Policy packages for modal shift and CO2 reduction in Lille,France

This paper proposes different policy scenarios to cut CO₂ emissions caused by the urban mobility of passengers. More precisely, we compare the effects of the ‘direct tool’ of carbon tax, to a combination of ‘indirect tools’ – not originally aimed at reducing CO₂ (i.e. congestion charging, parking charges and a reduction in public transport travel time) in terms of CO₂ impacts through a change in the modal split. In our model, modal choices depend on individual characteristics, trip features (including the effects of policy tools), and land use at origin and destination zones. Personal “CO₂ emissions budgets” resulting from the trips observed in the metropolitan area of Lille (France) in 2006 are calculated and compared to the situation related to the different policy scenarios. We find that an increase of 50% in parking charges combined with a cordon toll of €1.20 and a 10% travel time decrease in public transport services (made after recycling toll-revenues) is the winning scenario. The combined effects of all the policy scenarios are superior to their separate effects.     

Capturing correlation with a mixed recursive logit model for activity-travel scheduling

Representing activity-travel scheduling decisions as path choices in a time–space network is an emerging approach in the literature. In this paper, we model choices of activity, location, timing and transport mode using such an approach and seek to estimate utility parameters of recursive logit models. Relaxing the independence from irrelevant alternatives (IIA) property of the logit model in this setting raises a number of challenges. First, overlap in the network may not fully characterize perceptual correlation between paths, due to their interpretation as activity schedules. Second, the large number of states that are needed to represent all possible locations, times and activity combinations imposes major computational challenges to estimate the model. We combine recent methodological developments to build on previous work by Blom Västberg et al. (2016) and allow to model complex and realistic correlation patterns in this type of network. We use sampled choices sets in order to estimate a mixed recursive logit model in reasonable time for large-scale, dense time-space networks. Importantly, the model retains the advantage of fast predictions without sampling choice sets. In addition to estimation results, we present an extensive empirical analysis which highlights the different substitution patterns when the IIA property is relaxed, and a cross-validation study which confirms improved out-of-sample fit.     

Traffic and emissions impact of congestion charging in the central Beijing urban area: A simulation analysis

Congestion charging is being considered as a potential measure to address the issue of substantially increased traffic congestion and vehicle emissions in Beijing. This study assessed the impact of congestion charging on traffic and emissions in Beijing using macroscopic traffic simulation and vehicle emissions calculation. Multiple testing scenarios were developed with assumptions in different charging zone sizes, public transit service levels and charging methods. Our analysis results showed that congestion charging in Beijing may increase public transit use by approximately 13%, potentially reduce CO and HC emissions by 60–70%, and reduce NOx emissions by 35–45% within the charging zone. However, congestion charging may also result in increased travel activities and emissions outside of the charging zone and a slight increase in emissions for the entire urban area. The size of charging zone, charging method, and charging rate are key factors that directly influence the impact of congestion charging; improved public transit service needs to be considered as a complementary approach with congestion charging. This study is used by Beijing Transportation Environment and Energy Center (BTEC) as reference to support the development of Beijing’s congestion charging policy and regulation.     

地铁供电系统中压开关柜电流分析理论和方法

通过分析地铁供电系统不同电压等级的设备电流特征,确定35 kV电压等级设备电流可构造标准曲线,采用机器智能学习算法分析、测算地铁供电系统中各类开关峰谷时段运行电流,以均值-方差方法确定电流的高度异常偏离点,实现异常点数据周期内统计以及实时提醒功能。应用电流实测值分析电流在工作日、节假日的不同曲线,为负荷预测和非正常运行方式下的负荷叠加风险提供预测和评估依据,保障供电系统的安全运行,提高负荷管控效率。     

汉巴南铁路兰渝联络线电分相设置方案研究

联络线电分相设置方案影响因素众多,且其设置与否对工程和运营的影响也较大。本文对汉巴南铁路兰渝联络线电分相设置方案进行研究,提出高速铁路设置关节式电分相联络线最短长度;对联络线电分相不同设置方案进行比选研究,并结合各方案的土建工程、信号系统、供电系统及限制因素提出布局优化措施,以期为联络线电分相合理设置与优化布局提供新思路。     

Electric vehicles and residential parking in an urban environment: Results from a stated preference experiment

This paper presents the results of a preference survey of 1545 respondents’ willingness to purchase electric vehicles (EVs) in Philadelphia. We pay particular attention to respondents’ willingness to pay for convenient charging systems and parking spaces. If the value of dedicated parking substantially outweighs the value of convenient charging systems, residential-based on-street charging systems are unlikely to ever be politically palatable. As expected, respondents are generally willing to pay for longer range, shorter charging times, lower operating costs, and shorter parking search times. For a typical respondent, a $100 per month parking charge decreases the odds of purchasing an EV by around 65%. Across mixed logit and latent class models, we find substantial variation in the willingness to pay for EV range, charge time, and ease of parking. Of note, we find two primary classes of respondents with substantially different EV preferences. The first class tends to live in multifamily housing units in central parts of the city and puts a high value on parking search time and the availability of on-street charging stations. The second class, whose members are likelier to be married, wealthy, conservative, and residing in single-family homes in more distant neighborhoods, are willing to pay more for EV range and charge time, but less for parking than the first group. They are also much likelier to consider purchasing EVs at all. We recommend that future research into EV adoption incorporate neighborhood-level features, like parking availability and average trip distances, which vary by neighborhood and almost certainly influence EV adoption.     

无人船在港口水域海事监管中的应用探讨

近年来,随着与船舶自主航行相关的信息技术、人工智能技术水平的提高,无人船舶行业取得了长足的发展,其在海上安保、环境监测等领域应用也越来越成熟。为推动无人船在海事管理方面的应用研究,破解港口水域海事监管手段不足的瓶颈问题,文中在分析港口水域海事监管特点和无人船系统建设条件的基础上,定量研究了无人船在港口水域海事监管应用面临的性能指标确定、船型平台选择、载荷设备搭配、运行管理体系建设等方面的具体问题,提出了一种港口水域海事监管无人船系统的应用解决方案。     

Evaluating sustainability of supply chains by two-stage range directional measure in the presence of negative data

Assessing sustainability of supply chains is a critical and increasingly complex problem. In recent years sustainability has received more attention in supply chain management (SCM) literature with triple bottom lines including social, environmental, and economic factors. Conventional data envelopment analysis (DEA) models consider decision making units (DMUs) as black boxes that consume a set of inputs to produce a set of outputs and do not take into consideration internal interactions of DMUs. Two-stage DEA models deal with such DMUs. However, existing two-stage DEA models are applicable only in technologies characterized by positive inputs/outputs. This paper aims to build and present a new two-stage DEA model considering negative input-intermediate-output data. Some numerical examples along with some theorems and properties are given to show capability of proposed method. The proposed ideas are used in a case study where 29 Iranian supply chains producing equipment of expendable medical devices are evaluated in terms of sustainability.     

A carbon footprint-based closed-loop supply chain model under uncertainty with risk analysis: A case study

The management of products’ end-of-life and the recovery of used products has gained significant importance in recent years. In this paper, we address the carbon footprint-based problem that arises in a closed-loop supply chain where returned products are collected from customers. These returned products can either be disposed of or be remanufactured to be resold as new ones. Given this environment, an optimization model for a closed-loop supply chain (CLSC) in which carbon emission is expressed in terms of environmental constraints, i.e., carbon emission constraints, is developed. These constraints aim to limit the carbon emission per unit of product supplied with different transportation modes. Here, we design a closed-loop network where capacity limits, single-item management and uncertainty on product demands and returns are considered. First, fuzzy mathematical programming is introduced for uncertain modeling. Then, the statistical approach to the possibility to synthesize fuzzy information is utilized. Therefore, using a defined possibilistic mean and variance, we transform the proposed fuzzy mathematical model into a crisp form to facilitate efficient computation and analysis. Finally, the risk caused by violating the estimated resource constraints is analyzed so that decision makers (DMs) can trade off between the expected cost savings and the expected risk. We utilize data from a company located in Iran.     

How the environmental impact affects the design of logistics networks based on cost minimization

The degree of centralization of the logistics network is one of the important strategic decisions to take. This issue has often been studied but mainly from a cost minimization focus. This research studies the influence of incorporating the environmental impact in logistics network design models, comparing the results with those obtained considering cost minimization only. A fuzzy biobjective optimization model is used to carry out a number of experiments. By weighting the relative importance of the two objectives, the differences with respect to the base cost minimization solution can be ascertained. Our results show that in general more material is moved through warehouses when the environmental impact is considered and more decentralized facilities are opened.