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.     

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.     

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.     

On the variance of recurrent traffic flow for statistical traffic assignment

This paper generalizes and extends classical traffic assignment models to characterize the statistical features of Origin-Destination (O-D) demands, link/path flow and link/path costs, all of which vary from day to day. The generalized statistical traffic assignment (GESTA) model has a clear multi-level variance structure. Flow variance is analytically decomposed into three sources, O-D demands, route choices and measurement errors. Consequently, optimal decisions on roadway design, maintenance, operations and planning can be made using estimated probability distributions of link/path flow and system performance. The statistical equilibrium in GESTA is mathematically defined. Its multi-level statistical structure well fits large-scale data mining techniques. The embedded route choice model is consistent with the settings of O-D demands considering link costs that vary from day to day. We propose a Method of Successive Averages (MSA) based solution algorithm to solve for GESTA. Its convergence and computational complexity are analyzed. Three example networks including a large-scale network are solved to provide insights for decision making and to demonstrate computational efficiency.     

盾构法施工单机核算管理模式的应用

近年来盾构机越来越多地应用于各种隧道工程中,其中地铁应用的数量最多,约占80%。现代盾构已演变成为一种高度智能化的大型工程机械装备,对其控制的好坏将直接影响到整个工程的施工成本和企业的经营效益,而通过单机核算降低机械成本是降低施工成本、提高企业效益的有效手段,因此推行盾构法施工单机核算显得尤为重要。文章结合地铁2222标施工项目,重点介绍了盾构法单机核算管理模式及其在施工中的应用。     

乾元公司铁路专用线场站模式探讨

目前,传统的铁路专用线建设模式是铁路专用线自接轨站接轨,通过区间正线引入厂区的建设模式,这种模式的区间正线受地形条件、厂区位置和沿线规划影响较大,这些影响将不可避免地导致铁路专用线建设工程投资的增加,如能根据运输性质考虑缩短区间正线长度,在接轨站旁边设装车作业站,将大大减少专用线工程投资.以乾元公司铁路专用线建设模式为例来研究铁路专用线场站模式,就如何在接轨站旁边设装车作业站,实现接轨站设备与铁路专用线共用进行探讨.     

基于OWA与灰色聚类的城市轨道交通PPP融资风险评价方法研究

针对城市轨道交通PPP融资成本高、投资回收期长、不确定性因素多等特点导致整个融资过程充满风险,且难以进行科学的评价,进而增加风险评价难度的问题,提出基于OWA与灰色聚类的城市轨道交通PPP融资风险评价方法。首先从全寿命周期角度构建城市轨道交通PPP融资风险指标体系。然后基于OWA算子对专家决策数据按照降序的方式重新排序,消除极值带来的不利影响,加权得出指标的权重值。最后考虑指标的灰色性、信息不完整性,构建灰色白化权函数实现指标信息的透明化,完成对PPP融资风险的聚类分析。应用构建的模型对郑州地铁1号线一期工程PPP融资风险进行评价,认为该地铁工程PPP融资风险等级高,应重点关注前期策划、社会资本、政策环境、设计质量、成本超支、建设质量、残值7个主要风险指标的控制,以期为该项目融资风险管理提供建议,并进一步丰富城市轨道交通PPP融资风险的评价方法。     

复杂地形条件下桥隧相连隧道洞口结构设计研究

蒙华铁路坪桥1号隧道进口洞顶基岩外凸、洞顶以下岩面高且直立、洞顶上部地形偏压高陡,地形条件极其复杂。营盘山大桥与坪桥1号隧道进口紧密相连,存在桥台与隧道洞门结构相互干扰以及边坡防护、隧道出洞和洞口场地布置等一系列难题,设计难度极大。为解决这些难题,通过对现场实际地形、地质情况进行研究,对比分析"整体式"与"分离式"桥隧相连结构的优缺点,提出桥台与隧道相结合的"整体式"桥隧相连结构方案;同时,针对地形偏压高陡,提出非对称结构设计方案,实现了隧道"零"仰坡出洞,解决了洞口边坡防护的难题;最后,提出架立临时贝雷梁的方案,解决了隧道出洞及洞口场地布置的难题。     

A receding horizon sliding control approach for electric powertrains with backlash and flexible half-shafts

Active control of electric powertrains is challenging, due to the fact that backlash and structural flexibility in transmission components can cause severe performance degradation or even instability of the control system. Furthermore, high impact forces in transmissions reduce driving comfort and possibly lead to damage of the mechanical elements in contact. In this paper, a nonlinear electric powertrain is modelled as a piecewise affine (PWA) system. The novel receding horizon sliding control (RHSC) idea is extended to constrained PWA systems and utilised to systematically address the active control problem for electric powertrains. Simulations are conducted in Matlab/Simulink in conjunction with the high fidelity Carsim software. RHSC shows superior jerk suppression and target wheel speed tracking performance as well as reduced computational cost over classical model predictive control (MPC). This indicates the newly proposed RHSC is an effective method to address the active control problem for electric powertrains.