The invention relates to a method for traffic prognosis of vehicles, each with a navigation system for route calculation, wherein the vehicles are each equipped with a tracking unit, a digital road map and a communication unit communicating with a central communication unit. It is understood that all the models provided consistent and useful results when the developed models were compared with the statistical results. ScienceDirect ® is a registered trademark of Elsevier B.V.Copyright © 2014 Elsevier Ltd. All rights reserved.ScienceDirect ® is a registered trademark of Elsevier B.V. Moreover, existing research attention is mainly paid to find the nearest taxi, whilst in reality the nearest taxi may not be the optimal answer. Arbitrary kinds of roads and crossings are modeled as combinations of only a few basic elements. Request PDF | Forecasting traffic volume with space-time ARIMA model | The paper proposes a space–time autoregressive integrated moving average (STARIMA) model to predict the traffic volume … Seasonal autoregressive integrated moving average (SARIMA), artificial bee colony (ABC) and differential evolution (DE) algorithms are the techniques used in the optimization of models, which have been developed by using observation data for the D-200 highway in Turkey. © 2008-2020 ResearchGate GmbH. However, if forecasting duration is too long, the predicting accuracy may decline and may cause unnecessary traffic chaos.

Traffic Volume Forecasting Methods for Rural State Highways SuNIL K. SAHA AND JoN D. FRICKER This study builds on previous efforts found in the field of rural traffic forecasting. Towards this purpose, the study develops an evaluation model of road transport infrastructure, the TIM, which will help decision making in situations of choice between different alternatives of road projects. The feasibility of this approach is demonstrated through a time-lag recurrent network (TLRN) which was developed for predicting speed data up to 15 minutes into the future. Computational experiments show that the proposed model is both effective and practical.We use cookies to help provide and enhance our service and tailor content and ads.

Any author submitting a COVID-19 paper should notify us at Criterion indexes in experiment of different K value.Criterion indexes in experiment of different lag duration.Criterion indexes in experiment of different forecasting duration.Criterion indexes in experiment of normal algorithms and asymmetric algorithms.MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044, ChinaChina Railway Container Transport Co., Ltd Beijing Branch, Beijing 100055, ChinaSubject profile: the traffic profile of one specific day to be forecasted. Traffic flows for example are needed to properly simulate the influence of slip roads and motorway exits. To take into account the lack of information in the cluster assignment for the new predicted values, a weighted average fusion based on a similarity measurement is proposed to combine the predictions of each model. Its growth is linked to the average GDP growth expected for the country, industrial and agricultural production, and population size ... For instance, Chen and Grant-Muller (2001) propose and discuss the potential application of neural networks algorithm in the short-term traffic flow forecasting of motorway.

However, it is found that traffic flows from adjacent intersections show a similar trend. Overall, this research investigates the Revenue Management from the point of view of LTL carriers operating in a highly dynamic environment like Physical Internet. The results of the research shows that artificial intelligence methods can be successfully used in traffic management systems.After the generalized deployment of advanced traveler information systems, there exists an increasing concern about their profitability. Experiments show that DeepTrend can noticeably boost the prediction performance compared with some traditional prediction models and LSTM with detrending based methods.This paper addresses the problem of dynamic travel time (DTT) forecasting within highway traffic networks using speed measurements. With simulation scenario analyses and a genetic algorithm, the training system presented in this paper can help decision makers determine close-to-optimal layouts for initial AFV filling stations. Some techniques rely on aggregated historical information (e.g. With different layouts for these initial refueling stations, potential AFV adopters will have different concerns regarding the availability of refueling facilities, which will result in different starting points for the diffusion of AFVs. In this paper, we compare three different approaches in traffic forecasting, study the input data and output data for these approaches, as well as some general insights, and also propose BP neural network to estimate accurate traffic flow for a roadway section.

However, asymmetric cost is meaningful in traffic management. I make no apology for this; I felt it was important to cover as much of the contemporary work as was possible.The paper surveys both the application areas found to be fruitful and the range of neural network paradigms which have been used. All rights reserved.Due to its paramount relevance in transport planning and logistics, road traffic forecasting has been a subject of active research within the engineering community for more than 40 years. best prediction. Moreover, experimental results obtained from fuel delivery trucks, along the whole year of 2013 in Brazil, indicate that most of the observations can be predicted using this model within an acceptable error tolerance.Freight transportation in Brazil is heavily based on the road mode bringing heavy dependence of this mode to the country and some consequences such as high operating costs and high air emissions. An SUA approach is proposed to reduce the processing time for forecasting the conditions of all road sections in real-time, which is typically considerable and complex. We derive bounds for the error due to dimension reduction. To evaluate the effect of selecting a best matching initial matrix on traffic pattern estimation and prediction quality, a comparative application of different initial matrix choices is conducted using an on-line traffic estimation and prediction system (TrEPS).


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