Optimization of highway work zone decisions considering short-term and long-term impacts.

详细信息   

• 作者：Yang ; Ning.
• 学历：Doctor
• 年：2010
• 导师：Schonfeld, Paul M.,eadvisorChang, Gang-Lenecommittee memberGoulias, Dimitrios G.ecommittee memberCorsi, Thomas M.ecommittee memberChien, Steven I-Jyecommittee member
• 毕业院校：University of Maryland
• Department：Civil Engineering
• ISBN：9781124078830
• CBH：3409974
• Country：USA
• 语种：English
• FileSize：1549212
• Pages：256

文摘

With the increase of the number, duration, and scope of maintenance projects on the national highway system, transportation agencies face great challenges in developing effective comprehensive work zone management plans which minimize the negative impacts on road users and workers. The types of maintenance operation, timing, duration, configuration, and user impact mitigation strategies are major considerations in developing work zone management plans. Some of those decisions may not only affect road users during the maintenance phase but also have significant impacts on pavement serviceability in future years. This dissertation proposes a systematic methodology for jointly optimizing critical work zone decisions, based on analytical and simulation models developed to estimate short-term impacts during the maintenance periods and long-term impacts over the pavement life cycle. The dissertation starts by modeling the effects of different work zone decisions on agency and user costs during the maintenance phase. An analytic one-time work zone cost model is then formulated based on simulation analysis results. Next, a short-term work zone decision optimization model is developed to find the best combination of lane closure and traffic control strategies which can minimize the one-time work zone cost. Considering the complex and combinatorial nature of this optimization problem, a heuristic optimization algorithm, named two-stage modified population-based simulated annealing 2PBSA), is designed to search for a near-optimal solution. For those maintenance projects that may need more detailed estimation of user delay or other impacts, a simulation-based optimization method is proposed in this study. Through a hybrid approach combining simulation and analytic methods along with parallel computing techniques, the proposed method can yield satisfactory solutions while reducing computational efforts to a more acceptable level. The last part of this study establishes a framework for jointly optimizing short-term and long-term work zone decisions with the objective of maximizing cost-effectiveness. Case studies are conducted to test the performance of the proposed methods and develop guidelines for development of work zone management plans.