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10INTERNATIONAL SCIENTIFIC AND TECHNICAL CONFERENCE "DIGITAL TECHNOLOGIES: PROBLEMS AND SOLUTIONS OF PRACTICAL IMPLEMENTATION IN THE SPHERES" APRIL 27-28, 2023
AN ANALYSIS OF THE DEVELOPMENT OF INTELLIGENT TRANSPORTATION
SYSTEMS
Temurbek Kuchkorov 1, Jamshid Khamzaev2, Zamira Allamuratova3
1Department of Computer systems, Tashkent University of Information Technologies Named after Muhammad Al-Khwarizmi, Tashkent 100200, Uzbekistan. ^Department of Information-Computer Technologies and Programming, Tashkent University of Information Technologies Named after Muhammad Al-Khwarizmi, Tashkent 100200,
Uzbekistan. https://doi.org/10.5281/zenodo.7858365
Abstract. This article discusses the analysis of the development of intelligent transportation system and its integration into a city. As well as, the role, history and components of intelligent transportation system are provided briefly.
Keywords: Intelligent Transportation Systems, development, Traffic Management Systems, Identify Transportation Challenges.
Introduction
Intelligent Transportation Systems (ITS) is a technology-driven approach to improve the efficiency, safety, and sustainability of transportation systems. ITS integrates advanced communication, sensing, and control technologies to enhance the performance of transportation networks, vehicles, and travelers. The goal of ITS is to provide a seamless, safe, and sustainable transportation system that meets the needs of all users, including drivers, pedestrians, cyclists, and public transportation users. With the rapid advancement of technology, ITS is becoming increasingly important in addressing the challenges of urbanization, congestion, and environmental sustainability [1,2].
The development of Intelligent Transportation Systems (ITS) can be traced back to the 1960s when the first traffic control centers were established in the United States. These centers used closed-circuit television cameras and radio communication to monitor traffic flow and manage congestion. Over the years, ITS has evolved to include a wide range of technologies and applications.
In the 1980s, the development of computer technology and communication networks led to the emergence of advanced traffic management systems (ATMS) and advanced traveler information systems (ATIS). These systems used real-time data from sensors and cameras to monitor traffic flow and provide real-time information to drivers.
In the 1990s, the focus of ITS shifted towards the development of advanced vehicle control systems (AVCS) and advanced public transportation systems (APTS). AVCS used sensors and communication technologies to improve the safety and performance of vehicles, while APTS used technology to improve the efficiency and reliability of public transportation systems.
In the 2000s, the development of wireless communication technologies and the internet led to the emergence of new ITS applications such as connected vehicles and smart parking systems. Connected vehicles use wireless communication to exchange information with other vehicles and infrastructure, while smart parking systems use sensors and communication technologies to guide drivers to available parking spaces [10].
Main part
INTERNATIONAL SCIENTIFIC AND TECHNICAL CONFERENCE "DIGITAL TECHNOLOGIES: PROBLEMS AND SOLUTIONS OF PRACTICAL IMPLEMENTATION IN THE SPHERES" APRIL 27-28, 2023
Today, ITS is a rapidly evolving field that continues to develop new technologies and applications. The focus of ITS is shifting towards the development of integrated systems that combine multiple technologies to create a seamless, safe, and sustainable transportation system. The development of ITS is driven by the need to address the challenges of urbanization, population growth, and climate change.
The main part of Intelligent Transportation Systems (ITS) involves the integration of various technologies to improve the performance of transportation systems. These technologies include:
1. Advanced Traffic Management Systems (ATMS): ATMS uses real-time data from sensors, cameras, and other sources to monitor traffic flow and manage congestion. It helps to optimize traffic signal timings, reroute traffic, and provide real-time information to drivers.
2. Advanced Traveler Information Systems (ATIS): ATIS provides real-time information to travelers about traffic conditions, travel times, and alternative routes. It helps to improve the efficiency of travel and reduce congestion.
3. Advanced Vehicle Control Systems (AVCS): AVCS uses sensors and communication technologies to improve the safety and performance of vehicles. It includes technologies such as adaptive cruise control, lane departure warning, and collision avoidance systems.
4. Advanced Public Transportation Systems (APTS): APTS uses technology to improve the efficiency and reliability of public transportation systems. It includes technologies such as realtime passenger information, automatic vehicle location, and fare collection systems.
5. Commercial Vehicle Operations (CVO): CVO uses technology to improve the safety and efficiency of commercial vehicles. It includes technologies such as electronic logging devices, weigh-in-motion systems, and automated enforcement systems.
The integration of these technologies helps to create a seamless, safe, and sustainable transportation system that meets the needs of all users. ITS has the potential to reduce congestion, improve safety, and reduce environmental impacts. It is becoming increasingly important in addressing the challenges of urbanization, population growth, and climate change [9].
Integrating Intelligent Transportation Systems (ITS) into a city involves several steps, including:
1. Identify Transportation Challenges: The first step in integrating ITS into a city is to identify the transportation challenges that need to be addressed. This may involve analyzing traffic data, identifying bottlenecks and congestion points, and assessing the needs of different types of users [8].
2. Develop Goals and Objectives: Once the transportation challenges have been identified, the next step is to develop goals and objectives for the ITS. This may involve setting targets for reducing congestion, improving safety, and enhancing mobility.
3. Select Technologies and Applications: The next step is to select the appropriate technologies and applications to achieve the goals and objectives of the ITS. This may involve selecting sensors, cameras, communication networks, and other devices, as well as developing software and data management systems.
4. Develop System Architecture: Once the technologies and applications have been selected, the next step is to develop the system architecture. This involves determining how the
INTERNATIONAL SCIENTIFIC AND TECHNICAL CONFERENCE "DIGITAL TECHNOLOGIES: PROBLEMS AND SOLUTIONS OF PRACTICAL IMPLEMENTATION IN THE SPHERES" APRIL 27-28, 2023
different components of the ITS will work together and how data will be collected, analyzed, and shared.
5. Implement the System: The next step is to implement the ITS. This involves installing the hardware and software components of the system, integrating them into the existing transportation infrastructure, and testing the system to ensure that it is working properly.
6. Monitor and Evaluate the System: Once the ITS is operational, it is important to monitor and evaluate its performance. This involves collecting data on traffic flow, user behavior , and system performance, and assessing the effectiveness of the system in achieving its goals and objectives.
7. Maintain and Upgrade the System: Finally, it is important to maintain and upgrade the ITS to ensure that it continues to meet the needs of users and address changing transportation challenges. This may involve replacing outdated hardware and software components, upgrading communication networks, and integrating new technologies and applications.
Integrating ITS into a city requires collaboration between transportation agencies, technology providers, policymakers, and other stakeholders. It is important to involve users in the development process to ensure that the system meets their needs and is user-friendly.
On the other hand, modern Intelligent Transportation Systems (ITS) face several issues that need to be addressed to ensure their effectiveness and sustainability. Some of these issues include:
1. Data Privacy and Security [3-6]: ITS rely on the collection and sharing of large amounts of data, including personal information about drivers and passengers. Ensuring the privacy and security of this data is essential to maintain public trust in the system.
2. Interoperability: ITS often involve multiple technologies and applications that need to work together seamlessly. Ensuring interoperability between different systems and devices is essential to ensure the effectiveness of the system.
3. Funding and Financing: Developing and maintaining ITS can be expensive, and funding and financing can be a challenge. Ensuring sustainable funding sources is essential to ensure the long-term viability of the system.
4. User Acceptance: ITS can be complex and require changes in user behavior [7]. Ensuring user acceptance and adoption of the system is essential to ensure its effectiveness.
5. Legal and Regulatory Issues: ITS often involve new technologies and applications that may not be covered by existing laws and regulations. Ensuring that legal and regulatory frameworks are in place to support the development and operation of ITS is essential.
6. Equity and Accessibility: ITS should be accessible to all users, regardless of income, age, or ability. Ensuring equity and accessibility is essential to ensure that the benefits of ITS are shared by all members of society.
In summary, Intelligent Transportation Systems (ITS) have the potential to transform urban transportation by utilizing advanced technologies and data analytics to reduce congestion, enhance safety, and improve mobility for all users. However, the development and implementation of ITS face various challenges, including data privacy and security, interoperability, funding and financing, user acceptance, legal and regulatory issues, and equity and accessibility. Addressing these challenges requires collaboration among transportation agencies, technology providers, policymakers, and other stakeholders to ensure that ITS are sustainable, equitable, and effective.
INTERNATIONAL SCIENTIFIC AND TECHNICAL CONFERENCE "DIGITAL TECHNOLOGIES: PROBLEMS AND SOLUTIONS OF PRACTICAL IMPLEMENTATION IN THE SPHERES" APRIL 27-28, 2023
With the right strategies and partnerships, ITS can create more efficient, safe, and sustainable
transportation systems for our cities.
REFERENCES
1. Safarov F, Kutlimuratov A, Abdusalomov AB, Nasimov R, Cho Y-I. Deep Learning Recommendations of E-Education Based on Clustering and Sequence. Electronics. 2023; 12(4):809. https://doi.org/10.3390/electronics12040809
2. Kutlimuratov, A.; Abdusalomov, A.B.; Oteniyazov, R.; Mirzakhalilov, S.; Whangbo, T.K. Modeling and Applying Implicit Dormant Features for Recommendation via Clustering and Deep Factorization. Sensors 2022, 22, 8224. https://doi.org/10.3390/s22218224.
3. Abdusalomov, A.; Baratov, N.; Kutlimuratov, A.; Whangbo, T.K. An Improvement of the Fire Detection and Classification Method Using YOLOv3 for Surveillance Systems. Sensors 2021, 21, 6519. https://doi.org/10.3390/s21196519.
4. Ilyosov, A.; Kutlimuratov, A.; Whangbo, T.-K. Deep-Sequence-Aware Candidate Generation for e-Learning System. Processes 2021, 9, 1454. https://doi.org/10.3390/pr9081454.
5. Abdusalomov, A.B.; Mukhiddinov, M.; Kutlimuratov, A.; Whangbo, T.K. Improved RealTime Fire Warning System Based on Advanced Technologies for Visually Impaired People. Sensors 2022, 22, 7305. https://doi.org/10.3390/s22197305.
6. Makhmudov, F.; Kutlimuratov, A.; Akhmedov, F.; Abdallah, M.S.; Cho, Y.-I. Modeling Speech Emotion Recognition via Attention-Oriented Parallel CNN Encoders. Electronics 2022, 11, 4047. https://doi.org/10.3390/electronics1123404
7. Kutlimuratov, A.; Abdusalomov, A.; Whangbo, T.K. Evolving Hierarchical and Tag Information via the Deeply Enhanced Weighted Non-Negative Matrix Factorization of Rating Predictions. Symmetry 2020, 12, 1930.
8. Kuchkorov, T., Khamzaev, J., Allamuratova, Z., & Ochilov, T. (2021, November). Traffic and road sign recognition using deep convolutional neural network. In 2021 International Conference on Information Science and Communications Technologies (ICISCT) (pp. 1-5). IEEE. DOI: 10.1109/ICISCT52966.2021.9670228
9. Khamzaev J., Yaxshiboyev R., Ochilov T., Siddiqov B. Driver sleepiness detection using convolution neural network. Central Asian Journal of Education and Computer Sciences. VOLUME 1, ISSUE 4, AUGUST 2022(CAJECS), ISSN: 2181-3213
10. Kuchkarov T. A., Hamzayev J. F., Allamuratova Z. J. Tracking the flow of motor vehicles on the roads with YOLOv5 and deepsort algorithms. Международной научной конференции, Минск, 23 ноября 2022 / Белорусский государственный университет информатики и радиоэлектроники ; редкол.: Л. Ю. Шилин [и др.]. - Минск : БГУИР, 2022. - С. 61-62. https://libeldoc.bsuir.by/handle/123456789/49250
