专业旅游城市综合交通规划技术方法研究——以三亚市为例

为完善专业旅游城市的综合交通规划技术体系,通过总结国外专业旅游城市在综合交通规划建设过程中的经验,在识别旅游交通特征的基础上,分析专业旅游城市对交通体系的基本要求。针对专业旅游城市交通规划面临的关键问题和挑战,指出应将旅游交通特征和规律的研究贯穿综合交通规划始终,实现旅游交通与城市居民常规交通高度融合,进而提出综合交通规划技术体系框架。以三亚市为例,重点探讨了专业旅游城市交通设施合理规模的确定,以及交通设施规划基本思路。     

城市连绵地区轨道交通服务层级构建

面向城市连绵地区构建与之适应的轨道交通系统,关键在于提供具有针对性的服务层级,满足区域范围内不同的出行需求,应对出行链的复杂性和多样性。从城镇群、都市区、中心城市三个层面分析城市连绵地区的典型空间形态,并探讨与之对应的城际出行、城郊出行、城市内部出行活动特征。提出构建差异化的轨道交通层级,即区域轨道交通、市域轨道交通、市区轨道交通,重点探讨各个层级轨道交通的构成、作用、线路技术特征等,以及不同层级的衔接关系。     

基于城市功能整合的枢纽区域研究

为实现综合客运枢纽与城市空间结构及功能布局的协调发展,首先基于中国城镇化进程及现行体制,指出综合客运枢纽与城镇化发展不协调、与城市未能有机融合、综合客运枢纽交通功能不健全等主要问题。结合综合交通发展趋势,提出未来综合客运枢纽将呈现普及化、综合化、规模化的发展特点。借鉴国外枢纽成功经验,提出以多元交通方式整合、枢纽与城市功能区融合、立体多层连廊连通整个区域为主要特征的枢纽区域概念,并分析了枢纽区域的主要功能。最后,从规划、建设、运营体制机制,法律法规调整等方面提出综合客运枢纽与城市协调发展的相关建议。     

交通拥挤收费政策的经济影响分析

针对交通拥挤收费政策普遍采用的成本—效益分析(CBA)框架存在的缺陷,首先回顾了拥挤收费的经济学原理。然后从研究方法和研究内容两方面剖析CBA框架存在的问题,指出时间价值计算不严谨及交易成本被忽视等问题将对政策实施效果带来负面影响,并就伦敦和斯德哥尔摩拥挤收费案例社会净收益计算结果的可靠性提出质疑。接着结合各参与方的净收益分析、收费区商业影响及其他产业影响等内容,指出CBA分析框架可扩展的内容。最后提出了改进的经济影响分析框架,为全面评价拥挤收费政策效果提供参考。     

天津市双城战略下的交通特征与发展对策

为更好地促进天津市双城空间战略的实现以及城市交通的可持续发展,基于天津市4次居民出行调查,总结改革开放30年来城市交通在出行强度、出行分布、出行结构方面的交通特征与规律。从用地布局和交通模式两方面有针对性地提出了发展对策。用地布局方面,提出提升滨海新区核心区城市职能、注重职住平衡、提倡土地混合利用的发展策略;交通模式方面,针对双城间交通、双城对外交通、双城内部交通提出了具体策略。     

Multi-objective bilevel construction material transportation scheduling in large-scale construction projects under a fuzzy random environment

Abstract

This paper investigates a transportation scheduling problem in large-scale construction projects under a fuzzy random environment. The problem is formulated as a fuzzy, random multi-objective bilevel optimization model where the construction company decides the transportation quantities from every source to every destination according to the criterion of minimizing total transportation cost and transportation time on the upper level, while the transportation agencies choose their transportation routes such that the total travel cost is minimized on the lower level. Specifically, we model both travel time and travel cost as triangular fuzzy random variables. Then the multi-objective bilevel adaptive particle swarm optimization algorithm is proposed to solve the model. Finally, a case study of transportation scheduling for the Shuibuya Hydropower Project in China is used as a real world example to demonstrate the practicality and efficiency of the optimization model and algorithm.     

Shared ride services in North America: definitions,impacts, and the future of pooling

ABSTRACT

Shared ride services allow riders to share a ride to a common destination. They include ridesharing (carpooling and vanpooling); ridesplitting (a pooled version of ridesourcing/transportation network companies); taxi sharing; and microtransit. In recent years, growth of Internet-enabled wireless technologies, global satellite systems, and cloud computing - coupled with data sharing – are causing people to increase their use of mobile applications to share a ride. Some shared ride services, such as carpooling and vanpooling, can provide transportation, infrastructure, environmental, and social benefits. This paper reviews common shared ride service models, definitions, and summarises existing North American impact studies. Additionally, we explore the convergence of shared mobility; electrification; and automation, including the potential impacts of shared automated vehicle (SAV) systems. While SAV impacts remain uncertain, many practitioners and academic research predict higher efficiency, affordability, and lower greenhouse gas emissions. The impacts of SAVs will likely depend on the number of personally owned automated vehicles; types of sharing (concurrent or sequential); and the future modal split among public transit, shared fleets, and pooled rides. We conclude the paper with recommendations for local governments and public agencies to help in managing the transition to highly automated vehicles and encouraging higher occupancy modes.     

Optimum Capacity for Intermodal Container Terminals

Abstract

Achievement of a desirable level of customer service at intermodal terminals mainly depends on the efficient loading and unloading of trains without delays. The efficiency of the transfer between the modes in the terminal area can have a significant effect on these delays. In this article, an analytically based simulation model is developed to investigate delays of trains for different service configurations. Simulation outputs are used to find an optimum balance of the cost of train delays and variation from the desired level of service. Data from the Acacia Ridge Terminal in Brisbane, Australia are used to validate and test the model.     

Ground delay program planning under uncertainty in airport capacity

Abstract

This paper presents an algorithm for assigning flight departure delays under probabilistic airport capacity. The algorithm dynamically adapts to weather forecasts by revising, if necessary, departure delays. The proposed algorithm leverages state-of-the-art optimization techniques that have appeared in recent literature. As a case study, the algorithm is applied to assigning departure delays to flights scheduled to arrive at San Francisco International Airport in the presence of uncertainty in the fog clearance time. The cumulative distribution function of fog clearance time was estimated from historical data. Using daily weather forecasts to update the probabilities of fog clearance times resulted in improvement of the algorithm's performance. Experimental results also indicate that if the proposed algorithm is applied to assign ground delays to flights inbound at San Francisco International airport, overall delays could be reduced up to 25% compared to current level.     

Workplace travel plans: can they be evaluated effectively by experts?

Employers are regularly involved in transport planning and characteristic workplace-oriented tools include: (1) travel plans for building projects, (2) mandatory travel plans, (3) subsidies to employers with an advanced travel plan and (4) best travel plan awards. In all cases, experts judge the level of car use. We argue that decision-makers might benefit from a multiple regression-based benchmark modelling tool that estimates the expected share of the car. In this paper, we estimate the share of car users in the commuting modal split at workplaces. However, since the amount of information available to experts differs, we gradually add information to the model to measure the impact of data availability. Without historic data on modal split, the current share can only be predicted moderately well, i.e. within a 20% range. Besides adding the past, results improve by using homogenous and regional subsamples. Nevertheless, quantitative analyses do not make expert knowledge obsolete.