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A virtual world provides a completely controlled and safe testing environment for the development and testing of current and future automated driving systems. In order to provide conditions close to reality, the input data for the automated driving system generated by sensors for environmental perception have to match closely between virtual and real world. The data gathered by perception sensors...
Projects in Mining and Metals are costly, huge - and unique by their nature. Similar plants or expansions differ significantly from previous ones due to advancements in technology, to different geographical location, climate, local regulations and hosting social/cultural environment. In all phases of the works (design, construction, early operation), the Project could benefit from the model based...
This paper presents a positioning method through rasterization of MR (Measurement Report) data. MR data consists of numerous wireless information except longitude/latitude data. MR raster positioning method is used to calculate the relevant longitude/latitude information of MR data and group them into corresponding clusters. compared to conventional drive test and call quality test method, MR raster...
Real time traffic flow forecasting is a necessary requirement for traffic management in order to be able to evaluate the effects of different available strategies or policies. This paper focuses on short-term traffic flow forecasting by taking into consideration both spatial (road links) and temporal (lag or past traffic flow values) information. We propose a Layered Ensemble Model (LEM) which combines...
Crowd simulation technologies and systems can show and tell a lot of insights on massive crowds' movement behavior. Benefiting from such characteristics, they have found themselves useful in many application fields. On the other hand, a typical educational institution, such as university, has a large body of student population, whose course schedules dominate their daily movement patterns. How to...
The smart phones and their applications add the richness of the VANET applications and increase the requirements on data dissemination support of the networks. This paper focuses on the link reliability model for data dissemination in urban VANETs. First, we extend the analytic model on 1-dimension road to the roads with orthogonal crossings. Then, we verify the link reliability model for the irregularly...
Fatal accidents occur frequently on low-volume rural roads, and the accident rates are up to 4 times higher at curves. It is thus of paramount importance to perform road inventory of rural roads to develop safety plans. However, most states in U.S. face a challenge to maintain a database for low-volume rural roads due to limited funds for road inventory. In this paper, we propose to significantly...
This contribution illustrates the benefit of incorporating real-time environmental data into highway traffic information systems and describes the modelling and integration of weather conditions into a complex microscopic traffic simulation. Using stationary measured weather data as an example, the achieved results show the potential extended Floating Car Data (xFCD) - submitted to the traffic information...
In recent years, new IT solutions and services have been appeared. One of the challenging topics in this category is big data. Although there have been tremendous researches in this area, emergence of all characteristics and potential of big data are still in its early stages. Success in big data development requires implementation of strong infrastructure which effectively depends on a multidimensional...
The lack of the historical data of new rail line makes the passenger flow distribution prediction be a challenge. Traditional methods always use simple factors, which can not reflect the complexity of OD distribution. This paper proposes a novel passenger flow distribution prediction method based on multi-factor model. This method obtains quantitative impact factors of OD distribution by analyzing...
Short-term traffic forecasting has been a hot research area in transportation research for more than sixty years. In recent years, more and more spatio-temporal models for short-term traffic forecasting were put forward with the consideration of spatial-temporal characteristic of traffic. This paper reviews the spatio-temporal models on short-term traffic flow forecasting and points out that the novel...
The link traffic time estimation for urban traffic is an important part of the route guidance system, it is a necessary condition to realize the multiple functions of intelligent transportation, which has important effect on traffic planning, traffic management and traffic control. From the perspective of the research content, this paper analyzes the studies of link travel time estimation of urban...
With the rapid development of vehicular, communication and sensing technologies, intelligent transportation system(ITS) and vehicular network are widely used to improve the driving experience in the city. A key procedure of many applications in vehicular network is data gathering, a universal process to collect sensed data from sparse-distributed vehicles for further operations to provide services...
Traffic sign detection plays an important role in driving assistance systems and traffic safety. But the existing detection methods are usually limited to a predefined set of traffic signs. Therefore we propose a traffic sign detection algorithm based on deep Convolutional Neural Network (CNN) using Region Proposal Network(RPN) to detect all Chinese traffic sign. Firstly, a Chinese traffic sign dataset...
For the purpose of filtering road spectrum this paper proposed an adaptive Kalman filtering (AKF) algorithm based on accurate autoregressive (AR) model. The proposed AKF can overcome the disadvantages such as complicated computation process and poor real-time performance when applying normal AKF. The algorithm can implement AKF by adjusting gain matrix Kk on the base of innovation. The process of...
With the urbanization of modern cities, traffic congestion has become an inevitable challenge to authorities. A large volume of road traffic demands more space than the available road capacity. To ease the situation, researches have involved in addressing this issue. As a result, Intelligent Transportation System (ITS) as a promising paradigm has emerged. To alleviate traffic congestion, theories...
Max-flow has been adopted for semi-supervised data modelling, yet existing algorithms were derived only for the learning from static data. This paper proposes an online max-flow algorithm for the semi-supervised learning from data streams. Consider a graph learned from labelled and unlabelled data, and the graph being updated dynamically for accommodating online data adding and retiring. In learning...
This paper proposed a method to build knowledge from one and a half years of UK traffic data sets. The method used is the Fast Incremental Model Trees - Drift Detection (FIMT-DD) with an improvement on the perceptron rule. In order to predict a traditional data set, we first analyze the model. After we have analyzed the model, we then average it from different arrangements of the datasets. In a stream...
Intelligent Transportation Systems (ITS) plays a significant role in the traffic management, i.e. traffic jam prediction, route guidance. Due to the hardware failure or data transformation failure, some traffic observation data may be occasionally missed, which seriously affect intelligent transportation information service. So, the completion of traffic observation data has now become an issue that...
Trajectory data contain more spatial, temporal information. So publishing such trajectory data to the public or a third party for data mining, analysis could cause more serious privacy issues. In this work, we demonstrate that the presence of road network can cause serious damage to the identity privacy of individuals. Motivated attackers can utilize the constraints information of road network to...
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