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Predicting &Visualizing the impact of future
weather on traffic flow forecasting
Why

Currently, there exists no
tool that could effectively
incorporate weather info
into traffic forecasting

Team 29

Hongzhao Guan ·∙ Yi  Yao ·∙ Hanyu Liu
Zhao  Yan ·∙ Shi  Cheng ·∙ Jianan Jin

Weather-Related car
accidents are far more
deadly than tornadoes,
hurricanes, or floods
-- US DOT

However, the impact of weather on
traffic and road conditions are
significant and shouldn’t be neglected

Data Processing
Content

Weather History

Traffic Flow History

Sources

Weather
Underground

Georgia
Department of
Transportation

API (Limit)

Download &
Format with
Python Script

184,800 Records
14 Variables

1050,000 Records
7 Variables

Method
Size

Approach

• We joined the two datasets using
SQLite on two variables

Data

Location
[Postal Code]
&
Date-Time

• A total of 18 variables after joining of tables

Polynomial Fit Analysis

Traffic Flow without
considering weather influence

Therefore, we decide to
collect, process and study
historical data to develop
such tools to ensure safer
and more efficient travel on
road

Traffic Flow considering
weather influence

Fourier Curve Fitting
Periodic Time Series
y = f(t)
Degree = 4
1)
2)
3)
4)

Site-id
Weekday vs Weekend
Dec. vs other months
Weather (Clean, Rain,
Cloudy, Misc)

à y = a1*sin(b1*x+c1) +
Where y = traffic flow, x = hour in a weekday

Figure 1: The traffic flow has a strong relationship with the weekday and the hour of the day
Figure 2: By adding the influence of weather, the increment trend of the traffic flow can be
predictedin a certain confidential interval

Visualization: d3,JqueryUI
Testing: One experiment has been performed for PO 36416

a2*sin(b2*x+c2) +
a3*sin(b3*x+c3) +
a4*sin(b4*x+c4)

Where x = hour, y = traffic flow

Experiment & Value

• Red - traffic flow is getting worse, Yellow - changing too much (under 5 percentages), green better than under clear weather
• In this experiment, the figure shows the traffic is getting better under rainy weather in this region,
this makes sense because this station is on a local road next to I-75; - traffic is slower coming out
of I-75 / fewer drivers on the road at 1pm.

Innovation
Comparing to
existing models

1. Using hourly data from geologically discrete
locations and interpolation methods to reconstruct a
traffic flow map over all geological locations
Weekdays vs Weekend
2. Animating weather and traffic flow conditions via UI
implementation.






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