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智慧基础设施前沿论坛:Tabu Search Strategies for Variable Speed Limit Control at a Lane Drop Bottleneck (基于禁忌搜索算法的车道瓶颈区域可变限速控制)

报告题目:Tabu Search Strategies for Variable Speed Limit Control at a Lane Drop Bottleneck (基于禁忌搜索算法的车道瓶颈区域可变限速控制)

主  讲  人:Dr. Wei (David) Fan  范围

报告时间:2019年6月11日(星期二)上午9:00

地        点:土木与交通学院 309会议室

Dr. Wei (David) Fan currently serves as a tenured full professor in the Department of Civil and Environmental Engineering (CEE) at The University of North Carolina at Charlotte (UNCC). He is the Director of the USDOT University Transportation Center for Advanced Multimodal Mobility Solutions and Education (CAMMSE – http://cammse.uncc.edu/), a five-year $7.7 million multi-campus research center funded by USDOT. Dr. Fan holds a Ph.D. (May 2004) in Civil Engineering – Transportation from the University of Texas at Austin (Hook ’em Horns!). He was a Senior Analytical Optimization Software Developer for the R&D Department at SAS Institute Inc. located in Cary, North Carolina from June 2004 – August 2006.

专家介绍

Dr. Fan’s primary research interests include big data analytics for transportation (travel demand analysis, transportation safety data analysis, discrete choice modeling, machine learning and artificial intelligence); connected and autonomous vehicles (technologies, and impacts); multimodal transportation and shared mobility (non-motorized transportation including bicycle and public transit systems planning and operations, carsharing, and bike-sharing); traffic system operation and control (traffic simulation, and active traffic management including variable speed limits and managed lanes); transportation system analysis and network modeling (equilibrium-based traffic assignment, network design and highway improvements, travel time reliability, freeway bottleneck identification and mitigation, and congestion pricing); and Operations research applications and computer software development using C/C++/Java/SAS. Dr. Fan serves as an associate editor of IEEE Transactions – Intelligent Transportation Systems, an associate editor of ASCE Journal of Transportation Engineering, Part A: Systems, and an associate editor of International Journal of Transportation Science and Technology while also serving as a member of three other transportation journal editorial boards. Dr. Fan also serves as a member on the National Science Foundation (NSF) review panels, the National Cooperative Highway Research Program (NCHRP) panels, the Transit Cooperative Research Program (TCRP) panel and three Transportation Research Board (TRB) committees. He has been working as an active ad hoc reviewer for more than 20 prestigious journals as well as the national Highway Capacity Manual (HCM) (2010 version). He was selected by the students as the Best Civil Engineering Professor of the Year 2007 and was a proud ASCE Excellence in Civil Engineering Education (ExCEEd) Teaching Fellow in 2007.

Dr. Fan has been and is involved in many sponsored projects (over 14 million dollars in funding), having been principal or co-principal investigator on many research studies for the U. S. Department of Transportation (USDOT), Federal Highway Administration (FHWA), National Cooperative Highway Research Program (NCHRP), SHRP2 Education Connection, Texas Department of Transportation (TxDOT) and North Carolina Department of Transportation (NCDOT). He had published more than 100 journal articles, proceeding papers and technical reports on big data analytics for transportation, connected and autonomous vehicles, multimodal transportation and shared mobility; traffic system operation and control, and transportation system analysis and network modeling . He is a registered professional engineer in Texas.

  • 德克萨斯大学奥斯汀分校交通工程专业博士
  • 北卡罗莱纳大学土木与环境工程系终身教授
  • 美国交通部国家先进多模式交通研究与教育中心主任
  • 美国北卡罗莱纳大学交通运营和优化研究中心主任
  • 美国北卡罗莱纳大学交通工程组带头人
  • 美国北卡罗莱纳大学交通工程学生会指导教师
  • 美国德克萨斯州注册工程师
  • 国际期刊世界电气电子工程师学会智能交通系统(IEEE Transactions – Intelligent Transportation Systems)汇刊杂志副主编
  • 美国土木协会交通工程(ASCE Journal of Transportation Engineering, Part A: Systems)杂志副主编
  • 国际交通科学与技术(International Journal of Transportation Science and Technology)杂志副主编
  • 世界联合运输,国际交通运输等杂志编委
  • Accident Analysis and Prevention; ASCE Journal of Computing in Civil Engineering; ASCE Journal of Transportation Engineering, Part A: Systems; Computer-Aided Civil and Infrastructure Engineering; IEEE Transactions on Intelligent Transportation Systems; Transportation; Transportation Research Part B; Transportation Research Part C; Transportation Science等多种国际著名运输研究刊物审稿人
  • 美国国家自然科学基金,美国联邦公路局美国公路合作研究项目, 美国联邦公路局美国公交合作研究项目等专家评审人
  • 美国土木工程协会(ASCE)国家车联网自动驾驶车辆影响评估委员会,公共交通委员会,铁路交通委员会等委员
  • 美国科学院交通研究理事会(TRB) 公路铁路道口委员会, 运输设备维护委员会, 公共交通创新与技术委员会委员, 副大众运输委员会, 交通运输经济委员会等委员
  • 世界交通运输大会车辆网学科,联合主席
  • 目前杂志共收录62篇文章,34 篇SCI收录, 50篇EI收录,20篇在审,作为课题负责人总研究金额超过一千四百万美元
  • 2016美国北卡罗莱纳大学-夏洛特工程学院最佳研究生教学提名奖
  • 2012年德克萨斯大学-泰勒最佳研究奖 (University President’s Research Award)
  • 2011年由美国德克萨斯州交通部提名给美国运筹学和管理科学协会(INFORMS) Franz Edelman杰出研究奖
  • 收录在2010 和2007世界名人录
  • 美国德克萨斯大学-泰勒工程学院年度奖项,最佳教学和研究奖,2007
  • 美国土木工程协会(ASCE)土木工程优秀教育奖项-会士(Fellow),2007
  • 2004年美国西南地区大学交通中心美国交通部交通科学最高奖Robert Herman提名奖

报告内容

A tabu search–based algorithm is developed in this study and applied for optimizing a variable speed limit (VSL) control system. A macroscopic traffic flow model is used to predict the traffic states over the prediction horizon. The objective of the VSL control is to minimize the total value of travel time and total value of speed variation on the selected freeway segments. Sensitivity analyses are conducted for the tabu search parameters. Different weight sets of the objective function are selected and tested. Solution qualities from the tabu search algorithm and sequential quadratic programming (SQP) algorithm are compared. Numerical results clearly indicate that the proposed tabu search outperforms the SQP, which is used as a benchmark. The control results also show that the VSL can effectively reduce total travel time and total speed variation at a lane drop bottleneck. The relationships between the number of VSL control segments and total travel time, total speed variation, and combined objective function value corresponding to different weight sets are also given.

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