INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE
ISSN: 2692-5206, Impact Factor: 12,23
American Academic publishers, volume 05, issue 08,2025
Journal:
https://www.academicpublishers.org/journals/index.php/ijai
225
PROBLEMS OF DEVELOPING URBAN PASSENGER TRANSPORT SYSTEMS AND
THE ROLE OF ARTIFICIAL INTELLIGENCE
Zingirov Saydolim Zhuraevich
Associate Professor of the Department of Transport Logistics,
Andijan State Technical Institute
Abstract:
This article highlights the main problems in the development of urban passenger
transport systems and the role of artificial intelligence (AI) technologies in their solution. AI-
based systems play an important role in traffic flow management, traffic congestion reduction,
traffic speed increase, and passenger flow analysis. The article also analyzes how AI increases
the efficiency of the urban transport system through functions such as real-time data processing,
route optimization, and service quality monitoring. As a result, the possibilities of sustainable
and intelligent management of urban transport infrastructure using AI technologies are shown.
Keywords:
artificial intelligence, urban transport, traffic, passenger flow, optimization,
efficiency
Introduction.
Today, the rapid expansion of cities, the acceleration of the urbanization
process, and the growing demand of the population for transport make the development of
urban passenger transport systems an urgent issue. As population density increases, new and
complex problems arise for the city's internal transport systems. In particular, such issues as
traffic congestion, environmental pollution, inconvenience for passengers, ensuring the
continuity and safety of traffic require more and more attention. To effectively solve these
problems, the use of modern technologies, in particular, the capabilities of artificial intelligence
(AI), is expanding [1-3].
Traditional transport systems are often dependent on the human factor, which leads to certain
limitations and errors. Meanwhile, modern artificial intelligence systems can perform many
functions, such as accurate traffic flow management, passenger flow forecasting, traffic jam
prevention, and traffic optimization, by collecting, processing, and analyzing data in real time.
In particular, thanks to intelligent transport systems based on artificial intelligence (ITS -
Intelligent Transport Systems), it will be possible to achieve automatic control by integrating it
with urban infrastructure [4].
At the same time, through the introduction of AI technologies, efficiency will be achieved in
many areas, such as adapting the schedule of buses, subways, and other public transport,
optimizing routes, creating real-time passenger information systems, and monitoring the
technical condition of vehicles. This not only creates convenience for passengers, but also plays
an important role in ensuring environmental sustainability, reducing fuel consumption, and
reducing the overall costs of the transport system [5].
From this point of view, this scientific work is aimed at analyzing existing problems in the
development of urban passenger transport systems and a deep study of the role of artificial
intelligence technologies in solving these problems. The article examines current problems in
the transport system, the main functions of artificial intelligence, advanced foreign experience,
existing technologies, and the possibilities of their implementation. Also, the prospects of using
artificial intelligence in the cities of Uzbekistan, in particular, in the transport system of Andijan,
will be assessed based on the current situation and proposals [6].
INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE
ISSN: 2692-5206, Impact Factor: 12,23
American Academic publishers, volume 05, issue 08,2025
Journal:
https://www.academicpublishers.org/journals/index.php/ijai
226
The purpose of this study is to develop scientific and practical foundations for the
implementation of artificial intelligence technologies and to provide practical recommendations
for bringing the urban transport system to a more efficient, safe, and environmentally friendly
state.
Result and conclusion.
As a result of the analysis of urban passenger transport systems, the following problems were
identified:
1. unbalanced development of urban transport types (dominance of bus communication).
2. formation of barriers due to high load on the road network and, as a consequence, an increase
in the level of motorization, an increase in the number and size of the city's population.
3. lack of disorganized parking spaces and parking spaces, parking spaces for cars and
automobiles.
Low level of development of road infrastructure - the same level of location of roads and
railways, lack of priority movement of public transport.
4. low development of suburban transport, concentration of passengers using suburban transport,
etc. In the context of a modern large city, the main volume of passenger traffic is carried out
mainly by public transport, among which the most widespread.
Today, the problem of traffic congestion is the main one for millionaire cities.
Experience shows that the following organizational and road-building methods are used to
solve transport problems:
- organization of alternative movement of vehicles with even and odd numbers on different
days of the week;
- introduction of paid entry zones into the central part of the city;
- Strengthening measures against offenders for parking vehicles in improper locations,
underground and multi-level vehicle construction;
- allocation of separate roads for urban passenger transport;
- construction of a high-speed highway system capable of providing transport links bypassing
the city, etc.
In the current conditions, it is necessary to search for reserves for improving the traffic safety
system by increasing passenger speed and mobility. This will increase public trust in public
transport.
The models and methods proposed in the dissertation research, contributing to the high-quality
organization of SHYTT, allow organizing the rational use of various types of transport in urban
conditions.
INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE
ISSN: 2692-5206, Impact Factor: 12,23
American Academic publishers, volume 05, issue 08,2025
Journal:
https://www.academicpublishers.org/journals/index.php/ijai
227
Fig 1.
AI in Urban Mobility: Citizen-Centric Approach
Conclusion. n conclusion, the development of urban passenger transport systems is a crucial
aspect of modern city planning, especially in the context of growing population density, traffic
congestion, and increasing demand for sustainable mobility. Traditional management methods
are no longer sufficient to meet the complex and dynamic needs of urban transportation. The
integration of Artificial Intelligence (AI) into urban transport systems offers innovative
solutions for optimizing traffic flow, predicting passenger demand, enhancing safety, and
reducing environmental impact. AI-based technologies such as intelligent traffic control, real-
time route optimization, and predictive maintenance significantly improve the efficiency and
reliability of public transport services. Furthermore, AI enables the creation of adaptive systems
that respond swiftly to real-time changes and user needs. Implementing such smart transport
systems contributes not only to improving service quality and user convenience but also
supports energy saving and sustainable urban development.
Used literature:
1. H. Dia, "The role of intelligent transport systems in sustainable urban development,"
IEEE Transactions on Intelligent Transportation Systems
, vol. 11, no. 3, pp. 543–550,
Sep. 2010.
2. Y. Wang and M. Papageorgiou, "Real-time freeway traffic state estimation based on
extended Kalman filter: A general approach,"
Transportation Research Part B
, vol. 39,
no. 2, pp. 141–167, Feb. 2005.
3. S. Chen, B. He, and J. Sun, "AI-based smart public transportation: Opportunities and
challenges,"
IEEE Access
, vol. 8, pp. 145751–145765, 2020.
4. A. Nair, K. R. See, and S. Chan, "Predictive analytics in public transport: Using AI to
forecast passenger flow,"
IEEE Transactions on Big Data
, vol. 7, no. 2, pp. 377–387,
Jun. 2021.
INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE
ISSN: 2692-5206, Impact Factor: 12,23
American Academic publishers, volume 05, issue 08,2025
Journal:
https://www.academicpublishers.org/journals/index.php/ijai
228
5. M. Treiber and A. Kesting,
Traffic Flow Dynamics: Data, Models and Simulation
,
Springer, 2013.
6. R. Bishop, "Intelligent vehicle applications worldwide,"
IEEE Intelligent Systems
, vol.
15, no. 1, pp. 78–81, Jan.–Feb. 2000.
