Proactive, knowledge-based intelligent transportation system based on vehicular sensor networks (original) (raw)

ITSMEI: An intelligent transport system for monitoring traffic and event information

International Journal of Distributed Sensor Networks

The disorderly growth of urban centers can lead to serious socioeconomic disadvantages, such as health problems, due to long-term exposure to toxic gases and also monetary losses due to time stopped in congestion. Thus, there is a need for systems that help in the management and control of the flow of vehicles on the roads, seeking to reduce the damage resulting from a faulty transportation system and also avoiding the use of an inefficient system of information dissemination of urban roads. In this scenario, innovative systems are being developed to analyze the conjunction of road conditions to supervise and provide routes as needed for drivers to provide greater comfort and safety to vehicle traffic on urban roads. Thus, in this work, we propose the development of a system to monitor vehicle traffic, informing about events that are taking place on the roads in real time. The system can recommend new routes to drivers or allow drivers to take action based on information received fr...

Data Management Issues for Intelligent Transportation Systems (Position Paper)⋆

In this paper we discuss the technical challenges of devising a Data Stream Management System (DSMS) in the intelligent transportation scenario considered in the PEGASUS project, where the final aim is to provide reliable and timely information to improve the safety and the efficiency of vehicles' and goods' flows. The system should collect and integrate the large amounts of geo-located stream items coming from On Board Units (OBUs) installed on vehicles, with the aim of producing real-time maps including traffic and Points Of Interest (POIs) information to be then distributed to OBUs. OBUs' smart navigation engines will exploit these maps to enhance mobility and provide user-targeted information. We propose a two-tiered GIS DSMS architecture where stream items are pulled from the source input stream, processed and stored in a result container to be further pulled by other operators. The system reduces the data acquisition costs by adopting communication-saving policies, supports ad-hoc strategies for reducing the storage management costs (lowering response times and memory consumption), and provides the required data access functionalities through an SQL-like query language enhanced with stream, event, spatial and temporal operators. OBU stream items are also exploited to detect Events Of Interest (EOIs) such as jams and accidents and to support a collaborative mechanism for user-powered POI management and rating. EOIs and POIs are modeled through specific ontologies which allow for a flexible and extensible data management and guarantee data independence from the raw streams.

Intelligent Transport Systems

International Journal for Research in Applied Science & Engineering Technology (IJRASET), 2022

Growing economic activities aand others are among the factors that make many cities busy places today especially in traffic systems. Road networks that seem to be spacious sometimes become completely congested so much so that traffic mobility looks standstill. This impacts negatively on traffic users resources in terms of time management, fuel and other resource. This paper discusses the background trend in traffic activities amid congestion environment and proposes an Intelligent Traffic System that uses Machine Learning technique of predictive classification and regression to help traffic users determine forehand on the congestion status of available roads or highways. This further suggests that if the road user tries to avoid congestion, then the congestion levels will minimize. For simplicity, the data that has been used for congestion has been from a csv file containing previous datasets of local roads or highways.

Data management issues for intelligent transportation systems

Intelligent Transportation Systems: An Overview of Current Trends and Limitations

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT

Artificial intelligence (AI) is developing at a rapid rate, opening up previously unimaginable prospects to improve the performance of various industries and enterprises, including the transportation sector. AI is being used in the transportation sector to address issues such as rising travel demand, CO2 emissions, safety problems, and environmental damage. . In this digital age, it is more feasible to handle these challenges in a more effective and efficient manner due to the abundance of quantitative and qualitative data. A thorough understanding of the interactions between AI and data on the one hand, and the characteristics and factors of the transportation system on the other, is necessary for the successful use of AI. This article is a compendium of many problems affecting the transportation sector that are categorised as Intelligent Transportation Systems problems. Some of the sub-systems from Intelligent Transportation Systems that are taken into consideration are related to...

A survey on intelligent transportation systems

2013

Transportation or transport sector is a legal source to take or carry things from one place to another. With the passage of time, transportation faces many issues like high accidents rate, traffic congestion, traffic & carbon emissions air pollution, etc. In some cases, transportation sector faced alleviating the brutality of crash related injuries in accident. Due to such complexity, researchers integrate virtual technologies with transportation which known as Intelligent Transport System. The idea of virtual technologies integration is a novel in transportation field and it plays a vital part to overcome the issues in global world. This paper tackles the great variety of Intelligent Transport System applications, technologies and its different areas. The objective of this literature review is to integrate and synthesize some areas and applications, technologies discuss with all prospects. Furthermore, this research focuses on a wide field named Intelligent Transport Systems, discussed its wide applications, used technologies and its usage in different areas respectively.

Intelligent transportation systems to mitigate road traffic congestion

Intelligenza Artificiale, 2022

Intelligent transport systems have efficiently and effectively proved themselves in settling up the problem of traffic congestion around the world. The multi-agent based transportation system is one of the most important intelligent transport systems, which represents an interaction among the neighbouring vehicles, drivers, roads, infrastructure and vehicles. In this paper, two traffic management models have been created to mitigate congestion and to ensure that emergency vehicles arrive as quickly as possible. A tool-chain SUMO-JADE is employed to create a microscopic simulation symbolizing the interactions of traffic. The simulation model has showed a significant reduction of at least 50% in the average time delay and thus a real improvement in the entire journey time.

Intelligent Transportation Systems

Imagine knowing real-time traffic conditions for virtually every highway or arterial roadway in the country and having that information available on multiple platforms, both in-vehicle and out. Imagine driving down an expressway with a telematics unit that, combining GPS with real-time traffic information, could audibly alert you that you are approaching a blind curve with traffic backed up immediately ahead and that you need to brake immediately. Envision enjoying a mobile device that can display real-time traffic information (while simultaneously helping to generate that information), optimize your route accordingly, and electronically pay tolls when you are on the highway (or fares when you’re using mass transit). Imagine a performance-based transportation system that makes capital investment decisions regarding competing transportation projects based on a detailed understanding of their cost-benefit trade-offs enabled by meticulously collected data. Information technology (IT) has made all this possible and the platform for achieving this is Intelligent Transportation Systems. ITS applies advanced technologies of electronics, communications, computers, control and sensing and detecting in all kinds of transportation system in order to improve safety, efficiency and service, and traffic situation through transmitting real-time information. It caters for the inadequacies of the highway system. It has main objectives which include:  To improve traffic safety.  To relieve traffic congestion.  To improve transportation efficiency.  To reduce air pollution.  To increase the energy efficiency to promote the development of related industries. For a system of this efficiency and complexity, Civil engineers will definitely play an important role in achieving this system. Other professionals like electrical engineers, computer scientists are also instrumental in making this system a reality.

Query-based Information Gathering in Intelligent Transportation Systems

Electronic Notes in Discrete Mathematics, 2010

One of the roles of Intelligent Transportation Systems (ITS) is to collect and disseminate certain information from different locations of the road network. This information can be related to traffic safety (e.g. dangerous situations on the road), to traffic efficiency (e.g. current experienced travel times), or to other information (e.g. parking possibilities) the drivers are interested in. The communication network used for dissemination can be either distributed or centralized or a combination of them. In this paper we focus on optimizing the positions where vehicles along their routes should send query messages in order to collect information about traffic jams. This problem is formulated and solved as an Integer Linear Programming problem. Finally, the numerical results are presented and analyzed.

Proactive, knowledge-based intelligent transportation system based on vehicular sensor networks (original) (raw)

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