2014 InferringGasConsumptionandPollu

• (Shang et al., 2014) ⇒ Jingbo Shang, Yu Zheng, Wenzhu Tong, Eric Chang, and Yong Yu. (2014). “Inferring Gas Consumption and Pollution Emission of Vehicles Throughout a City.” In: Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2014) Journal. ISBN:978-1-4503-2956-9 doi:10.1145/2623330.2623653

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Cited By

• http://scholar.google.com/scholar?q=%222014%22+Inferring+Gas+Consumption+and+Pollution+Emission+of+Vehicles+Throughout+a+City
• http://dl.acm.org/citation.cfm?id=2623330.2623653&preflayout=flat#citedby

Quotes

Author Keywords

• Data mining; gas consumption; spatial databases and gis; spatial trajectories.; traffic pollution; urban computing

Abstract

This paper instantly infers the gas consumption and pollution emission of vehicles traveling on a city's road network in a current time slot, using GPS trajectories from a sample of vehicles (e.g., taxicabs). The knowledge can be used to suggest cost-efficient driving routes as well as identifying road segments where gas has been wasted significantly. The instant estimation of the emissions from vehicles can enable pollution alerts and help diagnose the root cause of air pollution in the long run. In our method, we first compute the travel speed of each road segment using the GPS trajectories received recently. As many road segments are not traversed by trajectories (i.e., data sparsity), we propose a Travel Speed Estimation (TSE) model based on a context-aware matrix factorization approach. TSE leverages features learned from other data sources, e.g., map data and historical trajectories, to deal with the data sparsity problem. We then propose a Traffic Volume Inference (TVI) model to infer the number of vehicles passing each road segment per minute. TVI is an unsupervised Bayesian Network that incorporates multiple factors, such as travel speed, weather conditions and geographical features of a road. Given the travel speed and traffic volume of a road segment, gas consumption and emissions can be calculated based on existing environmental theories. We evaluate our method based on extensive experiments using GPS trajectories generated by over 32,000 taxis in Beijing over a period of two months. The results demonstrate the advantages of our method over baselines, validating the contribution of its components and finding interesting discoveries for the benefit of society.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2014 InferringGasConsumptionandPollu	Yong Yu Yu Zheng Jingbo Shang Wenzhu Tong Eric Chang			Inferring Gas Consumption and Pollution Emission of Vehicles Throughout a City				10.1145/2623330.2623653		2014