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Hindi Review Article
Status and Research Topics in Developing Ecological Transportation System within Connected Vehicle Age with Knowledge Discovery in Database Techniques
Fengxiang Qiao, Qing Li* and Lei YuInnovative Transportation Research Institute, Texas Southern University, 3100 Cleburne Street, Houston, Texas, USA
- *Corresponding Author:
- Qing Li
Post-doctoral Fellow, Innovative Transportation Research Institute
Texas Southern University, 3100 Cleburne Street
Houston, Texas, 77004, USA
Tel: 713-313-7532
E-mail: liq@tsu.edu
Received date: April 24, 2017; Accepted date: April 27, 2017; Published date: April 30, 2017
Citation: Qiao F, Li Q, Yu L (2017) Status and Research Topics in Developing Ecological Transportation System within Connected Vehicle Age with Knowledge Discovery in Database Techniques. Environ Pollut Climate Change 1:124.
Copyright: © 2017 Qiao F, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Traditional transportation studies normally focus on the development of countermeasures for the improvement of safety and mobility of transportation systems. With the newly identified evidences and increased public concerns, the impacts of transportation activities on environment and ecologic systems attract more and more attentions. This article reviews the current air quality and vehicle emission models and real-time intelligent network control methods in ecological transportation (or called eco-transportation) systems with the efforts in reducing greenhouse gases and exhaust emissions, and improving air quality and public health. The ecological transportation system is considered in a Connected Vehicle environment, and the potential applications of the Knowledge Discovery in Databases (KDD) techniques in ecological transportation system are also reviewed. The proposed research topics can be extended to a better understanding of complex network modeling and controls associated with the development of sustainable urban environment with the ecological transportation system.
