Intelligent Transportation Systems Applications Research Articles

Applying deep learning techniques for the prediction of pedestrian behaviour on crossings with countdown signal timers.

The improvement of road safety is considered as a top priority on the agendas of governments and transport policy making stakeholders worldwide, with the ‘Vision zero’ target being the pinnacle of the European Commission’s road safety strategy. Increased attention has been given to pedestrians, since crashes involving this vulnerable user group, have a higher mortality rate. As a result, research focusing on the behaviour of pedestrians and on the application of Intelligent Transport Systems that will assist pedestrians, is of increased importance. This paper attempts to predict pedestrian behaviour on crossings with a Countdown Signal Timer (CST), through the application of two machine learning algorithms. In the frame of the case study presented, an intersection in the Kalamaria city of Thessaloniki, Greece, where countdown signal timers have been installed on the pedestrian traffic lights, is analysed. For the needs of the analysis two models were implemented, a Deep Neural Network (DNN) and a Logistic Regression model. Results of both models indicated a satisfactory performance. In detail, the DNN model managed to estimate the pedestrians’ crossing speed with a Mean Squared Error value of 0.0647 (km/h)2, while the Logistic Regression model, which classified pedestrians based on their behaviour, achieved an accuracy of 97%. The accurate determination of pedestrians’ crossing behaviour could not only underline the influence of countdown signal timers, but also highlight appropriate countermeasures that can make infrastructure safer for this user group. Findings of this research can prove beneficial for researchers, infrastructure operators and policy makers alike, in their effort to improve the safety level of pedestrians.

СИСТЕМА УПРАВЛЕНИЯ ДОРОЖНЫМ ДВИЖЕНИЕМ НА ОСНОВЕ ТЕХНОЛОГИИ БЛОКЧЕЙН И ИНТЕРНЕТА ВЕЩЕЙ

Blockchain is undergoing rapid development and has revolutionary potential applications in Intelligent Transportation Systems (ITS). Blockchain can be used to create a secure, reliable and decentralised autonomous system, creating the best use of legacy infrastructure and resources. One of the most important issues is the security issues caused by the evolution of ITS towards centralisation. Fast-growing technologies, including the Internet of Things (IoT) and cloud computing, enable most data processing, analysis and decision-making by centralised systems. With the continuous development of the Internet of Things, all kinds of smart systems are rapidly evolving to make life safer. Like many other industries, transport has entered a period of rapid change. The Intelligent Transport System is one of the fastest growing areas of smart systems, which is expected to improve road safety, alleviate traffic congestion and increase fuel efficiency. The main functions of an intelligent transport system are as follows: real-time monitoring of road conditions in specific areas, locating traffic accidents (crashes) in specific areas, dynamic monitoring and managing the continuous use of public transport services, which can lead to changes in vehicle traffic. In this paper, the above-mentioned functionality of an intelligent transport system will be used as basic modelling scenarios for the design and implementation of an intelligent transport system based on the Internet of Things and blockchain – both of which have the inherent characteristics of distributed technology – combining sensor nodes of the Internet of Things and distributed registry technology, to record changes in intelligent transport systems and create a credit token mechanism for op The intelligent transport system described in this paper is intended to be used only as a pilot project, subject to the conditions as shown in the simulated scenario. In real-world traffic scenarios, it may produce more complex system and data security issues, which will be described and analysed in detail in the article. An intelligent traffic system is a complex intelligent system; it can significantly change and reinvent the wheel for traffic conditions. Based on the system development discussed in this article, there are many more requirements and issues that need to be addressed in the future. Such topics will be covered in detail in our subsequent studies.

АНАЛИЗ ТЕНДЕНЦИЙ РАЗВИТИЯ ТЕХНОЛОГИЙ ГРУЗОВЫХ ПЕРЕВОЗОК В КИТАЙСКОЙ НАРОДНОЙ РЕСПУБЛИКЕ

Blockchain is undergoing rapid development and has revolutionary potential for application in Intelligent Transportation Systems (ITS) applications. Blockchain can be used to create a secure, reliable and decentralised autonomous system, creating the best use of legacy infrastructure and resources. One of the most important issues is the security issues caused by the evolution of ITS to-wards centralisation. Fast-growing technologies, including the Internet of Things (IoT) and cloud computing, enable most data processing, analysis and decision-making by centralised systems.

PyTrack: A Map-Matching-Based Python Toolbox for Vehicle Trajectory Reconstruction

The exponential growth of IoT devices, smartphones, smartwatches, and vehicles equipped with positioning technology, such as Global Positioning System (GPS) modules, has boosted the development of location-based services for several applications in Intelligent Transportation Systems. However, the inherent error of location-based technologies makes it necessary to align the positioning trajectories to the actual underlying road network, a process known as map-matching. To the best of our knowledge, there are no comprehensive tools that allow us to model street networks, conduct topological and spatial analyses of the underlying street graph, perform map-matching processes on GPS point trajectories, and deeply analyse and elaborate these reconstructed trajectories. To address this issue, we present PyTrack, an open-source map-matching-based Python toolbox designed for academics, researchers and practitioners that integrate the recorded GPS coordinates with data provided by the OpenStreetMap, an open-source geographic information system. This manuscript overviews the architecture of the library offering a detailed description of its capabilities and modules. Besides, we provide an introductory guide to getting started with PyTrack covering the most fundamental steps of our framework. For more information on PyTrack, users are encouraged to visit the official repository at <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/cosbidev/PyTrack</uri> or the official documentation at <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://pytrack-lib.readthedocs.io</uri> .

Intelligent Reflecting Surface in 6G Vehicular Communications: A Survey

The applications of Intelligent Transportation System (ITS) and autonomous driving in the 6G era heavily rely on the massive information exchange of ultra-wide bandwidth, high reliability, and low latency to guarantee the safety and experience. On the other hand, the signals in high frequency bands including millimeter wave and Terahertz (THz) can be easily blocked by the obstacles. To address this problem, Intelligent Reflecting Surface (IRS) has attracted a lot of attention since it allows for reflecting the signals and changing the propagation directions in a high intelligence and low power consumption way, which creates smart radio environments. Due to its easy deployment and low expense, it has been widely recognized as a promising technology for ground and aerial vehicular networks to enhance signal strength, physical layer security, and positioning accuracy. In this paper, we give a comprehensive survey of current research works on different IRS applications in ground-based vehicular communications and aerial vehicular communications after discussing its basic knowledge and main characteristics. To improve current works and spark more ideas, we summarize the challenges and discuss the future perspectives of IRS-aided 6G vehicular communications.

РАЗРАБОТКА САМОИСПОЛНЯЮЩИХСЯ СМАРТ-КОНТРАКТОВ НА ETHEREUM ДЛЯ КОНТЕЙНЕРНЫХ ПЕРЕВОЗОК В КИТАЕ

Blockchain is a revolutionary new technology that facilitates peer-to-peer transfer of value without the need for a centralised intermediary. It uses cryptographic hashing functions, consensus protocols and decentralised data storage to ensure security, decentralised trust, immutability and transparency of business transactions. Blockchain technology paired with smart contracts is a reliable method of automating business rules in an efficient and trustworthy mechanism. A smart contract is a self-executing piece of code that runs on a blockchain platform. Predefined rules between participating organisations are translated into smart contract functions to establish trust. Blockchain is undergoing rapid development and has revolutionary potential for application in Intelligent Transport Systems applications. Blockchain can be used to create a secure, reliable and decentralised autonomous system, creating the best use of legacy infrastructure and resources. One of the most important issues is security, caused by the evolution of ITS towards centralisation. Fast-growing technologies, including the Internet of Things (IoT) and cloud computing, allow most data processing, analysis and decision-making to be done by centralised systems. The distinguishing factor of Ethereum is that it is programmed according to user requirements, rather than providing users with a set of predefined transactions, such as Bitcoin transactions. As a result, it could theoretically be used to automatically and securely execute any transaction involving trust, security or persistence. Although Ethereum is a relatively new implementation of blockchain, it has sparked reaction because of its potential to change the way many businesses operate.

Intelligent network connection technology based on 5G intelligent highway

Intelligent highways are important practical scenarios in the application of modern intelligent transportation systems. The rapid development of 5G intelligent network technology provides important technical support for improving the travel efficiency of autonomous driving in intelligent transportation systems and reducing the risk of collisions. This paper introduces the technology of 5G intelligent network connection, discusses the integration application of intelligent highway scene and intelligent network connection technology, and finally predicts the future development trend of the intelligent transportation system.

Distributed Clustering-Based Cooperative Vehicular Edge Computing for Real-Time Offloading Requests

Mobile vehicles have been considered as potential edge servers to provide computation resources for the emerging Intelligent Transportation System (ITS) applications. However, how to fully utilize the mobile computation resources to satisfy the real-time arrived computation requests has not been explored yet. This work will address the critical challenges of limited computation resources, stringent computation delay and unknown requirement statistics of real-time tasks in realistic vehicular edge computing scenarios. Specifically, we design a distributed clustering strategy to classify vehicles into multiple cooperative edge servers according to the available computation resources, effective connection time and the distribution of tasks&#x2019; expected deadlines. Then, a &#x2018;Less than or Equal to&#x2019; Generalized Assignment Problem (i.e., LEGAP) is formulated to maximize the system service revenue, and on this basis, we propose an offline Bound-and-Bound based Optimal (BBO) algorithm to make periodical scheduling with a global view of tasks&#x2019; requirement statistics. The quick branching is conducted by following a greedy solution and the upper bound at each branch is derived by solving a multiple-choice knapsack problem. In addition, we present an online heuristic algorithm which makes real-time offloading decision with the guarantees that the resource capacities of all the computing servers are never exceeded with new tasks arriving. Through comparing with the other four online algorithms, the BBO algorithm achieves the highest service revenues by offloading tasks with shorter delays, and the online heuristic algorithm has the best performance in improving the service ratios.

Survey on Deep Learning-Based Marine Object Detection

We present a survey on marine object detection based on deep neural network approaches, which are state-of-the-art approaches for the development of autonomous ship navigation, maritime surveillance, shipping management, and other intelligent transportation system applications in the future. The fundamental task of maritime transportation surveillance and autonomous ship navigation is to construct a reachable visual perception system that requires high efficiency and high accuracy of marine object detection. Therefore, high-performance deep learning-based algorithms and high-quality marine-related datasets need to be summarized. This survey focuses on summarizing the methods and application scenarios of maritime object detection, analyzes the characteristics of different marine-related datasets, highlights the marine detection application of the YOLO series model, and also discusses the current limitations of object detection based on deep learning and possible breakthrough directions. The large-scale, multiscenario industrialized neural network training is an indispensable link to solve the practical application of marine object detection. A widely accepted and standardized large-scale marine object verification dataset should be proposed.

Intelligent Planning and Research on Urban Traffic Congestion

For large and medium-sized cities, the planning and development of urban road networks may not keep pace with the growth of urban vehicles, resulting in traffic congestion on urban roads during peak hours. Take Jinan, a mid-sized city in China’s Shandong Province, for example. In view of the daily traffic jam of the city’s road traffic, through investigation and analysis, the existing problems of the road traffic are found out. Based on real-time, daily road traffic data, combined with the existing road network and the planned road network, the application of a road intelligent transportation system is proposed. Combined with the application of a road intelligent transportation system, this paper discusses the future development of urban road traffic and puts forward improvement suggestions for road traffic planning. This paper has reference value for city development, road network construction, the application of intelligent transportation systems, and road traffic planning.

Overview of Intelligent Transportation System Safety Countermeasures for Wrong-Way Driving

Wrong-way driving (WWD) crashes are rare but tend to cause severe injuries and fatalities. When they occur, WWD crashes are mostly head-on and tend to be more severe than any other crash type. Currently, most efforts to mitigate WWD crashes focus on the application of intelligent transportation systems (ITS) technologies. Since the mid-1960s, many agencies have proposed and tested a variety of countermeasures ranging from the conventional, including improvements in signage and pavement markings, to the more advanced, based mainly on ITS. The application of ITS in detecting and deterring WWD crashes involves a combination of several components, such as detection, warning, and action. The main objective of this paper is to provide a comprehensive overview of ITS technologies implemented by different transportation agencies in the mitigation and prevention of WWD crashes. This study proves the importance of ITS technologies that have seen widespread application in recent years. Moreover, according to the evaluation studies of different ITS-related countermeasures, it shows that the countermeasures deployed have been effective in detecting wrong-way drivers and reducing the rate of wrong-way incidents. The results will provide insights for policymakers, engineers, and researchers into the application of ITS for reducing the severity and frequency of WWD crashes and other incidents on highway facilities.

Parametric Evaluation of Internet of Things Applications to Freight Transportation Using Model-Based Systems Engineering

The intended purpose of an intelligent transportation systems (ITS) project is to automate operations through device-to-device connectivity. These devices generally represent stakeholder’s endpoints and expose interfaces to automated operations. Current trends in communication allow more applications and devices to perform functions traditionally allocated to the transportation ITS infrastructure. This connected environment of industrial internet of things presents design challenges because of the diversity of stakeholders, interfaces, and the messages among them. This may require new ways in which ITS planning can handle the scale and complexity of these highly connected systems. This work focuses on the modeling of the architecture of a freight-focused ITS application, including maritime ports. The proposed model integrates stakeholders, behaviors, and messages using the Systems Modeling Language (SysML). The key contribution of this work is to demonstrate the creation of an executable SysML model for an ITS application without sacrificing the typical Systems Engineering Management Plan artifacts (e.g., requirements traceability matrices and interface control documents). At the same time, the proposed model provides a re-usable pattern to support parametric analysis of candidate architectures with respect to any measure of effectiveness. This allows establishing a single source of architecture definition and having multiple architecture specializations depending on the measure of effectiveness being evaluated. Recommendations for implementation and integration with existing ITS tools are provided.

An Enhancement for IEEE 802.11p to Provision Quality of Service with Context Aware Channel Access for the Forward Collision Avoidance Application in Vehicular Ad Hoc Network.

Key application of an intelligent transportation system is traffic safety, and it provides driver assistance. Safety messages are of two types, beacon messages and event messages. The nodes broadcast these messages in the vehicular networks. The system must rely on a robust medium access control (MAC) protocol to support delivery of safety messages. The standard medium access scheme that is used in vehicular networks to provide service differentiation to support various applications is IEEE 802.11p. The emergency event messages should reach the drivers immediately to take necessary steps to avoid casualties on the road. In IEEE 802.11p, both of these messages are considered with the same priority so that no separate differentiation is created. The proposed work focuses on improving the quality of service for forward collision warning applications in intelligent transportation systems. The scheme proposes a priority-based cooperative MAC (PCMAC) for channel access that works on the context of information. Simulation and analytical results validate improved performance of PCMAC in terms of packet delivery ratio, throughput, and average packet delivery delay, as compared with other eminent MAC protocols. The simulation results show that it has a 9% higher improvement in throughput than IEEE 802.11p and has better performance in the increasing number of emergency messages.

Grids Versus Graphs: Partitioning Space for Improved Taxi Demand-Supply Forecasts

Accurate taxi demand-supply forecasting is a challenging application of ITS (Intelligent Transportation Systems), due to the complex spatial and temporal patterns involved. We investigate the impact of different spatial partitioning techniques on the prediction performance of an LSTM (Long Short-Term Memory) network, in the context of taxi demand-supply forecasting. We consider two tessellation schemes: (i) the variable-sized Voronoi tessellation, and (ii) the fixed-sized Geohash tessellation. While the widely employed ConvLSTM (Convolutional LSTM) method can model fixed-sized Geohash partitions, the standard convolutional filters cannot be applied on variable-sized Voronoi partitions. To explore the impact of the Voronoi strategy, we propose the use of a GraphLSTM (Graph-based LSTM) model, by representing the Voronoi spatial partitions as nodes on an arbitrarily structured graph. The GraphLSTM model offers competitive performance against the ConvLSTM model, at a lower computational complexity, across three real-world large-scale taxi demand-supply data sets, with different performance metrics. To ensure superior performance across diverse settings, a HEDGE based ensemble learning algorithm is applied over the ConvLSTM and the GraphLSTM networks.

A Cost-Benefit Analysis of the Installation of an Automatic Incident Detection System in Vilnius

A well-functioning transport network is a key element of a successful economy. One of the biggest problems in transportation is the large number of vehicles, which leads to congestion. Traffic congestion negatively influences the social and economic environment: it creates pollution and causes many accidents. A variety of innovative technologies are being applied in all areas. Different countries use Intelligent Transport Systems to create a safer, more efficient, and sustainable transport system to monitor and manage traffic flow. The application of Intelligent Transport Systems helps solve problems in the transport sector: Intelligent Transport Systems helps manage traffic flows, reduce accident rates, environmental pollution, and inform drivers and passengers about the traffic situation. Consequently, Intelligent Transport System improves the efficiency of the transport system, the quality of services, increases mobility, reduces energy consumption, and reduces the negative impact of vehicles on the environment. As reported by the Department of Statistics data in Lithuania, the number of road vehicles in the Vilnius region increases every year. Traffic accidents remain constant, and long-lasting traffic jams occur. Due to these reasons, Vilnius and its residents incur economic costs, and the transport system is used inefficiently. This article examines the importance of Intelligent Transport System application in solving congestion, pollution and accidents in Vilnius. A cost-benefit analysis of the Automatic Incident Detection System installation in Vilnius is performed.

Performance enhancement method for multiple license plate recognition in challenging environments

Multiple-license plate recognition is gaining popularity in the Intelligent Transport System (ITS) applications for security monitoring and surveillance. Advancements in acquisition devices have increased the availability of high definition (HD) images, which can capture images of multiple vehicles. Since license plate (LP) occupies a relatively small portion of an image, therefore, detection of LP in an image is considered a challenging task. Moreover, the overall performance deteriorates when the aforementioned factor combines with varying illumination conditions, such as night, dusk, and rainy. As it is difficult to locate a small object in an entire image, this paper proposes a two-step approach for plate localization in challenging conditions. In the first step, the Faster-Region-based Convolutional Neural Network algorithm (Faster R-CNN) is used to detect all the vehicles in an image, which results in scaled information to locate plates. In the second step, morphological operations are employed to reduce non-plate regions. Meanwhile, geometric properties are used to localize plates in the HSI color space. This approach increases accuracy and reduces processing time. For character recognition, the look-up table (LUT) classifier using adaptive boosting with modified census transform (MCT) as a feature extractor is used. Both proposed plate detection and character recognition methods have significantly outperformed conventional approaches in terms of precision and recall for multiple plate recognition.

Performance Evaluation of DSRC-Zigbee Heterogeneous Network for Intelligent Transportation System

Transportation is one of the primary needs of human beings that cannot be avoided, with the increasing vehicle can lead to a congested road situation which can lead to less safe road safety. An Intelligent Transportation System (ITS) can be used to increase road safety. This system uses a Dedicated Short-Range Communication (DSRC) protocol for network access due to its low latency transmission time. Unfortunately, there is research shows that DSRC has a performance issue in a dense area or increased network load. This problem is mostly solved with a heterogeneous network DSRC-LTE but utilizes mobile phone networks that dynamically change can lead to inconsistent and unpredictable network performance. There is some research about ZigBee for ITS shows that it is decent enough for non-critical applications. Thus, the authors try to utilize Zigbee to create the DSRC-Zigbee heterogeneous network so that the network is independent for the ITS application. The proposed heterogeneous network is a fixed model due to its simple architecture. OMNeT++ and Simulation of Urban Mobility (SUMO) are used to evaluate the performance of the network in an urban area with various scenarios. The simulation result shows that the proposed heterogeneous network is capable to improve the messages dissemination rate by 15.78% and 1.22% in a certain scenario compared to the homogeneous network DSRC only.

VEHICLE TO EVERYTHING (V2X) COMMUNICATIONS TECHNOLOGY FOR SMART MOBILITY IN MALAYSIA: A COMPREHENSIVE REVIEW

Vehicle to Everything (V2X) communication technology assesses the potential as the new phenomenon for Intelligent Transportation Systems (ITS) in the context of vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), vehicle-to-pedestrian (V2P), and vehicle-to-network (V2N). Dedicated Short-Range Communications (DSRC) is the conventional vehicular communication standard for ITS. The cellular network based on 4G/5G for ITS deployment has become a competitor to DSRC. Recent advancements in technologies have motivated the research community to develop a hybrid DSRC, and cellular networks approach to support reliable ITS applications. Nevertheless, as new techniques come forward, the technical and regulatory challenges may also vary across countries. Given that the existing comparative studies have not been covered as a whole, we evaluated the V2X communication technology to classify the adaptability of DSRC, cellular networks, and hybrid methods. The study also includes available V2X technology platforms and products. In addition, the challenges of deployments are also depicted in this study. The outcome indicates that many automotive industries and telecommunication providers recognize V2X substantial effect on ITS. The work is underway to decide which capabilities will be added since this is a long-term benefit for our future transportation.

FACTORS DETERMINING THE DEVELOPMENT OF INTELLIGENT TRANSPORT SYSTEMS

Purpose – foreign and Lithuanian researchers analyse the benefits of ITS (Intelligent transport systems) application and development opportunities in various aspects. Due to the rapid development of technology, most authors emphasise the need for new or at least repeated research on intelligent transport systems ITS. The aim of this article is to evaluate the factors determining the development of ITS after theoretical substantiation. Research methodology – the primary data was collected from the following databases: Eurostat, OECD, World Bank. This study uses the analysis of scientific literature, expert survey, multicriteria assessment (SAW and COPRAS methods). Findings – the results of this article indicate which factors determine the development of ITS the most: investments, the aim to increase road safety, well-developed infrastructure. It also identifies which of the chosen for analaysis countries has the greatest potential for developing of ITS – Germany. Research limitations – firstly, due to the lack of statistics only eight countries are included and the period of analysis is only two years. Another limitation is that experts from only two countries completed the survey. Practical implications – research on the development of ITS is carried out in order to analyse the country that has the biggest opportunity to develop ITS and the factors affecting the mentioned development. The results can be beneficial for ministries of transport in different countries for planning the application of ITS. Originality/Value – current study contributes to the existing literature by examining the specific factors affecting the development of ITS that were not analysed earlier. This article differs from others as includes some Northern ,Western European and Baltic countries. Findings can be used by government in planning the installation of ITS to get the maximum benefit from it.

Visible light communication for intelligent transportation systems: A review of the latest technologies

In seeking to improve traffic congestion and safety on roads and highways, there has been an increased interest in intelligent transportation systems (ITS). The emerging visible light communication (VLC) technology is a new candidate to enable wireless access in ITS. The purpose of this study is to present a comprehensive review of the current studies related to VLC. Since VLC facilitates illumination and data communication simultaneously, it reduces energy consumption significantly. Additionally, VLC is immune to electromagnetic interference, provides high data security, and utilizes unregulated visible light spectrum, showing promise as a potentially cheaper alternative to existing radio frequency (RF) based technology. Moreover, recent advances in semiconductor materials and solid-state technologies have enabled the development of efficient light-emitting diodes (LEDs) and laser diodes (LDs) which are used as transmitters in a VLC system. Although 10 s of Gbits/s data rate has been demonstrated in indoor VLC links, successful implementation of it in outdoor environments requires further research to overcome the challenges presented by environmental factors, unwanted lights, non-line of sight communication, directional radiation pattern, frequent fragmentation, and so on. Besides, in recent years, semiconductor LDs have been garnering more attention since they can transmit more data over longer distances due to their high quantum efficiency and modulation bandwidth compared to LEDs. As a result, urban planners, policy-makers, transportation engineers, and vehicle manufacturers are considering LD-based VLC to facilitate vehicle-to-vehicle and vehicle-to-infrastructure communication. Thus, this paper reviews and compares the most recent developments in VLC technologies, identifies their benefits and potential use in ITS applications, discusses the probable barriers for their implementation in our existing transportation infrastructure, and suggests future research directions and recommendations to overcome these challenges. • Recent developments in visible light communication (VLC) technology and its potential use in ITS applications are reviewed. • Light-emitting diodes (LEDs) and laser diodes (LDs) can be used as transmitters in VLC systems. • The overall performance of LDs is superior to that of the LEDs. • LDs can transmit more data over longer distances due to their high quantum efficiency and modulation bandwidth. • It is recommended to focus more on LD-based illumination in V2V and V2I communications.