Assessing the social costs of urban transport infrastructure options in low and middle income countries

ABSTRACT

This paper develops cost models for urban transport infrastructure options in situations where motorcycles and various forms of taxis are important modes of transport. The total social costs (TSCs) of conventional bus, Bus Rapid Transit (BRT), Monorail, Metro (Elevated Rail), car, motorcycle, Taxi and Uber are calculated for an urban corridor covering operator, user and external costs. Based on the parameters for a 7?km corridor in Hanoi, Vietnam, the results show the lowest average social cost (ASC) transport modes for different ranges of demand. Motorcycle might be the best option at low demand levels while conventional bus has advantages with low-medium demand. At medium demand levels, bus-based technologies and Monorail are competitive options while Metro, with a higher person capacity, is the best alternative at the highest demand levels. Compared to other modes, the ASCs of car and Taxi/Uber are greater because of high capital cost (related to vehicles) per passenger and low occupancy. Transport planners and decision makers in low and middle income countries (LMICs) can draw on the findings of this study. However, various limitations are identified and additional research is suggested.     

产业转移背景下西部运输需求的完全分解模型

研究西部综合运输系统需求驱动因素，将产业转移因素考虑在内，对原有包含三大因素的完全分解模型进行改进，构建包含经济总量、运输需求强度、产业转移和产业结构整体变动等四大因素的完全分解模型，根据2002-2015年统计数据对西部地区综合运输系统需求进行实例计算.研究结果表明，经济总量增长是西部综合运输系统需求增长的主要原因，随着经济增速放缓，产业转移促进政策的出台，运输需求强度变化和产业转移的影响逐渐显著.在产业转移背景下，西部地区应该根据产业转移发展态势，有针对性地做好综合运输系统布局，创造更好的条件承接产业转移.     

城市绿色出行内涵和评价指标体系框架研究

绿色出行发展的根本目的是为了实现城市交通可持续发展,实现出行"安全、畅通、高效、舒适、环保、节能",从而实现社会、经济、交通和环境的协调发展。本文通过对绿色出行的概念、内涵、特征和实现途径等相关理论进行解读,确定绿色出行系统的主要构成;采用计划行为理论、交通需求管理理论等多视角,对影响和制约城市绿色出行发展的关键因素进行分析和识别,并研究提出围绕保障能力、基础设施、运输装备、运营服务等方面的绿色出行评价指标体系框架。     

基于候选列车集与弹性需求的城际铁路列车开行方案优化

城际铁路列车服务水平直接影响着全天各时段旅客出行需求量。为了研究这种影响关系,获得吻合出行需求的城际列车开行方案,首先建立旅客时段出行需求与广义出行费用间的弹性需求函数,并基于给定候选列车集构造旅客出行网络,进而以最大化列车开行收益为优化目标,构建面向弹性需求的城际列车开行方案优化模型。模型结合弹性客流在出行网络上的路径选择,从候选列车集中选择开行列车,并优化其停站方案与始发时刻。在生成初始列车开行方案基础上,设计其邻域解生成策略,构建求解模型的模拟退火算法。算例优化不同分布客流的列车开行方案,结果表明:模型与算法能够获得更吻合弹性需求的列车开行方案,且有助于提高旅客服务水平与企业经济效益。     

The station-free sharing bike demand forecasting with a deep learning approach and large-scale datasets

The station-free sharing bike is a new sharing traffic mode that has been deployed in a large scale in China in the early 2017. Without docking stations, this system allows the sharing bike to be parked in any proper places. This study aimed to develop a dynamic demand forecasting model for station-free bike sharing using the deep learning approach. The spatial and temporal analyses were first conducted to investigate the mobility pattern of the station-free bike sharing. The result indicates the imbalanced spatial and temporal demand of bike sharing trips. The long short-term memory neural networks (LSTM NNs) were then developed to predict the bike sharing trip production and attraction at TAZ for different time intervals, including the 10-min, 15-min, 20-min and 30-min intervals. The validation results suggested that the developed LSTM NNs have reasonable good prediction accuracy in trip productions and attractions for different time intervals. The statistical models and recently developed machine learning methods were also developed to benchmark the LSTM NN. The comparison results suggested that the LSTM NNs provide better prediction accuracy than both conventional statistical models and advanced machine learning methods for different time intervals. The developed LSTM NNs can be used to predict the gap between the inflow and outflow of the sharing bike trips at a TAZ, which provide useful information for rebalancing the sharing bike in the system.     

The allocation problem of electric car-sharing system: A data-driven approach

Car-sharing is an emerging transportation mode with increasing applications of electric vehicles (EVs). One of the important issues for one-way electric car-sharing systems (ECS) is unbalanced vehicle distributions and high relocation costs. To improve its efficiency and overall profit, this research proposes a data-driven optimization model with the consideration of demand uncertainty. Firstly, a large amount of historical order data from an ECS company are analyzed to characterize the dynamics of the vehicles and the behavioral features of the users. An important observation is that the daily demand by users, i.e., pick-ups, follows Poisson distribution; and the arrival rates vary across time exhibiting four major temporal stages. Based on this observation, this research constructs the ECS reallocation problem as a data-driven optimization model which is a combination of a probability expectation model and a linear programming problem with real-time data as input. More importantly, different from existing research, this research formulates the profit as the mathematical expectation of a discrete random variable with uncertain consumer demands. This allows for a comprehensive consideration of all possible future demands. Furthermore, driving range constraint has been considered in the proposed model as EV is the focus of this paper. A linear solution method is proposed to obtain the global optimal. At the end, the model is validated using real data from 30 ECS stations. The results indicate the daily improvement of profit could be as high as 19.05% with an average of 10.16%.     

中国第三方物流的市场潜力及其开发策略

简要分析了中国传统物流业所处的困境及其原因,指出提高服务质量、挖掘市场潜力才是摆脱困境的最根本途径;根据调查所得数据,对潜在需求的规模、没有走向市场的原因、第三方物流企业的目标市场以及市场需求的服务内容等进行了较深入的探讨,并据此提出了第三方物流企业开发市场的基本策略。     

运输需求经济分析

在阐述消费者剩余理论的基础上,提出了运输供给的品质与价格应定位在需求方能得到一定利益的前提下,为此建立了运输需求经济成本计量模型,并定性分析了该模型的构成要求对用户经济成本的影响,分析表明,运输价格对供需双方的影响并不对称,不宜以价格为主要因子来分析供需平衡规律,运输对象价值越高,运输过程中消耗对运输经济成本影响越小。     

基于乘客需求的地铁枢纽通道信息系统评价方法研究

为了更好地满足乘客对地铁枢纽通道信息不同程度的需求,文中基于马洛斯需求理论系统地分析了地铁乘客枢纽需求信息层次;利用KANO模型设置问卷对乘客需求信息进行调查,研究乘客对地铁枢纽通道各类信息的需求程度,提出了基于乘客需求的地铁枢纽通道信息系统评价方法,并就乘客对各类信息的敏感度进行了探讨.     

加强城市交通规划研究与实践推动城市交通发展模式转变

针对各种城市交通问题日益凸显,重点围绕加强城市交通规划研究与实践、推动城市交通发展模式转变展开探讨.首先指出我国城市交通在综合交通区域统筹、小汽车与公共交通发展、绿色交通实践、交通需求管理四个方面的发展现状与趋势.提出要加快转变城市交通发展观念,坚持节约资源、服务民生、和谐有序、科学决策.强调应继续贯彻和推进优先发展城...