Abstract

With the increase in electric mobility, public and private charge facilities will be required to provide solutions adjusted to the actual needs and requirements. A new methodology for dimensioning charge stations for electric vehicles (EVs) is presented in this paper. Such proposal is based on the Markov chains, and uses as output rates, the capabilities of the charge station in providing energy from the sun through photovoltaic generation, stored energy in local batteries and also as a back-up the power grid. A numerical result is also presented for a better understanding of the process. Document type: Conference object

Abstract

The Laboratory of Aviation Safety and Security at CTU in Prague has recently started a project aimed at runway protection zones. The probability of exceeding by a certain distance from the runway in common incident/accident scenarios (take-off/landing overrun/veer-off, landing undershoot) is being identified relative to the runway for any airport. As a result, the size and position of safety areas around runways are defined for the chosen probability. The basis for probability calculation is a probabilistic model using statistics from more than 1400 real-world cases where jet airplanes have been involved over the last few decades. Other scientific studies have contributed to understanding the issue and supported the model’s application to different conditions. Document type: Article

Abstract

We present an approach for validation of advanced driver assistance systems, based on randomized algorithms. The new method consists of an iterative randomized simulation using adaptive importance sampling. The randomized algorithm is more efficient than conventional simulation techniques. The importance sampling pdf is estimated by a kernel density estimate, based on the results from the previous iteration. The concept is illustrated with a simple adaptive cruise control problem.

Abstract

SUMMARY In this paper we consider a specific Air Traffic Management problem, where multiple aircraft in as pecif ic region are required to reach ad if ferent target zone in minimum expected time, while maintaining safe separation. The problem is complicated by the presence of random wind disturbances. We propose a realistic policy to automatically generate optimal and safe manoeuvres for each aircraft. The parameters of the optimal policy are computed using a Sequential Monte Carlo approach. Copyright c � 2010 John Wiley & Sons, Ltd.

Abstract

Weather conditions are widely acknowledged to contribute to the occurrence of congestion on motorway traffic by influencing both traffic supply and traffic demand. To the best of our knowledge, this is the first paper that explicitly integrates supply and demand effects in predicting the influence of adverse weather conditions on the probability of occurrence of congestion. Traffic demand is examined by conducting a stated adaptation experiment, in which changes in travel choices are observed under adverse weather scenarios. Based on these choices, a Panel Mixed Logit model is estimated. Supply effects are taken into account by examining the influence of precipitation on motorway capacity. Based on the Product Limit Method, capacity distribution functions are estimated for dry weather, light rain and heavy rain. With the developed model to integrate the supply and demand effects breakdown probabilities can be calculated for any given traffic demand and capacity. The results show that rainfall leads to a significant increase in the probability of traffic breakdown at bottleneck locations. Interestingly the probability of a breakdown at these bottleneck locations is predicted to be slightly higher in light rain (98.7%) than in heavy rain (95.7%) conditions, which is the result of the higher traffic demand in light rain conditions. Based on the results presented in this paper, it can be recommended to always incorporate both supply and demand effects in the predictions of motorway breakdown probabilities due to adverse weather conditions to improve the validity of the predictions. © 2015 Editorial Board EJTIR. All rights reserved.

Abstract

This article reviews known approaches to determining the uncertainty of predictive models: probabilistic analytical, probabilistic simulation and fuzzy. The main elements determining the specificity of a given approach are shown. The advantages and disadvantages are compared. Finally, the application guidelines are listed.