TY - GEN
T1 - Simulation evaluation of fuel-saving systems in the city of Chicago
AU - Zhao, Yiran
AU - Yao, Shuochao
AU - Liu, Dongxin
AU - Shao, Huajie
AU - Liu, Shengzhong
AU - Abdelzaher, Tarek
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/7
Y1 - 2019/7
N2 - This paper presents realistic traffic simulations in four representative regions in Chicago, using real map data and historical traffic statistics, to estimate the amount of fuel that can be saved by two types of systems, namely, a Green Light Optimal Speed Advisory (GLOSA) system and an Eco-Routing system. In particular, two previous systems called GreenDrive and GreenRoute are selected to estimate how much fuel they can save in a year, assuming they enjoy the same popularity as Google Maps. Evaluating intelligent transportation systems in simulation has attracted significant research efforts as large scale real-world experiments are often too expensive to carry out. However, simulation-based evaluations pose serious questions on how real the simulated environments are. In this paper, we resort to several data sources from the city of Chicago to quantify the approximation in simulated traffic, so as to convincingly derive the amount of fuel savings on a larger scale. Specifically, we create SUMO simulations of four real regions of Chicago, and utilize traffic counts data, road speed data, and taxi trips data to validate each simulation scenario. In the end, we show that by using our previously proposed systems, the estimated fuel saved in a year can be 17.6 million gallons for the entire Chicago area.
AB - This paper presents realistic traffic simulations in four representative regions in Chicago, using real map data and historical traffic statistics, to estimate the amount of fuel that can be saved by two types of systems, namely, a Green Light Optimal Speed Advisory (GLOSA) system and an Eco-Routing system. In particular, two previous systems called GreenDrive and GreenRoute are selected to estimate how much fuel they can save in a year, assuming they enjoy the same popularity as Google Maps. Evaluating intelligent transportation systems in simulation has attracted significant research efforts as large scale real-world experiments are often too expensive to carry out. However, simulation-based evaluations pose serious questions on how real the simulated environments are. In this paper, we resort to several data sources from the city of Chicago to quantify the approximation in simulated traffic, so as to convincingly derive the amount of fuel savings on a larger scale. Specifically, we create SUMO simulations of four real regions of Chicago, and utilize traffic counts data, road speed data, and taxi trips data to validate each simulation scenario. In the end, we show that by using our previously proposed systems, the estimated fuel saved in a year can be 17.6 million gallons for the entire Chicago area.
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U2 - 10.1109/ICCCN.2019.8846953
DO - 10.1109/ICCCN.2019.8846953
M3 - Conference contribution
AN - SCOPUS:85073147278
T3 - Proceedings - International Conference on Computer Communications and Networks, ICCCN
BT - ICCCN 2019 - 28th International Conference on Computer Communications and Networks
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 28th International Conference on Computer Communications and Networks, ICCCN 2019
Y2 - 29 July 2019 through 1 August 2019
ER -