This document summarizes a project to create models for fuel consumption and CO2 emissions from vehicle data. The project involved collecting position, speed, and acceleration data from a device called EcoGyzer, along with noting road events. This data was then used to calculate slope, fuel consumption based on speed and slope, and CO2 emissions. The data was stored in shapefiles and could detect dangerous driving behaviors like heavy braking or strong turns. The goals were met by creating consumption models and enriching a geographic database with this vehicle performance and environmental impact data.

1. Project made by Arnaud Grégoire, Antoine Moutou,
Axel Orger et Antoine Roca in july 2016
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2. Introduction
Goals :
- Creation of a fuel consumption and a CO2 emissions models
- Enrichment of the geographic database of the departement
- Detection of road behaviour
How ?
- Acquisition of position/speed/accelerations
- Acquisition of road events position
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3. Acquisition by EcoGyzer
 What does it do?
Every second it saves :
1. Time
2. Latitude/longitude
3. Speed
4. Accelerations
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4. Acquisition via PC
Acquisition of road events
- Link them with EcoGyzer raw data (long, lat, speed…)
- First approach : Handwritten notation
- Solution : Creation of a embedded software
Store the meeting date of a road event
Matching of Eco Gyzer date and software date. 4

5. Embedded software interface
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6. Gathering of EcoGyzer and software data
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7. What does .shp contain ?
 Raw data:
- Position, speed, road events
 Calculated data :
- Slope
- Fuel consumption
- CO2 emissions
- Dangerous driving detection
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8. 8
Speed

9. Road events + Speed
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10. Slope
DataBase TOPO (Z)
Position (X,Y)
X,Y,Z +
slope 𝛼
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11. The Forcalquier-La Bégude route without and with smoothing.
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12. Slope
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13. Consumption
𝑎 ∗ 𝑣2
+ 𝑏 ∗ 𝑣 + 𝑐 ∗ (1 + sin(𝛼))
(ℝ+,[0,360])
Speed v (km/h), 𝛼(°)
ℝ+
K(L/100km)
{
• With some observations we performed of :
- The speed v
- The road slope 𝛼
- The consumption K
• We identify (a,b,c) by least square method
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14. 14
Fuel consumption model depending on the speed an the slope

15. Fuel consumption
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16. 16
CO2 emissions (cste*K)

17. Dangerous driving detection
Detection limit
Heavy breaking:
Ax> 350 mG
Strong turn :
Ay> 750 mG
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18. Conclusion
 Creation of shapefiles with :
- Speed, position, accelerations, slope, consumption,
CO2 emissions, dangerous driving detection
 Possible improvement :
- Retry this projects with several cars
- Take account of road traffic
 Creation of a fuel consumption model
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