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A vehicle path planning method based on a dynamic traffic network that considers fuel consumption and emissions
Dong Guo1, Juan Wang1, Jin B Zhao1
1School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo, China.
The Science of the Total Environment
|February 12, 2019
Summary
Optimizing vehicle routes using dynamic traffic data significantly cuts fuel use and pollution. This study introduces a new path planning model to reduce urban environmental impact.
Area of Science:
- Environmental Science
- Transportation Engineering
- Computer Science
Background:
- Vehicle use increases fuel consumption and pollution.
- Urban dynamic traffic flow data can mitigate these issues.
Purpose of the Study:
- Develop a model for vehicle path planning to reduce fuel consumption and emissions.
- Improve urban environmental quality in China.
Main Methods:
- Established a fuel consumption and emissions model coupled with a dynamic traffic network.
- Improved the Dijkstra algorithm for path planning.
- Performed simulations in MATLAB using ArcGIS-generated road networks.
Main Results:
- Road type and intersection traffic significantly impact fuel use and emissions.
- Path planning results vary based on optimization targets (time, distance, fuel, emissions).
Conclusions:
- The proposed model effectively reduces vehicle fuel consumption and emissions.
- Offers a novel approach to mitigate urban environmental pollution through optimized path planning.
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