The document discusses an online traffic monitoring system for mobile users that provides information on traffic jams, meteorological conditions, traffic flow parameters, air pollution levels, and short-term and long-term health risks. It uses a Gaussian model of turbulent diffusion to calculate pollutant concentrations from traffic emissions based on factors like emission rates, wind speed, and source height. The system obtains real-time traffic and weather data from online sources to analyze current conditions. It also allows users to obtain routes with lowest estimated health risks and get categorized risk levels for their journey. While the simple calculation methods make instant estimates possible, the summary notes that more detailed road and vehicle data could improve accuracy.

1. ONLINE TRAFFIC JAM
MONITORING FOR MOBILE
USERS
Assoc. Prof. Dr. Alexander V. Ivanov
Prof. Dr. Alexander Yu. Platov
Undergraduate Student Dmitry V. Stepanov
Nizhny Novgorod State University of Architecture
and Civil Engineering,
Russia
NNSUACE

2. • New reality includes
– Traffic congestion localities, described by average
“jam” velocity and the congestion size,
– Meteorological data including wind velocity and solar
radiation,
– Calculated traffic flow parameters
– Calculated air pollution (concentration of air pollutants
and noise)
– Calculated short term and long term health risk.
NNSUACE Online Monitoring of Traffic Jam

3. Gaussian Model of Turbulent Diffusion
where:
C is the concentration of a pollutant in the air, mg/m3;
Q is the emission rate of the pollutant, mg/s
is the standard deviation of the Gaussian dispersion in the horizontal
direction at x0, y0, z0; m;
is the standard deviation of the Gaussian dispersion in the vertical
direction at x0, y0, z0; m;
U is the wind speed, m/s;
F is the background pollutant concentration, mg/m3.
h is the effective height of the source, m
x, y, z are the emission source coordinates, m;
NNSUACE
.
2
,
2 22
U
xK
U
xK z
z
y
y == σσ

4. Gaussian Model of Turbulent DiffusionNNSUACE

5. Gaussian Model of Turbulent DiffusionNNSUACE

6. Atmosphere Boundary layer stability
NNSUACE
Wind Velocity,
m/s
Classes of sustainability A-F
Day time
Solar radiation
Night time.
Clouds
Strong
Convection
Moderate
Convection
Slight
Convection
>50% <50%
<2 A (A+B)/2 B E F
2-3 (A+B)/2 B C E F
3-5 B (B+C)/2 C D E
5-6 C (C+D)/2 D D D
>6 C D D D D
Pasquill stability categories

7. Online MeteoData Including Wind Velocity and Solar Radiation
http://www.realmeteo.ru/
Meteorological Data is basic info for turbulent diffusion calculation

8. Moscow Never SleepsNNSUACE

9. Measured Share of
Cars, Buses, Lorries and TrucksNNSUACE

10. Every Congestion Has Unic PortraitNNSUACE

11. User – Server Interaction Procedure
NNSUACE

12. NNSUACE Online Flow Velocity http://www.yandex.ru/maps/47/
Internet address:
https://yandex.ru/maps/47/nizhny-novgorod/?
ll=44.005986%2C56.332609&z=11&l=map%2Ctrf%2Ctrfe&source=traffic

13. Interactive User-Server Algorithm
NNSUACE

14. Internet Service for Mobile Users
Eco-routesNNSUACE
Avalable at http://eco-routes.appspot.com
/

15. Web-Service Application Form
Start point and
destination point
Start calculation

16. Calculated Concentration 1 of NOx

17. Calculated concentration 2 of Nox
NNSUACE

18. Short Term Health Risk AssessmentNNSUACE
Short term risk assessment follows the methodology developed by A.V.
Kiselyov and L.A. Savvateeva :
The 1st
class of hazard: Prob = -9.15 + 11.66 * lg (С/MAC sh.t.),
The 2nd
class of hazard: Prob = -5.51 + 7.49 * lg (С/ MAC sh.t.),
The 3rd
class of hazard: Prob = -2.35 + 3.73 * lg (С/ MAC sh.t.),
The 4th
class of hazard: Prob = -1.41 + 2.33 * lg (С/ MAC sh.t.).

19. Long Term Toxic Risk Assessment
Risk = 1 – exp{ln(0,84) [C/(MAC*Кз
)]b
t},
С – daily average concentration;
MAC – max. allow. concentration;
Кз
- coefficient of safety is equal to 7,5 для 1st
class of
hazard, 6 – for 2th
class, 4,5 - for 3th
class and 3,0 - for 4th
class of hazard;
b – isoeffectiveness coefficient is equal to 2,4 for 1 class,
1,31 - for 2 class, 1,0 - for 3 class and 0,86 for 4class of
hazard;
t – term of exposition; t = 1 for 70 years.
NNSUACE

20. Long Term Toxicological Health risk
• To calculate the pollution indicators, the user must
click "Rate risk". As a result, the user sees
ancategorized level of the Risk.
• The calculated level has Three categories
• 1. Favored
2. Satisfactory
3. Danger
NNSUACE

21. Conclusion 1
Both short term and long term health risk estimations are important
online services for mobile users especially during traffic congestion.
Rather simple formulas are used to make instant estimation.
Traffic intensity and flow rate are the basic parameters for emission of
pollutants.
Calculation of flow rate during traffic congestion is a very popular
internet service provided by feveral private companies.
Several certified companies provide online meteorological services.
Key assumption for the calculations is that the measurement of
the flow rate during traffic jam enables calculating traffic
intensity.
The above mentioned assumptions and services give hope to spread
online health risk assessment for the whole country.
NNSUACE

22. Conclusion 2
The weak point of the online monitoring is the lack of
comparison with observations.
The service needs more detailed information about
roads and vehicles. Number of lanes, traffic lights and
age of vehicles are important for the accurate
calculation.
Adaptation of the calculation for local circumstances
will be a further task.
NNSUACE

23. Thank YouThank You
for Your Kind Attentionfor Your Kind Attention!!
NNSUACE
Alexander Ivanov,Alexander Ivanov,
alexanderivanov52@gmail.comalexanderivanov52@gmail.com