T and a road network G(V,E),find the
path P from G that matches T with its real path.
LET’S GO INTO DETAILS
Two Observation Of ST-Matching Algorthm
SPATIAL ANALYSIS
TEMPORAL ANALYSIS
Algorithm Architecture
Candidate Preparation
* 经度：相差3.234059999999772秒，距离相差100.00386455484937
* 纬度：相差7.2766800000096055秒，距离相差100.00159837312073
Candidates num K = 5
If no candidates, return
“null”, then ignore this
trajectory point.
Spatial Analysis
Geometric and topological Information of the road network
1.Geometric information is incorporated using observation probability
2.Topological information is expressed using transmission probability
候选点之间的最短路径使用ArcGIS进行求值。
使用的是python接口
Temporal Analysis(but I feel weird about the way they took)
Warning:
Suppose: Highway: [100,100,100]
Service Road:[20,20,20]
average speed of taxi:
[19,19,19]
Similarity results are the same! Inseparable!
Result Matching
最长路径算法：基于Dijkstra算法的改型。
Example
Evaluation Approaches
Obviously, ST-Matching algorithm does’t take other points except the
closest points.
But:
1.The position context of a GPS point as well as the topological information of road networks
2.The mutual influence between GPS points(the matching result of a point references the
positions of its neighbors ; in turn ,when matching its neighbors , the position of this point will
also be referenced)
3.The strength of the mutual influence weighted by the distance between GPS points(the
farther distance is the weaker influence exists)
So , they work out a new algorithm called IVMM(Interactive-voting
based map matching algorithm)
From the above figure , we can see the first two phases are the same
with ST-Matching . Using Spatial and Temporal Analysis , we get the
Static Score Matrix.
Mutual Influence Modeling
Interactive Voting
Evaluation Approach
近年来的相关研究
Microsoft Research Asia & Geolife
Detect Gathering Patterns
Kai Zheng et al. On Discovery of Gathering Patterns from Trajectories, ICDE 2013
Taxi Collaborative Recommendation
Nicholas Jing Yuan et al. T-Finder: A Recommender System for Finding Passengers and
Vacant Taxis. TKDE 2012
Urban Computing
Yu Zheng et al. Urban Computing with Taxicabs, Ubiquitous Computing (Ubicomp) 2011
Map-Matching
Jing Yuan et al. An Interactive Voting-based Map Matching Algorithm, IEEE Mobile Data
Management (MDM) 2010.
………
Map-Matching (GPS地图匹配算法)
ArcGIS
@Ersi
地理数据处理软件（ArcGIS）
路网数据格式：1、gdb格式
2、shapefile格式
求解最短路径：提供network analysis和spatial analysis功能
数据导出：XML格式，因此处理路网数据时，格式化文件，那么需要进行超大XML文件解析，我们这次接触的是解析400M左右
的单个XML文件，格式非标准xml，单行显示。所以需要流读取进行处理。Java和python都提供了SAX解析包。
GeoCoding编码以及逆编码
通过地址查询GPS数据
http://maps.googleapis.com/maps/api/geocode/json?address=1600+Amphitheatre+Parkway,+Mountain+View,+CA&sensor= true_or_false
通过GPS数据查询地址（城市、街道等信息）
http://maps.googleapis.com/maps/api/geocode/json?latlng=40.714224,-73.961452&sensor=true_or_false
最短路径算法（本算法中，需要想反，使用最长路径算法）
1.Dijkstra's Algorithm
2.A*算法
谢谢！