Identifying the early adopters of alternative fuel vehicles: A case study of Birmingham,United Kingdom

The transport sector has been identified as a significant contributor to greenhouse gas emissions. As part of its emissions reduction strategy, the United Kingdom Government is demonstrating support for new vehicle technologies, paying attention, in particular, to electric vehicles.Cluster analysis was applied to Census data in order to identify potential alternative fuel vehicle drivers in the city of Birmingham, United Kingdom. The clustering was undertaken based on characteristics of age, income, car ownership, home ownership, socio-economic status and education. Almost 60% of areas that most closely fitted the profile of an alternative fuel vehicle driver were found to be located across four wards furthest from Birmingham city centre, while the areas with the poorest fit were located towards the centre of Birmingham. The paper demonstrates how Census data can be used in the initial stages of identifying potential early adopters of alternative vehicle drivers. It also shows how such research can provide scope for infrastructure planning and policy development for local and national authorities, while also providing useful marketing information to car manufacturers.     

Assessing air quality and health benefits of the Clean Truck Program in the Alameda corridor,CA

In this paper, vehicle microscopic simulation and emission models were combined with an air pollutant dispersion model and a health assessment tool to quantify some social costs resulting from urban freight transportation in the Alameda corridor that links the Ports of Los Angeles and Long Beach to downtown Los Angeles. Traffic on two busy freeways, the I-710 and the I-110, and some heavily trafficked arterial roads was analyzed to estimate the health impacts caused by drayage truck emissions of particulate matter (PM) for four different years: 2005, which serves as a baseline for various pollution inventories, as well as 2008, 2010 and 2012. These years correspond to deadlines for the Clean Truck Program (CTP), which was put in place to improve air quality in the Alameda corridor. Results show that the health costs from particulate matter (PM) emitted by drayage trucks exceeded 440 million dollars in 2005. However, these costs decreased by 36%, 90%, and 96% after accounting for the requirements of the 2008, 2010, and 2012 CTP deadlines. These results quantify the magnitude of the social costs generated by drayage trucks in the Alameda corridor, suggest that these costs justified replacing drayage trucks operating there, and indicate that the Clean Truck Program likely exceeded its target.     

Eliminating barriers to nighttime activity participation: the case of on-demand transit in Belleville,Canada

Transportation - Demand-responsive technologies are rapidly changing the transportation landscape. The City of Belleville, Ontario has recently replaced its evening and nighttime fixed route bus...     

Design of a survey to assess prospects for consumer electric mobility in Canada: a retrospective appraisal

Transportation - This paper reviews the process that led to the development of a national survey instrument used to gather over 20,000 observations across Canada. This survey captured aspects of...     

A behavioral choice model of the use of car-sharing and ride-sourcing services

There are a number of disruptive mobility services that are increasingly finding their way into the marketplace. Two key examples of such services are car-sharing services and ride-sourcing services. In an effort to better understand the influence of various exogenous socio-economic and demographic variables on the frequency of use of ride-sourcing and car-sharing services, this paper presents a bivariate ordered probit model estimated on a survey data set derived from the 2014–2015 Puget Sound Regional Travel Study. Model estimation results show that users of these services tend to be young, well-educated, higher-income, working individuals residing in higher-density areas. There are significant interaction effects reflecting the influence of children and the built environment on disruptive mobility service usage. The model developed in this paper provides key insights into factors affecting market penetration of these services, and can be integrated in larger travel forecasting model systems to better predict the adoption and use of mobility-on-demand services.     

基于CML的级联失效下异质多层交通网络节点抵抗特性研究

为了有效刻画拟合实际的多层交通网络级联失效过程，识别多层网络中对整体韧性安全影响显著的对象，提升交通网络抵抗失效的能力，建立一种基于耦合映象格子（Coupled Map Lattice， CML）的级联失效模型。首先，将交通管控措施赋予交通网络节点额外的容纳能力引申为节点抵抗特性，通过为CML添加抵抗参数H，形成考虑抵抗特性的级联失效（HCML）模型，沿常值-拓扑关联-时变拓扑关联的路径深化H的表征方式，并在小世界（Small World， SW）网络上对比3类表征方式的优劣；其次，应用Space H方法建立异质3层公共交通网络，对比度值与介数2种时变拓扑指标关联的抵抗效果，探究不同交通层抵抗系数对网络失效的影响程度；最后，在6组不同的网络结构上进行HCML模型与传统模型的对比，讨论建网方法、网络规模等不同网络性质的差异对模型有效性的影响，并结合实际客运数据验证HCML模型优越性。研究结果表明：3类表征方式中时变拓扑关联可以兼顾其余2类的优点；同等条件中网络在介数关联的抵抗特性作用下失效增速更缓，模型识别得到的对网络整体失效影响更大交通方式符合客流量实际；HCML模型在多种不同类型的多层交通网络中均可以有效实施，相比于传统模型，HCML模型的最终失效比例平均下降了5.78%，与实际交通级联失效过程更加拟合。     

A latent variable representation of count data models to accommodate spatial and temporal dependence: Application to predicting crash frequency at intersections

This paper proposes a reformulation of count models as a special case of generalized ordered-response models in which a single latent continuous variable is partitioned into mutually exclusive intervals. Using this equivalent latent variable-based generalized ordered response framework for count data models, we are then able to gainfully and efficiently introduce temporal and spatial dependencies through the latent continuous variables. Our formulation also allows handling excess zeros in correlated count data, a phenomenon that is commonly found in practice. A composite marginal likelihood inference approach is used to estimate model parameters. The modeling framework is applied to predict crash frequency at urban intersections in Arlington, Texas. The sample is drawn from the Texas Department of Transportation (TxDOT) crash incident files between 2003 and 2009, resulting in 1190 intersection-year observations. The results reveal the presence of intersection-specific time-invariant unobserved components influencing crash propensity and a spatial lag structure to characterize spatial dependence. Roadway configuration, approach roadway functional types, traffic control type, total daily entering traffic volumes and the split of volumes between approaches are all important variables in determining crash frequency at intersections.     

Identification and quantification of link vulnerability in multi-level public transport networks: a passenger perspective

Robust public transport networks are important, since disruptions decrease the public transport accessibility of areas. Despite this importance, the full passenger impacts of public transport network vulnerability have not yet been considered in science and practice. We have developed a methodology to identify the most vulnerable links in the total, multi-level public transport network and to quantify the societal costs of link vulnerability for these identified links. Contrary to traditional single-level network approaches, we consider the integrated, total multi-level PT network in the identification and quantification of link vulnerability, including PT services on other network levels which remain available once a disturbance occurs. We also incorporate both exposure to large, non-recurrent disturbances and the impacts of these disturbances explicitly when identifying and quantifying link vulnerability. This results in complete and realistic insights into the negative accessibility impacts of disturbances. Our methodology is applied to a case study in the Netherlands, using a dataset containing 2.5 years of disturbance information. Our results show that especially crowded links of the light rail/metro network are vulnerable, due to the combination of relatively high disruption exposure and relatively high passenger flows. The proposed methodology allows quantification of robustness benefits of measures, in addition to the costs of these measures. Showing the value of robustness, our work can support and rationalize the decision-making process of public transport operators and authorities regarding the implementation of robustness measures.     

Oblique Wave Scattering Problems Involving Vertical Porous Membranes

Oblique surface waves incident on a fixed vertical porous membrane of various geometric configurations is analyzed here. The mixed boundary value problem is mod...     

On Control Laws for Vehicle Suspensions Accounting for Input Correlations

Input correlations involving time delays are common in active vehicle suspension system problems. One approach to control law derivation fur such systems is to restrict attention to slate feedback laws in the interests of practicality and it is then of interest to determine the law which is, in some sense, the best. Under assumptions which are common in this area. relating to input, system and cost Function forms, a new derivation of the expression for the cost, accounting for time delays, is given. The use of the expression in numerical procedures for determining effective control gains is discussed and an example for a half car planar vehicle model is described. By comparing results with existing ones which are truly optimal, an estimate is made of the loss of performance which results from the restriction of the control law form in this case. Some generalisation of the results is attempted and they are placed in a contemporary context at the conclusion.