DISSECTING REGIONAL WEATHER-TRAFFIC SENSITIVITY THROUGHOUT A CITY Ye Ding 1, Yanhua Li 2, Ke Deng 3,...

DISSECTING REGIONAL WEATHER-TRAFFIC SENSITIVITY THROUGHOUT A CITY

Ye Ding 1 , Yanhua Li 2 , Ke Deng 3 , Haoyu Tan 1 , Mingxuan Yuan 4 , Lionel M. Ni 5

1 Guangzhou HKUST Fok Ying Tung Research Institute, The Hong Kong University of Science and Technology2 Computer Science Department, Worcester Polytechnic Institute3 School of Computer Science and Information Technology, RMIT University4 Noah’s Ark Lab, Huawei Technologies Co., Ltd.5 University of Macau

[email protected], [email protected], [email protected], [email protected], [email protected], [email protected]

Dissecting Regional Weather-Traffic Sensitivity throughout a City 2

INTRODUCTIONOverview

Heavy Rain Traffic Jam

Why?

Inappropriate Urban Planning or Infrastructure

Tunnels with Bad Sewer Systems

Highways with Bad Entrance Structures

How to Detect Regional Weather-Traffic Sensitivity?

Low

High

Tour AttractionBad Weather + Crowd = Traffic

JamProve Our Method Makes Sense

Regular CommunityNo Conspicuous Reasons

Alert City Planners to Examine


Factor Analysis

RegionalFeatures

Factor Analysis Component

TrafficParameters

WeatherInformation

Weather-Traffic Index

Weather-Traffic Index Establishment Component

THE WEATHER-TRAFFIC INDEX SYSTEMSystem Architecture

RoadNetwork

TaxiTrajectories

WeatherReport Data

Region Partitioning

Regional Information

Data Preparation Component


THE WEATHER-TRAFFIC INDEX SYSTEMData Preparation

TAXI TRAJECTORIES

WEATHER REPORT DATA

REGIONAL INFORMATION

ROAD NETWORK

Provided by the government

~33,000 road segments



TAXI TRAJECTORIES

WEATHER REPORT DATA


ROAD NETWORK

Taxis = traffic sensors

Provided by the government

4,529 taxis, ~115.2 GB

Jan. 2006 – Nov. 2007

Sampling rate: ~20 seconds

Traffic measure: average driving speed

Trajectory Sample Point

Taxi ID: 10001Location: 121.3926, 31.1655Time: 2006-01-06 10:03:01Driving Speed: 40



TAXI TRAJECTORIES

WEATHER REPORT DATA


ROAD NETWORK

Crawled from wunderground.com

Reported on hourly basis

14 weather features



TAXI TRAJECTORIES

WEATHER REPORT DATA


ROAD NETWORK

Categories: # of POIs (place-of-interests) Area structure Density of POIs and roads Community information

Crawled from: dianping.com (like Foursquare) fang.com (like Zillow)


THE WEATHER-TRAFFIC INDEX SYSTEMRegion Partitioning

TAXI TRAJECTORIES

WEATHER REPORT DATA


ROAD NETWORK

Road-intersection-oriented partitioning

Voronoi diagram

Only major road segments are used

VORONOI CELL / REGION

TRAFFIC PARAMETERS

WEATHER INFORMATION

REGIONAL FEATURES


THE WEATHER-TRAFFIC INDEX SYSTEMWeather-Traffic Correlation Detection

Heavy Rain

TrafficParameter

s

WeatherInformatio

n

Infer

Traffic Jam

High accuracy = area traffic is more sensitive to weather

Low accuracy = area traffic is less sensitive to weather

There are many other reasons which impact traffic: The traffic in peak-hour differs from that in non-peak hours The traffic accident in one road segment will influence the traffic in nearby road

networks The road works slow down the average speed …

These reasons are dominant in most cases


THE WEATHER-TRAFFIC INDEX SYSTEMWeather-Traffic Correlation Detection

TrafficParameter

sin

TrafficParameter

sin

Predict

Traffic prediction methods

Accuracy

Accuracy

= average difference of and

We call as weather-traffic index

TrafficParameter

sin

WeatherInformatio

nin

TrafficParameter

sIn

Predict

Predict

t0 , … , tn

* Algorithm details are shown in the paper


THE WEATHER-TRAFFIC INDEX SYSTEMFactor Analysis

Which regional features affect weather-traffic index the most?

Use weather-traffic indices of adjacent cells to predict the weather-traffic index of each cell

Use regional features to construct the similarity function

Feature selection on all regional features via the above inference method

𝑔𝑢 𝑔𝑖 𝑔𝑣Similarity

𝑚(𝑖 ,𝑢)Similarity

𝑚(𝑖 ,𝑣 )

𝜌 (𝑔𝑢) 𝜌 (𝑔𝑣)𝜌 (𝑔𝑖)


EMPIRICAL STUDYWeather-Traffic Index

1 Yu Garden, a tourism attraction

2 Shanghai Confucian Temple, a tourism attraction

3 Shanghai Town God Temple, a tourism attraction

4 / 5 No conspicuous reasons, maybe construction areas


EMPIRICAL STUDYFactor Analysis

Community features have the most influence on weather-traffic index

# of POIs have the least influence on weather-traffic index

# OF NEIGHBOURING CELLS

TOTAL ROAD LENGTH PER SQUARE METER

RATIO OF MAJOR / MINOR ROADS

AVERAGE HOUSE AGE

AVERAGE HOUSE UNIT PRICE

# OF LEISURE SPOTS PER SQUARE METER

MINOR ROAD LENGTH PER SQUARE METER

MAJOR ROAD LENGTH PER SQUARE METER

# OF INTERSECTIONS

# OF RESIDENTIAL COMMUNITIES


CONCLUSION

A systematic approach has been proposed for establishing weather-traffic index throughout a city

A novel method has been proposed to successfully address the impact of weather to traffic from many other reasons

A supervised learning method have been proposed to disclose the key factors and their weights contributing to weather-traffic index throughout the city

We conduct empirical study in the largest city of China using large-scale real-life data

Dissecting Regional Weather-Traffic Sensitivity throughout a City

Thanks!Dissecting Regional Weather-Traffic

Sensitivity throughout a City

Presented by Ye Ding

DISSECTING REGIONAL WEATHER-TRAFFIC SENSITIVITY THROUGHOUT A CITY Ye Ding 1, Yanhua Li 2, Ke Deng 3,...

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