Green Routing System in Buffalo-Niagara Region shows over 16 percent reduction in CO and NOx.
Green Routing in Buffalo-Niagara Region
Made Public Date
09/11/2013
Identifier
2013-B00866
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An Evaluation of Likely Environmental Benefits of a Time-dependent Green Routing System in the Greater Buffalo-Niagara Region

Summary Information

The focus of this study is on an Intelligent Transportation Systems (ITS) strategy which involves providing route guidance to travelers with the objective of minimizing emissions or fuel consumption, as opposed to the traditional objective of minimizing travel times. Specifically, this study conducts a realistic assessment, using a real-world case study, of the likely environmental benefits of environmentally-based route guidance. The research utilizes a realistic case study of a medium-sized metropolitan area in the U.S. with a population of about 1.2 million. The research then applies the latest state-of-the-art models on both the transportation as well as the environmental modeling side, through the development of an integrated model combing the Transportation Analysis and Simulation System (TRANSIMS) model and the Multi-Scale MOtor Vehicle Emissions Simulator model (MOVES). The integrated model is used to approximate "Green User Equilibrium", and to investigate the impact of market penetration on the likely environmental benefits of green routing.

METHODOLOGY

The integrated modeling framework takes the output from TRANSIMS micro-simulator (i.e. the second-by-second vehicle speed trajectories) and feeds that into EPA MOVES model for the purpose of calculating the link-based emissions and/or fuel consumption, using the link drive schedule approach. This results in calculating link-based emissions production factors. The link-based emissions production factors are then fed back into the TRANSIMS Router, which then calculates new routes using the emissions criterion. Matlab was used to automate the process of extracting the output from TRANSIMS, converting the output into the format required by MOVES, running the MOVES model, extracting the MOVES output and feeding it back to the TRANSIMS Router.

FINDINGS

The simulation was run for 4 different cases:
  • Passenger car Carbon Monoxide (CO) emissions
  • Passenger car nitrogen oxides (NOx)
  • Passenger car fuel consumption
  • Long haul truck CO emissions
Each case was run multiple times and was analyzed for the emissions or fuel reduction as well as average travel time. Case 1, based on passenger car:
  • CO emissions showed a average reduction in CO of 16.77 percent when compared to the shortest path route and showed only a 3.33 percent increase in the average travel time.
  • When the route was based on NOx, a 19.47 percent decrease was seen, with an 11.04 percent increase in travel time.
  • For fuel consumption there was an average decrease of 5.55 percent gallons used with a 12.70 percent increase in travel time.
For the long haul truck case:
  • An 18.65 percent reduction in CO was seen with a 2.46 percent increase in travel time.