Problem Statement
Urban transportation faces challenges such as traffic congestion, inefficient route
planning, and a lack of coordination between vehicles. An intelligent and integrated
transportation system is needed to address these issues. This project aims to develop a
comprehensive Intelligent Transportation System (ITS) using AI
Abstract
The Intelligent Transportation System project aims to transform urban mobility by
leveraging AI technologies. The system will incorporate AI algorithms for traffic
prediction, dynamic route optimization, and coordination with autonomous vehicles. By
integrating data from various sources, including traffic cameras and sensors, the ITS will
provide real-time solutions to enhance the efficiency and safety of urban transportation.
Outcome
● Traffic Prediction: Implement AI models for accurately predicting traffic
conditions in real-time.
● Dynamic Route Optimization: Develop algorithms for optimizing routes based on
current traffic and user preferences.
● Autonomous Vehicle Coordination: Enable communication and coordination
between autonomous vehicles to improve traffic flow.
● Safety Enhancement: Implement features to enhance road safety, such as
collision avoidance and emergency response systems.
● Reduced Congestion: Ultimately, contribute to reduced traffic congestion and
improved overall urban transportation.
Reference
Over the past decades, Intelligent Transportation Systems (ITS) have developed and deployed in order to improve transportation safety and mobility, reduces environmental impact, promotes sustainable transportation development and enhances productivity. ITS combines high technology and improvements in information systems, communication, sensors, controllers and advanced mathematical methods with the conventional world of transportation infrastructure. As an inter-disciplinary research field, it is difficult to have a clear picture about the whole system for a novice researcher. This paper (1) proposes an ITS architecture, which is based on the requirement and technology at the present stage, (2) sort out the bottleneck issue that lie behind intelligent transportation research, (3) explores the future prospect of the ITS and research focus as new technologies become available.
- J.-P. Rodrigue, C. Comtois and B. Slack, The Geography of Transport Systems, Routledge, 2013.
- J. Sussman, Perspectives on intelligent transportation systems (ITS), Springer Science+Business Media, 2005.
- “Transportation Operations: An Organizational and Institutional Perspective” in Perspectives on Intelligent Transportation Systems (ITS), Springer US, pp. 21-74, 2005.
- X. Yan, H. Zhang and C. Wu, “Research and Development of Intelligent Transportation Systems,” 2012 11th International Symposium on Distributed Computing and Applications to Business Engineering Science, pp. 321-327, 2012.
- J. A. Moral-Muñoz, M. J. Cobo, F. Chiclana, A. Collop and E. Herrera-Viedma, “Analyzing Highly Cited Papers in Intelligent Transportation Systems,” IEEE Trans. Intell. Transp. Syst., vol. 17, no. 4, pp. 993-1001, Apr. 2016.
https://ieeexplore.ieee.org/document/7980336