Ambient concentrations of trace elements with 2 h time resolution were measured in PM10−2.5, PM2.5−1.0 and PM1.0−0.3 size ranges at kerbside, urban background and rural sites in London during winter 2012. Samples were collected using rotating drum impactors (RDIs) and subsequently analysed with synchrotron radiation-induced X-ray fluorescence spectrometry (SR-XRF). Quantification of kerb and ur...

Currently, there are kinds of algorithms in order to detect real-time urban traffic condition. Most of these approaches consider speed of vehicles as a main metric to describe traffic situation. In this paper, we find out two important observations through several experiments. (1) In urban city, the speed of vehicles is influenced significantly by some factors such as traffic lights delay and r...

Based on the two-dimension cellular automaton traffic flow model (BML model), a mixed traffic flow model of urban traffic that considering the transit traffic is established in this paper by using theDon't block the box rules. We have investigated the influences of the transit traffic ratio, and found that, in most cases, the urban traffic flow exhibited jam phase. Moreover, focusing on the tra...

By 2050, two-thirds of the world’s 9.6 billion people will live in urban areas [2]. In many cities, opportunities to expand urban road networks are limited, so existing roads will need to more efficiently accommodate higher volumes of traffic. Consequently, there is a pressing need for technologically viable, low-cost solutions that can work with existing infrastructure to help alleviate increa...

Reliable Advanced Driver Assistance Systems (ADAS) aid drivers in a variety of traffic and environment/weather conditions. Growing traffic volumes require sensors and systems that handle difficult urban and non-urban scenarios. For such systems, the EU FP7 project ADOSE is developing and evaluating new cost-efficient sensor technology that will provide vehicles with a ‘virtual safety belt’ by a...

In the world of transport management, the term ‘anticipation’ is gradually replacing ‘reaction’. Indeed, the ability to forecast traffic evolution in a network should ideally form the basis for many traffic management strategies and multiple ITS applications. Real-time prediction capabilities are therefore becoming a concrete need for the management of networks, both for urban and interurban en...

The rapid and ever-increasing population and urban activities have imposed a massive demand on Urban Transportation Systems (UTS). These systems were not prepared for such events, so traffic congestion and defective metropolitan systems were a direct consequence of this deficiency. The explosion of the computing technology brought together expertise from different scientific and technical disci...

Urban traffic gathers increasing interest as cities become bigger, crowded and “smart”. We present a system for heterogeneous stream processing and crowdsourcing supporting intelligent urban traffic management. Complex events related to traffic congestion (trends) are detected from heterogeneous sources involving fixed sensors mounted on intersections and mobile sensors mounted on public transp...

In this project we focuss on intelligent dynamic urban traffic management and control system that can adaptively respond to real-time traffic conditions. In this paper we investigate the usability and aplicability of autonomous intelligent agents, while maintaining high levels of accuracy and usability of such a dynamic urban traffic system. Aim of this part of the research is to develop insigh...