台北公共交通月及无车日活动回顾与展望

台北国际无车日自2002年起举办了5次,由最早的骑自行车活动扩大至包含“走路上学日”与“公共交通月”丰富多彩的系列活动,渐渐获得民众认同。无车日活动的目标是通过活动的倡导和社会参与来改变民众使用交通工具的行为,潜移默化的效应可促使形成可持续交通政策,当可持续交通政策与基础设施建设落实后又可具体改变交通环境,形成良性的循环机制。首先说明了“无车日”的由来,并回顾台北都会区过去5年来举行无车日系列活动的内容与经验,同时基于活动的发展与成果归纳出无车日活动的成功要素,最后提出未来活动将扩大举办的内容、方式与展望,以期能为其他城市作参考。     

伦敦的公交优先政策及启示

通过对比分析的方法,将伦敦曾经面临过的与国内大中城市正面临的城市交通问题进行对比,研究了英国交通发展的历史,伦敦公交发展现状,着重研究了伦敦公交优先政策实施的主要措施.提出,公交优先是多种公共交通模式并存的优先发展,实现公交优先,需要整合各种交通基础设施,并将城市用地、交通需求管理和可持续性的公共交通三者结合起来共同考虑.最后,对提升现有常规公交的服务水平提出了5点具体建议.     

Exploring the issue of integrating logistics and traffic control in urban areas

This paper proposes an optimization framework for urban transportation networks’ (re-)design which explicitly takes into account the specific decision-making processes of ordinary users and logistic operators. Ordinary users are typically commuters whose travels consist of well-defined pairs of origin and destination points, while logistic operators make deliveries at multiple locations. Obviously, these two user classes have different objectives and scopes of action. These differences are seldom considered in traffic research since most models aggregate the flow demand in OD matrices and use assignment models to predict the response of all users as if the dynamics of their optimization processes were of the same nature. This work demonstrates that better results can be achieved if the particular features of each user class are included in the models. It potentially improves the estimation of the responses and allows managers to shape their control measures to address specific user needs.     

A new generalized travel cost based connectivity metric applied to Scandinavian airports

This article proposes a new, generalized travel cost based method to operationalize network accessibility provided by airports. The approach is novel as it integrates features of network topology with multiple quality aspects of scheduled air transport services into one metric. The method estimates generalized travel costs for the full set of feasible travel paths between an airport and all network destinations. Rooftop modeling accounts for schedule delay and isolates the most cost-efficient travel paths per O-D relation. Respecting the assumed arrival time preference of passengers and adjusting for destination importance, connectivity scores are derived. The method is then applied to explore changes in the global connectivity pattern of Scandinavian airports from 2004 to 2018. The results suggest distinct spatial differences throughout the network, but less pronounced in size than suggested by popularly applied connectivity measures. Findings also highlight the importance of the geographical location as a determinate of an airport’s connectivity.     

Benefit of speed reduction for ships in different weather conditions

Currently, the shipping industry is facing a great challenge of reducing emissions. Reducing ship speeds will reduce the emissions in the immediate future with no additional infrastructure. However, a detailed investigation is required to verify the claim that a 10% speed reduction would lead to 19% fuel savings (Faber et al., 2012).This paper investigates fuel savings due to speed reduction using detailed modeling of ship performance. Three container ships, two bulk carriers, and one tanker, representative of the shipping fleet, have been designed. Voyages have been simulated by modeling calm water resistance, wave resistance, propulsion efficiency, and engine limits. Six ships have been simulated in various weather conditions at different speeds. Potential fuel savings have been estimated for a range of speed reductions in realistic weather.It is concluded that the common assumption of cubic speed-power relation can cause a significant error in the estimation of bunker consumption. Simulations in different seasons have revealed that fuel savings due to speed reduction are highly weather dependent. Therefore, a simple way to include the effect of weather in shipping transport models has been proposed.Speed reduction can lead to an increase in the number of ships to fulfill the transport demand. Therefore, the emission reduction potential of speed reduction strategy, after accounting for the additional ships, has been studied. Surprisingly, when the speed is reduced by 30%, fuel savings vary from 2% to 45% depending on ship type, size and weather conditions. Fuel savings further reduce when the auxiliary engines are considered.     

Using GPS-data to determine optimum electric vehicle ranges: A Michigan case study

Fuel-switching personal transportation from gasoline to electricity offers many advantages, including lower noise, zero local air pollution, and petroleum-independence. But alleviations of greenhouse gas (GHG) emissions are more nuanced, due to many factors, including the car’s battery range. We use GPS-based trip data to determine use type-specific, GHG-optimized ranges. The dataset comprises 412 cars and 384,869 individual trips in Ann Arbor, Michigan, USA. We use previously developed algorithms to determine driver types, such as using the car to commute or not. Calibrating an existing life cycle GHG model to a forecast, low-carbon grid for Ann Arbor, we find that the optimum range varies not only with the drive train architecture (plugin-hybrid versus battery-only) and charging technology (fast versus slow) but also with the driver type. Across the 108 scenarios we investigated, the range that yields lowest GHG varies from 65 km (55+ year old drivers, ultrafast charging, plugin-hybrid) to 158 km (16–34 year old drivers, overnight charging, battery-only). The optimum GHG reduction that electric cars offer – here conservatively measured versus gasoline-only hybrid cars – is fairly stable, between 29% (16–34 year old drivers, overnight charging, battery-only) and 46% (commuters, ultrafast charging, plugin-hybrid). The electrification of total distances is between 66% and 86%. However, if cars do not have the optimum range, these metrics drop substantially. We conclude that matching the range to drivers’ typical trip distances, charging technology, and drivetrain is a crucial pre-requisite for electric vehicles to achieve their highest potential to reduce GHG emissions in personal transportation.     

城市公交车身轻量化分析与设计

作为城市枢纽的公交车,采用纯电动技术可作为降低城市环境污染、减少能源消耗的切入点。目前续驶里程短是制约纯电动公交发展的主要因素。可以通过增加动力电池的电量或者对整车进行轻量化来增加续驶里程。在轻量化设计方面,对高强钢、铝合金、镁合金、工程塑料和碳纤维等几种轻量化材料进行对比分析,从中选出目前较为合适的铝合金材料。通过理论计算与设计,再通过有限元分析手段进行验证,设计出合理的车身骨架用型材截面以及连接结构。实现减重的同时保证车身结构可靠性,同时通过全生命周期中成本评估对比,发现铝合金车身可以实现降本。     

适用于一票制公交大数据的系统化处理方法及应用 ——以银川市为例

为分析公交乘客出行特征,利用公交IC卡数据、公交GPS数据、车载机数据和单程站点关系表,通过各类数据关联融合,提出适用于一票制公交大数据的系统化处理方法。基于Oracle搭建分析数据库,采用Python语言编写代码,构建了乘客上车站点推断算法、基于出行链的乘客下车站点推断算法、基于概率的乘客下车站点推断算法和乘客换乘站点识别算法4种站点推断算法。基于此,运用银川公交大数据进行客流集散点识别、客流走廊识别,得到公交站点上下客流量分布情况、公交线路客流量分布情况、公交站点的换乘客流量分布情况。研究结果表明,一票制公交大数据系统化处理方法在分析公交乘客出行特征方面具有一定的应用价值。     

基于 VAR 模型的区域交通运输需求与GDP 的关系实证分析

为研究区域交通运输需求和经济发展之间的关系,运用协整理论进行实证分析,选取1985—2013年重庆货运周转量、客运周转量、GDP数据,建立交通运输需求与经济之间的VAR模型,运用脉冲响应和方差分解对系统进行动态分析。结果表明：交通运输需求和GDP之间存在长期协整关系,GDP带动交通运输业的发展,交通运输业对GDP的贡献率较小;但随着交通运输业的不断发展,在逐渐加大对区域经济的推动作用。最后根据实证分析的结论,对重庆市交通运输业的发展提出相关建议。     

各种运输方式协调发展模式探讨

基于江苏省交通运输现状,通过计算各种运输方式的外部广义费用,结合江苏省交通运输的实际情况,提出优先发展公路运输、铁路运输和公路、铁路运输兼顾发展的3种运输模式。根据外部广义费用计算结果,分析比较3种运输模式优劣势,最后基于公路运输为主,适度提高铁路运输的公、铁、水3种交通运输方式协调发展的综合运输模式的建议。