中国区域轨道交通发展的宏观政策思考

区域轨道交通是国家新型城镇化发展的必然选择。区域轨道交通发展过程中在规划、审批、跨区域和跨部门协调、行业管理以及投融资等方面存在较多问题,已不能适应城市群和都市圈的发展要求。通过分析区域轨道交通发展的现状、特点及上述问题,提出应统筹区域轨道交通规划,创新规划审批机制,建立跨行政区划、跨部门协调机制,加强轨道交通行业管理,完善投融资体制机制等发展策略。在此基础上,阐述了具体的宏观发展政策,以便理顺区域轨道交通发展关系、完善区域轨道交通发展政策、促进区域轨道交通健康及可持续发展。     

基于换乘运力协调的地铁列车运行调整策略

为了应对城市轨道交通网络化条件下的延误影响,提出基于线路间换乘运力协调的列车运行调整策略.通过上海轨道交通系统的多源运营大数据分析,得到运行延误对相邻线路列车间衔接关系和换乘站客流组成的影响规律,提出衔接调整策略和分流调整策略.结合相邻线路连接关系,考虑客流需求和站台能力约束,给出换乘运力协调方案的求解算法,并分析策略适用情况.实例验证结果表明,线间协调调整策略能够有效降低延误影响,优于传统的延误本线疏解方案,可为网络化运营条件下的延误管理提供解决方案.     

长三角城市群交通发展新趋势与路径导向

长三角城市群城市间分工协作和区域治理日趋完善,交通发展呈现新的趋势和挑战。从城际关系、枢纽格局、空间演变、供需关系、理念技术五个方面探讨长三角城市群交通发展新的趋势特征以及衍生问题。区域及城际交通体系层面,提出面向全局的交通资源优化配置和面向城镇群空间的城际客运交通系统整合两条路径;城市交通转型和可持续发展层面,提出交通与空间协同发展、交通系统整合提效、交通精细化管理三项策略;新理念下交通发展层面,提出促进低碳交通、应用新技术引导交通革新、主动适应新态势三类导向。最后,从体制机制层面提出相关建议。     

信息技术在汽车维修中的应用研究

为有效提升汽车维修成效,实现故障原因的快速判定与处理,需构建起完善的汽车维修体系,强化维修服务能力.文章以信息技术作为切入点,在明确现阶段汽车维修存在问题的基础上,对现有的汽车维修方式做出针对性的调整,稳步增强汽车故障诊断、排除成效,促进维修工作的信息化、智能化,旨在为后续汽车维修工作的开展提供借鉴参考.     

A two-sided market platform analysis for the electric vehicle adoption: Firm strategies and policy design

This study explores how to facilitate the electric vehicle (EV) diffusion from a two-sided market platform competition. We develop a stylized model depicting the platform competition between electric and gasoline vehicles by combining indirect network effects of consumer and energy supplier sides as well as vehicle manufacturers’ profits. The findings of this study provide several meaningful strategic and policy implications for EV manufacturers and policymakers who wish to enhance EV diffusion. First, EV sales are significantly influenced by indirect network effects from the energy supplier side to the consumer side, and vice versa. This implies that EV manufacturers who wish to boost EV diffusion should implement a strategy providing energy suppliers with incentives to willingly join the EV platform. Second, the dynamic nature of the effects of energy costs on platform competition might render counter-intuitive evidence that the drop in oil prices does not always negatively influence EV sales. This requires EV manufacturers to prepare a contingent strategy adjusting to such unexpected conditions. Third, governments should consider the energy supplier side as well as the consumer side in designing EV diffusion policies. When governments have a very challenging EV diffusion target, a balanced policy, which treats both gasoline and electric vehicle technologies fairly, may be more effective than a consumer subsidy policy.     

A methodology to evaluate driving efficiency for professional drivers based on a maturity model

Over the last decade, transport companies have tried to reduce fuel consumption using efficient driving programs. In them, motorists have to apply different specific techniques while driving. Thus, to succeed in this learning process there are two key elements: the knowledge of efficient driving techniques and the drivers’ motivation. The latter is a human factor which companies usually bring about by using reward systems. In this case, having a fair evaluation mechanism is the keystone to determine goal fulfilment. This paper presents a complete methodology to evaluate driving efficiency of drivers in professional fleets. The evaluation methodology is based on a continuous process which determines the maturity of the motorist in different aspects, such as the efficiency during the start of the vehicle movement, during motion or in stop events. In addition, the evaluation methodology includes an early-classification method to establish the initial efficiency level of the individual drivers which permits an adaptation of the learning process from the beginning. A dashboard has also been developed to support the evaluation methodology. 880 professional drivers have been evaluated with this methodology. Results show that the evaluation methodology identifies drivers’ weaknesses, to be improved in successive iterations of the learning process.     

The Share-a-Ride problem with stochastic travel times and stochastic delivery locations

We consider two stochastic variants of the Share-a-Ride problem: one with stochastic travel times and one with stochastic delivery locations. Both variants are formulated as a two-stage stochastic programming model with recourse. The objective is to maximize the expected profit of serving a set of passengers and parcels using a set of homogeneous vehicles. Our solution methodology integrates an adaptive large neighborhood search heuristic and three sampling strategies for the scenario generation (fixed sample size sampling, sample average approximation, and sequential sampling procedure). A computational study is carried out to compare the proposed approaches. The results show that the convergence rate depends on the source of stochasticity in the problem: stochastic delivery locations converge faster than stochastic travel times according to the numerical test. The sample average approximation and the sequential sampling procedure show a similar performance. The performance of the fixed sample size sampling is better compared to the other two approaches. The results suggest that the stochastic information is valuable in real-life and can dramatically improve the performance of a taxi sharing system, compared to deterministic solutions.     

短时记忆与外语学习

短时记忆在外语学习中起着十分重要的作用。本文论述了短时记忆的特点及与长一时记忆、工作记忆的关系，探讨了短时记忆与外语学习的关系，最后提出了提高外语学习的一些方法。     

投标过程中的不平衡报价

为了获得更多的收益,投标者在投标过程中必须讲究一定的报价策略.不平衡报价就是投标者经常使用的一种有效方法.笔者给出了不平衡报价的意义、使用条件,在此基础上分析了不平衡报价给投标人带来的收益和可能存在的风险,并利用线形规划理论提出收益预测模型.