Abstract

In this paper, a comparative study between a hybrid technique that combines a Genetic Algorithm with a Cross Entropy method to optimize Fuzzy Rule-Based Systems, and literature techniques is presented. These techniques are applied to traffic congestion datasets in order to determine their performance in this area. Different types of datasets have been chosen. The used time horizons are 5, 15 and 30 min. Results show that the hybrid technique improves those results obtained by the techniques of the state of the art. In this way, the performed experimentation shows the competitiveness of the proposal in this area of application. Document type: Part of book or chapter of book

Abstract

Recent advances in wireless communication technologies are making it possible for automobiles to be integrated into the global network. Intelligent Transportation Systems with vehicles in the loop are expected to significantly improve road safety, reduce traffic congestion and cut greenhouse gas emissions. This is made possible in the USA by Dedicated Short Range Communications (DSRC), which employs the IEEE 802.11p standard over the 75MHz of spectrum in the 5.9 GHz band allocated by the FCC for vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications. DSRC is expected to revolutionize road transportation by making possible many real-time safety applications. However, global deployment of DSRC is not expected to materialize in the near term due to regulatory and financial challenges. In the meantime, vehicles and their passengers are increasingly equipped with different forms of wireless networking capabilities, e.g., cellular, WiFi and WiMAX. Thus there is also a growing interest in supporting applications like infotainment, travel advisory, route planning, etc., using heterogeneous wireless networks. In this presentation, I shall describe several applications that leverage the wireless communications to put vehicles in the loop. Different applicants impose different requirements on the wireless network for data routing, transfer latency, etc. I shall review the technical challenges that need to be overcome to meet some of these requirements, and describe solutions developed in our recent research to meet these challenges. I shall conclude the presentation by discussing some future research directions. Document type: Part of book or chapter of book

Abstract

Intelligent Transportation Systems emerged to meet the increasing demand for more efficient, reliable and safer transportation systems. These systems combine electronic, communication and information technologies with traffic engineering to respond to the former challenges. The benefits of Intelligent Transportation Systems have been extensively proved in many different facets of transport and Soft Computing has played a major role in achieving these successful results. This book chapter aims at gathering and discussing some of the most relevant and recent advances of the application of Soft Computing in four important areas of Intelligent Transportation Systems as autonomous driving, traffic state prediction, vehicle route planning and vehicular ad hoc networks. Document type: Part of book or chapter of book

Abstract

This paper describes a system for pedestrian detection in infrared images implemented and tested on an experimental vehicle. A specific stabilization procedure is applied after image acquisition and before processing to cope with vehicle movements affecting the camera calibration. The localization of pedestrians is based on the search for warm symmetrical objects with specific size and aspect ratio. A set of filters is used to reduce false detections. The final validation process relies on the human shape’s morphological characteristics. Document type: Part of book or chapter of book

Abstract

The energy consumption from the expanding use of information and communications technology (ICT) is unsustainable with present drivers, and it will impact heavily on the future climate change. However, ICT devices have the potential to contribute signi - cantly to the reduction of CO2 emission and enhance resource e ciency in other sectors, e.g., transportation (through intelligent transportation and advanced driver assistance systems and self-driving vehicles), heating (through smart building control), and manu- facturing (through digital automation based on smart autonomous sensors). To address the energy sustainability of ICT and capture the full potential of ICT in resource e - ciency, a multidisciplinary ICT-energy community needs to be brought together cover- ing devices, microarchitectures, ultra large-scale integration (ULSI), high-performance computing (HPC), energy harvesting, energy storage, system design, embedded sys- tems, e cient electronics, static analysis, and computation. In this chapter, we introduce challenges and opportunities in this emerging eld and a common framework to strive towards energy-sustainable ICT. Document type: Part of book or chapter of book

Abstract

There is great concern over growing road accidents and associated fatalities. In order to reduce accidents, improve congestion and offer smooth flow of traffic, several measures, such as providing intelligence to transport, providing communication infrastructure along the road, and vehicular communication, are being undertaken. Traffic safety information broadcast from traffic lights using Visible Light Communication (VLC) is a new cost effective technology which assists drivers in taking necessary safety measures. This chapter presents the VLC broadcast system considering LED-based traffic lights. It discusses the integration of traffic light Roadside Units (RSUs) with upcoming Intelligent Transportation Systems (ITS) architecture. Some of the offered services using this technology in vehicular environment together with future directions and challenges are discussed. A prototype demonstrator of the designed VLC systems is also presented. Document type: Part of book or chapter of book

Abstract

Traffic congestion is a major issue that plagues many urban road networks large and small. Traffic engineers are now leaning towards Intelligent Traffic Systems as many types of physical changes to road networks are costly or infeasible. Multi-Agent Systems (MAS) have become a popular paradigm for exploring intelligent solutions to traffic management problems. There are many MAS approaches to traffic management that utilise market mechanisms. In market-based approaches, drivers “pay” to use the roadways. However, a major issue with many of these solutions is that they require technology that, as yet, does not exist or is not widely available. For example, they rely on a special software agent that resides within the vehicle. This “vehicle agent” is responsible for participating in the market mechanism and communicating with the transportation infrastructure. In this paper, an auction-based traffic controller is proposed which exploits all the benefits of market mechanisms without the need for a vehicle agent. Experimental results show that such a controller is better at reducing delay and increasing throughput in a simulated city, as compared to fixed-time signal controllers. Document type: Part of book or chapter of book

Abstract

An Intelligent Transportation System (ITS) is a system based on wireless communications which has been investigated for many years in order to provide new technologies able to improve safety and efficiency of road transportation with integrated vehicle and road systems. It combines all aspects of technology and systems design concepts in order to develop and improve transportation system of all kinds. ITS, which utilise information and communications technology in vehicle as well as within the roadside infrastructure, can also be used to improve mobility while increasing transport safety, reducing traffic congestion, maximising comfort, and reducing environmental impact (Andrisano et al., 2000). Intelligent transportation systems and applications can improve the quality of travel by selecting routes with up-to-the-minute information data, giving priority to response vehicle teams, notifying drivers about road incidents, and delivering ITS services to drivers. They can reduce fuel consumption by routing the vehicles to their destinations so that fuel waste is significantly reduced, and also fully utilise the capacity of the existing road vehicular networks by controlling the flow of vehicles based on traffic monitoring and detecting congestions. Document type: Part of book or chapter of book

Abstract

Class imbalance is among the most persistent complications which may confront the traditional supervised learning task in real-world applications. Among the different kind of classification problems that have been studied in the literature, the imbalanced ones, particularly those that represents real-world problems, have attracted the interest of many researchers in recent years. In order to face this problems, different approaches have been used or proposed in the literature, between then, soft computing and ensemble techniques. In this work, ensembles and fuzzy techniques have been applied to real-world traffic datasets in order to study their performance in imbalanced real-world scenarios. KEEL platform is used to carried out this study. The results show that different ensemble techniques obtain the best results in the proposed datasets. Document type: Part of book or chapter of book