Prediction of vehicle CO₂ emission and its application to eco-routing navigation

Transportation sector accounts for a large proportion of global greenhouse gas and toxic pollutant emissions. Even though alternative fuel vehicles such as all-electric vehicles will be the best solution in the future, mitigating emissions by existing gasoline vehicles is an alternative countermeasure in the near term. The aim of this study is to predict the vehicle CO₂ emission per kilometer and determine an eco-friendly path that results in minimum CO₂ emissions while satisfying travel time budget. The vehicle CO₂ emission model is derived based on the theory of vehicle dynamics. Particularly, the difficult-to-measure variables are substituted by parameters to be estimated. The model parameters can be estimated by using the current probe vehicle systems. An eco-routing approach combining the weighting method and k-shortest path algorithm is developed to find the optimal path along the Pareto frontier. The vehicle CO₂ emission model and eco-routing approach are validated in a large-scale transportation network in Toyota city, Japan. The relative importance analysis indicates that the average speed has the largest impact on vehicle CO₂ emission. Specifically, the benefit trade-off between CO₂ emission reduction and the travel time buffer is discussed by carrying out sensitivity analysis in a network-wide scale. It is found that the average reduction in CO₂ emissions achieved by the eco-friendly path reaches a maximum of around 11% when the travel time buffer is set to around 10%.

• Record URL:
  https://doi.org/10.1016/j.trc.2016.04.007
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S0968090X16300110
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/0968090X
• Supplemental Notes:
  • Abstract reprinted with permission of Elsevier.
• Authors:
  • Zeng, Weiliang
  • Miwa, Tomio
  • Morikawa, Takayuki
• Publication Date: 2016-7

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: pp 194-214
• Serial:
  • Transportation Research Part C: Emerging Technologies
  • Volume: 68
  • Publisher: Elsevier
  • ISSN: 0968-090X
  • Serial URL: http://www.sciencedirect.com/science/journal/0968090X

Subject/Index Terms

• TRT Terms: Carbon dioxide; Ecodriving; Exhaust gases; Fuel consumption; Mathematical prediction; Navigation systems; Probe vehicles; Routing; Shortest path algorithms; Travel time
• Uncontrolled Terms: Ecorouting; Pareto optimum
• Geographic Terms: Toyota City (Japan)
• Subject Areas: Environment; Highways; Operations and Traffic Management; Planning and Forecasting;

Filing Info

• Accession Number: 01605364
• Record Type: Publication
• Files: TRIS
• Created Date: Jun 13 2016 9:48AM