- 重要日期
- 截稿日期: 2019年11月4日
- 会议日期:2019年12月16-18日
- 录用通知:投稿后20-40天
- 论文出版:收到最终稿后15-20天
- 联系我们
- 邮箱:conference123net@126.com
- 手机:0086-18101720867
- 座机:021-51098086
- 微信:18101720867
演讲嘉宾信息如下:
Biography: Dr. Huaguo Zhou is a Professor in Transportation Engineering of Department of Civil Engineering at Auburn University. His research interests include highway design and safety, highway inventory and access management and traffic control devices. Dr. Zhou has conducted research that has exceeded $6 million in funding, sponsored by federal, state, and local agencies. He has extensive experience working with a group of technical panelists on various projects. He is currently serving as a PI on NCHRP project 03-135 Wrong-Way Driving Solutions, Policy and Guidance. He also has an extensive list of publications, with over 100 articles published or presented in journals, at international conferences, and in technical reports. He is currently a member of two TRB committees: Access Management and Traffic Control Devices, a fellow of ITE and a member of ATSSA.
Topic: Modeling the Risk of Wrong-Way Driving at the Exit Ramp Terminals of Partial Cloverleaf Interchanges
Abstract: Partial cloverleaf (parclo) interchanges with closely spaced parallel entrance and exit ramps are more prone to wrong-way driving (WWD) compared to other interchange types. In this study, a Firth’s model has been developed to predict the risk of WWD at the exit ramp terminals of parclo interchanges based on effect of geometric design features, wrong-way related traffic control devices, area type, and traffic volume. According to the model, the significant predictors of WWD at parclo exit ramp terminals include corner radius from crossroad to entrance, type of median on crossroad, width of median on two-way ramp, channelizing island, distance to the nearest access point, “Keep Right” sign, wrong-way arrow, intersection signalization, and traffic volume at the exit and entrance ramps. This model was used to conduct network screening for all the exit ramp terminals of parclo interchanges in Alabama and Georgia to identify high-risk locations in these two states. Seven high-risk locations were monitored by video cameras for 48-hours to observe the occurrences of WWD incidents. Results suggest that two locations in Alabama and two locations in Georgia experienced multiple WWD incidents within 48-hours of a typical weekend. Therefore, the observation of WWD incidents at high-risk locations demonstrates strong evidence that the model was capable of identifying the exit ramp terminals with high risk of WWD.
Biography: Dr. Syed Abdul Rehman Khan is an expert of Supply Chain and Logistics Management. Dr Khan achieved his CSCP—Certified Supply Chain Professional certificate from the U.S.A. and completed his PhD in China. Since 2018, Dr Khan has been affiliated with Tsinghua University as a postdoctoral researcher. He has more than twelve years’ core experience of supply chain and logistics at industry and academic levels. He has attended several international conferences and also has been invited as a keynote speaker in different countries. He has published more than 70+ scientific research papers in different well-renowned international peer-reviewed journals and conferences. Dr Khan is the authored of 4 books related to the sustainability in supply chain and business operations. He is a regular contributor to conferences and workshops around the world. During the last three years, Dr Khan has won 5 different national/provincial-level research projects. Besides, Dr Khan has achieved scientific innovation awards three times consecutively by the Education Department of Shaanxi Provincial Government, China. Also, Dr Khan holds memberships in the following well-renowned institutions and supply chain bodies/associations: APCIS-U.S.; Production and Operation Management Society, India; Council of Supply Chain Management of Professionals U.S.; Supply Chain Association of Pakistan; and Global Supply Chain Council China.
Topic: De-carbonization to Logistics and Transportation Industry: Preparing for Tomorrow, Today
Abstract: This article examines the association between green logistics operations, social, environmental and economic indicators of SAARC (South Asian Association for Regional Cooperation) countries. The research used GMM (Generalized Method of Moments) and FGLS (Feasible Generalized Least Squares) two methods to tackle the problems of heterogeneity, serial correlation and heteroskedasticity. The findings show that fossil fuel consumption is at the heart of logistics operations; the more fossil fuel and non-green energy resources that are used, the more negative effects on society and environmental sustainability result from this. A lower quality of transport-related infrastructure and logistics services is negatively correlated with fossil fuel usage, carbon emissions, health expenditure, greenhouse gas emissions and political instability of SAARC countries. Conversely, efficient customs procedures and greater information sharing among supply chain partners increase trade opportunities and also improve environmental sustainability in terms of minimum carbon emissions due to the shorter waiting and queue times involved. Further, the application of green energy resources and green practices can mitigate negative effects on social and environmental sustainability due to better logistics operations while improving financial performance in terms of higher GDP per capita, trade openness and greater export opportunities around the globe. As there is very limited research using green practices relationship with macro-level indicators in current literature, this research will assist both practitioners and policymakers to understand the roles of green supply chain and green logistics in enhancing environmental sustainability, social improvement and economic growth for a better future.
Biography: Dr. Guangjun Gao is a professor of train collision dynamics and train safety. He is the director of the National Joint Engineering Research Center for Rail Transit Train Safety Guarantee Technology, the Secretary-General of the Railway Transportation and Engineering Teaching and Instruction Committee of the Ministry of Education, the member of the Ministry of Transportation and Energy, the deputy editor of the Transportation Safety and Environment. He has the memberships of the Expert Committee of the Bureau, the High-Speed Railway Committee of the China Railway Association, the Traffic Safety Committee of the China Intelligent Transportation Association and the Special Committee of China Aerodynamics Wind Engineering and Industrial Aerodynamics. He has published 49 SCI papers, cited 619 times by Scopus in Sciences, ranked first in 13 authorized Chinese invention patents, and 6 patents from abroad. He has won 3 National Science and technology awards, 1 national patent gold award, 6 provincial and ministerial first-class awards, and 5 industry associations awards. In the past five years, he has presided over one key project of the National Natural Science Foundation of China, one project on the surface of the National Natural Science Foundation of China, three tasks in key fields of the Ministry of Science and Technology and 11 other projects with a contractual fund of nearly 30 million yuan.
Topic: Study of the snow accretion of the metro train and improvement of anti-snow performance based on flow control
Abstract: In this study, the snow and ice issue of a subway train was studied and discussed with the unsteady Reynolds-Averaged Navier-Stokes simulations (URANS) coupled with the Discrete Phase Model (DPM), and the influences of the deflectors ahead and back of each bogie on the flow field and snow distribution are taken into account. The results show that the front deflectors keep the windward surfaces of the bogie away from the being directly impacted by strong flow and the rear deflectors with the increasing degree make the flow characteristic more complicated. Thus, the snow particles in the bogie region, especially for the upper region, decrease sharply. What’s more, the front deflectors improved the distribution on the upper region, which contributes to the amount of the snow particles on the first bogie reduced by 23.94% in the minimum among the equipment by the quantitative analysis of the snow particles. Instead, the increasing degree of the rear deflectors will at some degrees increase the snow particles on the heat-producing components such as motors and the gear covers of the rest bogies.