Life cycle cost of conventional,battery electric,and fuel cell electric vehicles considering traffic and environmental policies in China

Electric vehicles (EVs) are considered a promising alternative to conventional vehicles (CVs) to alleviate the oil crisis and reduce urban air pollution and carbon emissions. Consumers usually focus on the tangible cost when choosing an EV or CV but overlook the time cost for restricting purchase or driving and the environmental cost from gas emissions, falling to have a comprehensive understanding of the economic competitiveness of CVs and EVs. In this study, a life cycle cost model for vehicles is conducted to express traffic and environmental policies in monetary terms, which are called intangible cost and external cost, respectively. Battery electric vehicles (BEVs), fuel cell electric vehicles (FCEVs), and CVs are compared in four first-tier, four new first-tier, and 4 s-tier and below cities in China. The comparison shows that BEVs and FCEVs in most cities are incomparable with CVs in terms of tangible cost. However, the prominent traffic and environmental policies in first-tier cities, especially in Beijing and Shanghai, greatly increase the intangible and external costs of CVs, making consumers more inclined to purchase BEVs and FCEVs. The main policy benefits of BEVs and FCEVs come from three aspects: government subsidies, purchase and driving restrictions, and environmental taxes. With the predictable reduction in government subsidies, traffic and environmental policies present important factors influencing the competitiveness of BEVs and FCEVs. In first-tier cities, BEVs and FCEVs already have a competitive foundation for large-scale promotion. In new first-tier and second-tier and below cities, stricter traffic and environmental policies need to be formulated to offset the negative impact of the reduction in government subsidies on the competitiveness of BEVs and FCEVs. Additionally, a sensitivity analysis reveals that increasing the mileage and reducing fuel prices can significantly improve the competitiveness of BEVs and FCEVs, respectively.     

Expert evaluation of traffic signs: conventional vs. alternative designs

Traffic sign comprehension is significantly affected by their compliance with ergonomics design principles. Despite the UN Convention, designs vary among countries. The goal of this study was to establish theoretical and methodological bases for evaluating the design of conventional and alternative signs. Thirty-one conventional signs and 1–3 alternatives for each conventional sign were evaluated for their compliance with three ergonomics guidelines for sign design: physical and conceptual compatibility, familiarity and standardisation. Twenty-seven human factors and ergonomics experts from 10 countries evaluated the signs relative to their compliance with the guidelines. Analysis of variance across alternatives revealed that for 19 of the 31 signs, an alternative design received a significantly higher rating in its ergonomics design than the conventional sign with the same meaning. We also found a very high correlation between the experts’ ratings and comprehension from previous studies. In conclusion, many countries use signs for which better alternative designs exist, and therefore UN Convention signs should be re-examined, and ergonomics experts evaluation can serve as a good surrogate for road users’ comprehension surveys.

Practitioner summary: This study presents theoretical and methodological bases for evaluating the design of UN Conventional and alternative traffic signs. Human factors and ergonomics experts evaluated 31 conventional and 68 alternative road signs, based on ergonomics principles for sign design. Results indicated the need to re-examine poorly designed UN Convention signs.     

Accuracy of wind energy forecasts in Great Britain and prospects for improvement

The metric representing the wind energy forecast error, when reported as a percent, is calculated quite differently than the error metrics for electricity transmission, electricity load, or in other industries such as manufacturing when they are also reported as a percent. The resulting calculated metric is quite different from what would be reported if the method utilized elsewhere was employed. This paper examines the possible forecast assessment and operational challenges associated with this finding. Concerning the prospects for improvement, the errors reported in MW of energy have a systematic component. With this insight, we developed a model to improve accuracy.     

Local weather prediction system for a heating plant using cognitive approaches

Present-day requirements emphasize the need of saving energy. It relates mainly to industrial companies, where the minimization of energy consumption is one of their most important tasks they face. In our paper, we deal with the design of the so-called weather prediction system (WPS) for the needs of a heating plant. The primary task of such a WPS is timely predicting expected heat consumption to prepare the technology characterized by long delays in advance. Heat prediction depends primarily on weather so the crucial part of WPS is the weather, especially temperature, prediction. However, a prediction system needs a variety of further data, too. Therefore, WPS must be regarded as a complex system, including data collection, its processing, own prediction and eventual decision support. This paper gives the overview about existing data processing systems and prediction methods and then it describes a concrete design of a WPS with distributed data measuring points (stations), which are processed using a structure of neural networks based on multilayer perceptrons (MLP) with a combination of fuzzy logic. Based on real experiments we show that also such simple means as MLPs are able to solve complex problems. The paper contains a basic methodology for designing similar WPS, too.     

Can child-pedestrians’ hazard perception skills be enhanced?

ObjectiveTraffic collisions yield a substantial rate of morbidity and injury among child-pedestrians. We explored the formation of an innovative hazard perception training intervention – Child-pedestrians Anticipate and Act Hazard Perception Training (CA²HPT). Training was based upon enhancing participants’ ability to anticipate potential hazards by exposing them to an array of traffic scenes viewed from different angles.MethodTwenty-four 7–9-year-olds have participated. Trainees underwent a 40-min intervention of observing typical residential traffic scenarios in a simulated dome projection environment while engaging in a hazard detection task. Trainees were encouraged to note differences between the scenarios presented to them from separate angles (a pedestrian's point-of-view and a higher perspective angle). Next, trainees and control group members were required to perform crossing decision tasks.ResultsTrainees were found to be more aware of potential hazards related to restricted field of view relative to control.ConclusionsChild pedestrians are responsive to training and actively detecting materialized hazards may enrich child-pedestrians’ ability to cross roads.     

Profiling drunk driving recidivists in Denmark

Drunk drivers are a menace to themselves and to other road users, as drunk driving significantly increases the risk of involvement in road accidents and the probability of severe or fatal injuries. Although injuries and fatalities related to road accidents have decreased in recent decades, the prevalence of drunk driving among drivers killed in road accidents has remained stable, at around 25% or more during the past 10 years. Understanding drunk driving, and in particular, recidivism, is essential for designing effective countermeasures, and accordingly, the present study aims at identifying the differences between non-drunk drivers, drunk driving non-recidivists and drunk driving recidivists with respect to their demographic and socio-economic characteristics, road accident involvement and other traffic and non-traffic-related law violations. This study is based on register-data from Statistics Denmark and includes information from 2008 to 2012 for the entire population, aged 18 or older, of Denmark. The results from univariate and multivariate statistical analyses reveal a five year prevalence of 17% for drunk driving recidivism, and a significant relation between recidivism and the drunk drivers’ gender, age, income, education, receipt of an early retirement pension, household type, and residential area. Moreover, recidivists are found to have a higher involvement in alcohol-related road accidents, as well as other traffic and, in particular, non-traffic-related offences. These findings indicate that drunk driving recidivism is more likely to occur among persons who are in situations of socio-economic disadvantage and marginalisation. Thus, to increase their effectiveness, preventive measures aiming to reduce drunk driving should also address issues related to the general life situations of the drunk driving recidivists that contribute to an increased risk of drunk driving recidivism.     

A study on the monitoring model development for quality measurement of internet traffic

The recent trend of integration among new network services such as the long-term evolution (LTE) based on internet protocol (IP) needs reputable analyses and prediction information on the internet traffic. The IP along with increased internet traffics due to expanding new service platforms such as smartphones will reflect policies such as network QoS according to new services. The establishment of monitoring methods and analysis plans is thus required for the development of internet traffics that will analyze their status and predict their future. The paper with the speed of Internet traffic model is developed for monitoring the state of the experiment and verified. The problem is that the proposed service Internet service provider (ISP) to resolve the conflict between the occurrences can be considerably Internet traffic and that the state of data may be helpful in understanding. The paper advancement policy to reflect the network traffic volume of Internet services and users irradiation with increased traffic due to the development and management of the analysis was carried out experimental measurements.     

A privacy mechanism for mobile-based urban traffic monitoring

In mobile-based traffic monitoring applications, each user provides real-time updates on their location and speed while driving. This data is collected by a centralized server and aggregated to provide participants with current traffic conditions. Successful participation in traffic monitoring applications utilizing participatory sensing depends on two factors: the information utility of the estimated traffic condition, and the amount of private information (position and speed) each participant reveals to the server. We assume each user prefers to reveal as little private information as possible, but if everyone withholds information, the quality of traffic estimation will deteriorate. In this paper, we model these opposing requirements by considering each user to have a utility function that combines the benefit of high quality traffic estimates and the cost of privacy loss. Using a novel Markovian model, we mathematically derive a policy that takes into account the mean, variance and correlation of traffic on a given stretch of road and yields the optimal granularity of information revelation to maximize user utility. We validate the effectiveness of this policy through real-world empirical traces collected during the Mobile Century experiment in Northern California. The validation shows that the derived policy yields utilities that are very close to what could be obtained by an oracle scheme with full knowledge of the ground truth.     

Quantitative analysis of semiconductor supply chain contracts with order flexibility under demand uncertainty: A case study

The evidence base for the configuration of rolling horizon flexibility (RHF) contracts (a type of quantity flexibility contract) used in the semiconductor industry to coordinate production and demand remains meagre, more art than science. Informed by the characteristics of actual clauses and demand behaviors drawn from a company’s experience, a discrete-event simulation model is developed to represent the company’s supply chain. It comprises of three parties: a customer, a supplier (semiconductor manufacturer), and a capacity provider. Through analysis of customer forecasted demand the paper characterizes forecast demand as being under, over or unbiased. Models of these forecasted demands drives both long and short term planning. In long term planning, which is given twelve months before an order is delivered, capacity at the capacity provider is booked. Short term planning is also driven by this forecast which, within a binding period, is governed by an RHF contract. Results from the model report inventory levels, and delivery compliance, namely Delivery Performance (DP) and Delivery Reliability (DR), measures widely used in this sector. It is concluded from this work that on the balance of performance measures RHF contracts with asymmetrical flexibility bounds are substantially better than those with symmetrical boundaries, and that this conclusion is robust with regard to both over-planning and under-planning behaviors. This robustness is a critical attribute with respect to the endemic medium-term vacillation between both states experienced in practice in this sector.