考虑环境因素的公交车队管理研究

提出了一种公交车辆管理模型,可以在考虑环境因素以及资金、技术等限制条件下做出车辆购买、淘汰的决策.在满足污染物排放限定条件下达到成本投入最小.通过案例分析,结果表明该模型行之有效.     

Optimisation of lateral car dynamics taking into account parameter uncertainties

Simulation studies on an active all-wheel-steering car show that disturbance of vehicle parameters have high influence on lateral car dynamics. This motivates the need of robust design against such parameter uncertainties. A specific parametrisation is established combining deterministic, velocity-dependent steering control parameters with partly uncertain, velocity-independent vehicle parameters for simultaneous use in a numerical optimisation process. Model-based objectives are formulated and summarised in a multi-objective optimisation problem where especially the lateral steady-state behaviour is improved by an adaption strategy based on measurable uncertainties. The normally distributed uncertainties are generated by optimal Latin hypercube sampling and a response surface based strategy helps to cut down time consuming model evaluations which offers the possibility to use a genetic optimisation algorithm. Optimisation results are discussed in different criterion spaces and the achieved improvements confirm the validity of the proposed procedure.     

重型柴油车NOx排放远程监测准确性研究

文章通过采用不同浓度的反应剂来模拟重型国六柴油车正常状态、临界超标及SCR性能失效状态下的实际道路NOx排放,从而研究远程排放管理平台对超标车型识别的效果。试验结果表明,NOx临界超标与SCR完全失效状态下,远程排放管理平台采集的国六整车实际道路NOx排放与PEMS设备结果基本一致,而正常状态下,尿素过量喷射导致的NH3泄露会对车载NOx传感器精度造成影响,进而导致远程排放管理平台采集的国六整车NOx排放与PEMS设备存在偏差。     

An evaluation framework for traffic calming measures in residential areas

The paper evaluates the effectiveness of various traffic calming measures from the perspectives of traffic performance and safety, and environmental and public health impacts. The proposed framework was applied to four calming measures – two types of speed humps, speed tables, and chicanes – to demonstrate its usefulness and applicability. A field experiment using probe vehicles equipped with global positioning system devices was conducted to obtain vehicle trajectory data for use in more realistic simulations. In addition, a recently developed vehicle emissions model was used for more accurate evaluation of environmental and public health impacts. The results show that chicane is better than the other types of traffic calming measures considered, except in terms of vehicle emissions.     

Port e-Transformation,customer satisfaction and competitiveness

ABSTRACT

e-Transformation in container ports means port organization-wide innovative transformation encompassing internal and external value chains based on information and communication technology. There is a considerable theoretical literature on the impact of e-Transformation on business performance, but there is very little empirical study on its effectiveness in ports. The objective of this paper is to empirically investigate how e-Transformation in container port management can influence customer satisfaction and port competitiveness. The findings reveal that e-Transformation in container ports can affect customer satisfaction and port competitiveness through e-Workplace, customer relationship management and security, implying that container ports should make every effort to focus on e-transformation in these critical areas. Due to limited empirical studies in this area, the findings have provided an empirical support for the importance of e-Transformation in container terminal management and shed more light on how e-Transformation can affect customer satisfaction and port competitiveness.     

Strategies to achieve deep reductions in metropolitan transportation GHG emissions: the case of Philadelphia

ABSTRACT

This paper investigates strategies that could achieve an 80% reduction in transportation emissions from current levels by 2050 in the City of Philadelphia. The baseline daily lifecycle emissions generated by road transportation in the Greater Philadelphia Region in 2012 were quantified using trip information from the 2012 Household Travel Survey (HTS). Emissions were projected to the year 2050 accounting for population growth and trends in vehicle technology for both the Greater Philadelphia Region and the City of Philadelphia. The impacts of vehicle technology and shifts in travel modes on greenhouse gas (GHG) emissions in 2050 were quantified using a scenario approach. The analysis of 12 different scenarios suggests that 80% reduction in emissions is technically feasible through a combination of active transportation, cleaner fuels for public transit vehicles, and a significant market penetration of battery-electric vehicles. The additional electricity demand associated with greater use of electric vehicles could amount to 10.8 TWh/year. The use of plug-in hybrid electric vehicles (PHEV) shows promising results due to high reductions in GHG emissions at a potentially manageable cost.     

Modeling the relationships among urban passenger travel carbon dioxide emissions,transportation demand and supply,population density,and proxy policy variables

To support the development of policies that reduce greenhouse gas (GHG) emissions by encouraging reduced travel and increased use of efficient transportation modes, it is necessary to better understand the explanatory effects that transportation, population density, and policy variables have on passenger travel related CO₂ emissions. This study presents the development of a model of CO₂ emissions per capita as a function of various explanatory variables using data on 146 urbanized areas in the United States. The model takes into account selectivity bias resulting from the fact that adopting policies aimed at reducing emissions in an urbanized area may be partly driven by the presence of environmental concerns in that area. The results indicate that population density, transit share, freeway lane-miles per capita, private vehicle occupancy, and average travel time have a statistically significant explanatory effect on passenger travel related CO₂ emissions. In addition, the presence of automobile emissions inspection programs, which serves as a proxy indicator of other policies addressing environmental concerns and which could influence travelers in making environmentally favorable travel choices, markedly changes the manner in which transportation variables explain CO₂ emission levels.     

Impacts of trade related sustainability strategies on freight transportation: Modelling framework and application for France

The circular and functional economies are being presented in the literature as potential strategies for future sustainable societies. In terms of the consequences for supply chains, they will promote a much more dispersed and diversified, local and network based usage of goods than the current economy, which is comparatively linear, concentrated, long distance oriented and scale economy based. A gap in the literature is the assessment of the effects of these systems on freight transport flows. In our paper, we present a first attempt at estimating this impact using freight transport scenario building and quantitative modelling. In order to translate the main parameters that characterize these systems into factors determining freight transportation volumes, we develop a framework based on a typology of goods categories describing functional and spatial proximity between producers and consumers. In order to simulate changes in the economy, we develop scenarios for the shifting of goods from one category to another and, additionally, include internalization policies that should guide their realization. We calculate the impacts on freight flows using a new interregional transport model for France that includes distribution chains and produces estimates of external costs of transport. Our results show that circular and functional economies could lead to a 2–5% reduction of air pollutant emissions and up to a 14–26% reduction if combined with the internalization of external costs. The scenario with ongoing mass production for differentiated demand is found to lead to a 5% increase of environmental impacts compared to the baseline.     

Commuters’ behavior towards upgraded bus services in Greater Beirut: Implications for greenhouse gas emissions,social welfare and transport policy

Climate change is one of the most critical environmental challenges faced in the world today. The transportation sector alone contributes to 22% of carbon emissions, of which 80% are contributed by road transportation. In this paper we investigate the potential private car greenhouse gas (GHG) emissions reduction and social welfare gains resulting from upgrading the bus service in the Greater Beirut Area. To this end, a stated preference (SP) survey on mode switching from private car to bus was conducted in this area and analyzed by means of a mixed logit model. We then used the model outputs to simulate aggregate switching behavior in the study area and the attendant welfare and environmental gains and private car GHG emissions reductions under various alternative scenarios of bus service upgrade. We recommend a bundle of realistic bus service improvements in the short term that will result in a reasonable shift to buses and measurable reduction in private car emissions. We argue that such improvements will need to be comprehensive in scope and include both improvements in bus level of service attributes (access/egress time, headway, in-vehicle travel time, and number of transfers) and the provision of amenities, including air-conditioning and Wi-Fi. Moreover, such a service needs to be cheaply priced to achieve reasonably high levels of switching behavior. With a comprehensively overhauled bus service, one would expect that bus ridership would increase for commuting purposes at first, and once the habit for it is formed, for travel purposes other than commuting, hence dramatically broadening the scope of private car GHG emissions reduction. This said, this study demonstrates the limits of focused sectorial policies in targeting and reducing private car GHG emissions, and highlights the need for combining behavioral interventions with other measures, most notably technological innovations, in order for the contribution of this sector to GHG emissions mitigation to be sizable.     

A mixed logit model for predicting exit choice during building evacuations

Knowledge on human behaviour in emergency is crucial to increase the safety of buildings and transportation systems. Decision making during evacuations implies different choices, of which one of the most important concerns is the escape route. The choice of a route may involve local decisions on alternative exits from an enclosed environment. This study investigates the effect of environmental (presence of smoke, emergency lighting and distance of exit) and social factors (interaction with evacuees close to the exits and with those near the decision-maker) on local exit choice. This goal is pursued using an online stated preference survey carried out making use of non-immersive virtual reality. A sample of 1503 participants is obtained and a mixed logit model is calibrated using these data. The model shows that the presence of smoke, emergency lighting, distance of exit, number of evacuees near the exits and the decision-maker and flow of evacuees through the exits significantly affect local exit choice. Moreover, the model indicates that decision making is affected by a high degree of behavioural uncertainty. Our findings support the improvement of evacuation models and the accuracy of their results, which can assist in designing and managing building and transportation systems. The main aim of this study is to enrich the understanding of how local exit choices are made and how behavioural uncertainty affects these choices.