The transportation system is one of the most important parts of the country's economy. At the same time, the growth in road traffic has a significant negative impact on the economic performance of the industry. One of the ways to increase the efficiency of using the transportation infrastructure is to manage traffic flows, incl. by controlling traffic signals at signalized intersections. One of the trends in the development of intelligent transportation systems is the creation of vehicular ad hoc networks that allow the exchange of information between vehicles and infrastructure, as well as the development of autonomous vehicles. As a result, it becomes possible to formulate the problem of cooperative control of vehicle trajectories and traffic signals to increase the capacity of intersections and reduce fuel consumption and travel time. This paper presents a method for managing traffic flow at an intersection, which consists of the cooperative control of traffic signals and trajectories of connected/autonomous vehicles. The developed method combines an algorithm for the adaptive control of traffic signals based on a deterministic model for predicting the movement of vehicles and a two-stage algorithm for constructing the trajectory of vehicles. The objective optimization function used to construct the optimal trajectories takes into account fuel consumption, travel time on the road lane, and waiting time at the intersection. Experimental studies of the developed method were carried out in the microscopic traffic simulation package SUMO using three simulation scenarios, including two synthetic scenarios and a scenario in a real urban environment. The results of experimental studies confirm the effectiveness of the developed method in terms of fuel consumption, travel time, and waiting time in comparison with the adaptive traffic signal control algorithm.
The connectivity of autonomous vehicles induces new attack surfaces and thus the demand for sophisticated cybersecurity management. Thus, it is important to ensure that in-vehicle network monitoring includes the ability to accurately detect intrusive behavior and analyze cyberattacks from vehicle data and vehicle logs in a privacy-friendly manner. For this purpose, we describe and evaluate a method that utilizes characteristic functions and compare it with an approach based on artificial neural networks. Visual analysis of the respective event streams complements the evaluation. Although the characteristic functions method is an order of magnitude faster, the accuracy of the results obtained is at least comparable to those obtained with the artificial neural network. Thus, this method is an interesting option for implementation in in-vehicle embedded systems. An important aspect for the usage of the analysis methods within a cybersecurity framework is the explainability of the detection results.
The paper proposes a solution to the problem of selecting the bandwidth capabilities of digital communication channels of a transport communication network taking into account the imbalance of data traffic by priorities. The algorithm for selecting bandwidth guarantees the minimum costs associated with renting digital communication channels with optimal bandwidth, provided that the requirements for quality of service of protocol data blocks of the first, second, and k-th priority in an unbalanced in terms of priorities transport communication network are met. At the first stage of solving the problem, using the method of Lagrange multipliers, an algorithm for selecting the capacities of digital communication channels for a balanced in terms of priorities transport network was developed. High performance of this algorithm was ensured by applying algebraic operations on matrices (addition, multiplication, etc.). At the second stage of solving the problem, using the generalized Lagrange multipliers method, we compared the conditional extrema of the cost function for renting digital communication channels for single active quality of service requirements for protocol data blocks, for all possible pairs of active quality of service requirements for protocol data blocks, for all possible triples of active requirements for the quality of service of protocol data units, and so on up to the case when all the requirements for quality of service maintenance of protocol data units are active simultaniously. At the third stage of solving the problem, an example of selecting the bandwidth capabilities of digital communication channels of the unbalanced by priorities transport network consisting of eight routers serving protocol data blocks of three priorities was considered. At the fourth stage of the solution of the problem of the choice of carrying capacities the estimation of efficiency of the developed algorithm by a method of simulation modeling was carried out. To this end, in the environment of the network simulator OMNet ++, the unbalanced in terms of priority transport communication network consisting of eight routers connected by twelve digital communication channels with optimal bandwidth was investigated.
Personal mobility devises become more and more popular last years. Gyroscooters, two wheeled self-balancing vehicles, wheelchair, bikes, and scooters help people to solve the first and last mile problems in big cities. To help people with navigation and to increase their safety the intelligent rider assistant systems can be utilized that are used the rider personal smartphone to form the context and provide the rider with the recommendations. We understand the context as any information that characterize current situation. So, the context represents the model of current situation. We assume that rider mounts personal smartphone that allows it to track the rider face using the front-facing camera. Modern smartphones allow to track current situation using such sensors as: GPS / GLONASS, accelerometer, gyroscope, magnetometer, microphone, and video cameras. The proposed rider assistant system uses these sensors to capture the context information about the rider and the vehicle and generates context-oriented recommendations. The proposed system is aimed at dangerous situation detection for the rider, we are considering two dangerous situations: drowsiness and distraction. Using the computer vision methods, we determine parameters of the rider face (eyes, nose, mouth, head pith and rotation angles) and based on analysis of this parameters detect the dangerous situations. The paper presents a comprehensive related work analysis in the topic of intelligent driver assistant systems and recommendation generation, an approach to dangerous situation detection and recommendation generation is proposed, and evaluation of the distraction dangerous state determination for personal mobility device riders.
A frequent problem of traffic flow characteristics acquisition is data loss, which leads to uneven time series analysis. An effective approach to uneven data analysis is the spectral analysis, which requires obtaining process with a constant sampling interval, for example, by restoring missing data, which leads to the appearance of dating error. Thus, the main purpose of this study is to develop a method and software for wavelet analysis of traffic flow characteristics without restoring the missing data.
To analyze and interpret non-stationary uneven time series obtained from traffic monitoring systems, we propose the wavelet transformation method with adjustment of the sampling intervals, which results in a time-frequency domain with a constant sampling interval. Wavelet analysis is applied to the macroscopic traffic flow characteristics.
We developed the software for traffic flow wavelet analysis on the "ITSGIS" intelligent transport geo-information framework using the attribute-oriented approach.
Wavelet analysis of traffic flows characteristics using Morlet wavelets was accomplished for data analysis of the city of Aarhus, Denmark. Wavelet spectra and scalograms were constructed and analyzed, general dependencies in the frequency distribution of extremes, and differences in spectral power were revealed.
The developed software is being experimentally tested in solving practical problems of municipalities and road agencies in Russia.
The purpose of any rescue and other emergency operations is to save people and assist to sufferers, to localize accidents and eliminate the damage hindering rescue operations, as well as to create conditions for the subsequent recovery works. In the presence of factors that menace life and health of the people carrying out these works (rescuers, firefighters, etc.) there is an objective need for application of the automated robotic means of transportation of a sufferer. A lack of the corresponding methodological and program- algorithmic tools causes a need to model specified means. A model of a transportation position of the sufferer on the basis of Bayesian belief networks is presented in the paper.
The paper provides a discussion about the development of information system to increase citizens’ mobility. The system is also known as system for infomobility. The following questions are discussed in the paper: the system expediency, main system’s features main principles that is used for system development. Additionally, the comparison of existing services that provide infomobility is presented in the paper.
The paper discusses features of construction and operation of automated systems of railway transport. As main distinguishing factors, the great variety and diversity of such systems, their mutual co-relationships and links with public networks, and strong heterogeneity of internal user are highlighted. The architecture of a multi-level intelligent information security system that proposed to protect information in automated systems of railway transport is suggested and discussed. To store data about security in a multilevel intelligent system of protection it is proposed to use a hybrid ontology repository. Formal task statements for intelligent services of data analysis at the top level of the reviewed protection systems are offered. Analysis of these statements showed that development of intelligent services for correlation management, security analysis and attack modeling should be assigned to analysis tasks. Intelligent services for decision support and visual data analysis are among the synthesis tasks.
The paper encompasses a design conception for combined embedded device security to be applied within the development process of protection mechanisms for systems and services of complex security on rail transport. A model and technique proposed are intended for configuring embedded device security components developed taking into consideration expert knowledge in the embedded security field. The goal of the configuration process is to find a security configuration that meets all necessary security requirements and constraints of the device platform, satisfies set resource consumption criteria and does not contain known types of security component inconsistencies.
Hardware-software complex «RiskDetektor» (ISA of Russian Academy of Sciences) is described in the article. This Complex realizes in a mode of dialogue the computer—the user the basic procedures of maintenance of the transport safety, defined by directive documents. The ideology of a complex has been developed and published earlier and assumes that the control system of risks of infringement of transport safety is constructed on a basis of categori-zation of transport objects by an estimation of a possible damage at realization threats of terror-ist influence.
The increasing storage density of modern NAND flash memory chips, achieved both due to scaling down the cell size, and due to the increasing number of used cell states, leads to a decrease in data storage reliability, namely, error probability, endurance (number of P/E cycling) and retention time. Error correction codes are often used to improve the reliability of data storage in multilevel flash memory. The effectiveness of using error correction codes is largely determined by the model accuracy that exhibits the basic processes associated with writing and reading data. The paper describes the main sources of disturbances for a flash cell that affect the threshold voltage of the cell in NAND flash memory, and represents an explicit form of the threshold voltage distribution. As an approximation of the obtained threshold voltage distribution, a Normal-Laplace mixture model was shown to be a good fit in multilevel flash memories for a large number of rewriting cycles. For this model, a performance analysis of the concatenated coding scheme with an outer Reed-Solomon code and an inner multilevel code consisting of binary component codes is carried out. The performed analysis makes it possible to obtain tradeoffs between the error probability, storage density, and the number of P/E cycling. The resulting tradeoffs show that the considered concatenated coding schemes allow, due to a very slight decrease in the storage density, to increase the number of P/E cycling up to 2–2.5 times than their nominal endurance specification while maintaining the required value of the bit error probability.
An increase in the number of cars is higher than rates of transport infrastructure development, resulting in a reduction of cargo and passenger transportation efficiency in city conditions. Simulation of flow irregularity in time (peak hour) shows the key role of a car motion interval as a factor of overcoming accumulation at average speed reduction in conditions of highly loaded roads. To reduce the effective time of driver reaction, defining the least distance between cars, it is necessary to minimize the influence of human factors. Automation of the process (unmanned control) requires an effective exchange of navigation and route data between traffic participants. A summary of requirements for such an information exchange system defines the priority of the suggested communication and navigation system (CNS) on the base of radio broadcast communication. Its application gives an opportunity to rise simultaneously traffic safety and efficiency. An increase in neighbor driver action predictability leads to traffic safety ensuring. The exchange of data with traffic control centers (TCC) enables the centralization of motion regulation. A distributed network of transceiver stations forms a local positioning system based on trilateration principles. Algorithms of onboard positioning result verification and automatic resolution of communication conflicts ensure high reliability of CNS functioning. Refusal from point-to-point communication principles allows it to operate even in conditions of high car density up to several thousand per square kilometer. In cooperation with advanced technologies of traffic organization (formation of city highway grid and “total green wave” mode), CNS and TCC are capable of rising the average speed in city conditions higher than 45 km/hour. The aggregate economy of expense on last mile transportation because of the suggested innovations is to be at the level of several GDP percent due to a decrease in accidents and congestion even without accounting for social and ecological effects.
An increase in the number of vehicles, especially in large cities, and inability of the existing road infrastructure to distribute transport flows, leads to a higher congestion level in transport networks. This problem makes the solution to navigational problems more and more important. Despite the popularity of these tasks, many existing commercial systems find a route in deterministic networks, not taking into account the time-dependent and stochastic properties of traffic flows, i.e. travel time of road links is considered as constant. This paper addresses the reliable routing problem in stochastic networks using actual information of the traffic flow parameters. We consider the following optimality criterion: maximization of the probability of arriving on time at a destination given a departure time and a time budget. The reliable shortest path takes into account the variance of the travel time of the road network segments, which makes it more applicable for solving routing problems in transport networks compared to standard shortest path search algorithms that take into account only the average travel time of network segments. To describe the travel time of the road network segments, it is proposed to use parametrically defined stable Levy probability distributions. The use of stable distributions allows replacing the operation of calculating convolution to determine the reliability of the path to recalculating the parameters of the distributions density, which significantly reduces the computational time of the algorithm. The proposed method gives a solution in the form of a decision, i.e. the route proposed in the solution is not fixed in advance, but adaptively changes depending on changes in the real state of the network. An experimental analysis of the algorithm carried out on a large-scale transport network of Samara, Russia, showed that the presented algorithm can significantly reduce the computational time of the reliable shortest path algorithm with a slight increase in travel time.
Currently, the coordinated use of autonomous underwater vehicles groups seems to be the most promising and ambitious technology to provide a solution to the whole range of oceanographic problems. Complex and large-scale underwater operations usually involve long stay activities of robotic groups under the limited vehicle’s battery capacity. In this context, available charging station within the operational area is required for long-term mission implementation. In order to ensure a high level of group performance capability, two following problems have to be handled simultaneously and accurately – to allocate all tasks between vehicles in the group and to determine the recharging order over the extended period of time. While doing this, it should be taken into account, that the real world underwater vehicle systems are partially self-contained and could be subjected to any malfunctions and unforeseen events.
The article is devoted to the suggested two-level dynamic mission planner based on the rendezvous point selection scheme. The idea is to divide a mission on a series of time-limited operating periods with the whole group rendezvous at the end of each period. The high-level planner’s objective here is to construct the recharging schedule for all vehicles in the group ensuring well-timed energy replenishment while preventing the simultaneous charging of a plenitude of robots. Based on this schedule, mission is decomposed to assign group rendezvous to each regrouping event (robot leaving the group for recharging or joining the group after recharging). This scheme of periodic rendezvous allows group to keep up its status regularly and to re-plan current strategy, if needed, almost on-the-fly. Low-level planner, in return, performs detailed group routing on the graph-like terrain for each operating period under vehicle’s technical restrictions and task’s spatiotemporal requirements. In this paper, we propose the evolutionary approach to decentralized implementation of both path planners using specialized heuristics, solution improvement techniques, and original chromosome-coding scheme. Both algorithm options for group mission planner are analyzed in the paper; the results of computational experiments are given.
As a result of the analysis, it was revealed that social networks (Vkontakte, Facebook), thematic communities in microblogging networks (Twitter), resources for travelers (TripAdvisor), transport portals (Autostrada) are a source of up-to-date and operational information about the traffic situation, the quality of transport services and passenger satisfaction with the quality of levels of transport services. However, the existing transport monitoring systems do not contain software tools capable of collecting and analyzing traffic information located in the Internet environment. This paper discusses the task of building a system for automatically retrieving and classifying road traffic information from transport Internet portals and testing the developed system for analyzing the transport networks of Crimea and the city of Sevastopol. To solve this problem, an analysis of open source libraries for thematic data collection and analysis was carried out. An algorithm for extracting and analyzing texts has been developed. A crawler was developed using the Scrapy package in Python3, and user feedback from the portal http://autostrada.info/ru was collected on the state of the transport system of Crimea and the city of Sevastopol. For texts lemmatization and vector text transformation, the tf, idf, tf-idf methods and their implementation in the Scikit-Learn library were considered: CountVectorizer and TF-IDF Vectorizer. For word processing, Bag-of-Words and n-gram methods were considered. During the development of the classifier model, the naive Bayes algorithm (MultinomialNB) and the linear classifier model with optimization of the stochastic gradient descent (SGDClassifier) were used. As a training sample, a corpus of 225,000 labeled texts from the Twitter resource was used. The classifier was trained, during which the cross-validation strategy and the ShuffleSplit method were used. Testing and comparison of the results of the pitch classification were carried out. According to the results of validation, the linear model with the n-gram scheme [1, 3] and the vectorizer TF-IDF turned out to be the best. During the approbation of the developed system, the collection and analysis of reviews related to the quality of transport networks of the Republic of Crimea and the city of Sevastopol were conducted. Conclusions are drawn and prospects for further functional development of the developed tools are defined.
In the paper is considered the task of control the process of information interaction in heterogeneous virtual network of cyber-objects. We propose the infrastructure model that allows using various technologies of OSI transport layer, including multi-protocol wireless data exchange tools. The simulation results of access to telematics services confirm the possibility of creating sustainable delay-tolerant virtual channels.
The paper describes an architecture of the logistics system based on application of the smart space idea to finding fellow-travelers for drivers. The ontology formed by mobile devices of the system participants and interconnections between them are presented. The paper also describes algorithms for finding appropriate fellow-travelers for drivers as well as definition of the pick-up and drop-off points meeting requirements of both drivers and passengers. Due to the rather large dimension of the problem, the usage of heuristics significantly reducing the dimension of the task is proposed. To demonstrate the possibilities of the architecture and its underlying components, the software prototype of this system has been developed and described.
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