Framework for Traffic Pattern Identification: Required Step for Short-term Forecasting

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 environments, and today’s road operator has increasingly complex and exacting requirements. Recognising temporal patterns in traffic or the manner in which sequential traffic events evolve over time have been important considerations in short-term traffic forecasting. However, little work has been conducted in the area of identifying or associating traffic pattern occurrence with prevailing traffic conditions. This paper presents a framework for detection pattern identification based on finite mixture models using the EM algorithm for parameter estimation. The computation results have been conducted taking into account the traffic data available in an urban network.

Shot-noise spectroscopy of energy resolved ballistic currents

We investigate the shot noise of nonequilibrium carriers injected into a ballistic conductor and interacting via long-range Coulomb forces. Coulomb interactions are shown to act as an energy analyzer of the profile of injected electrons by means of the fluctuations of the potential barrier at the emitter contact. We show that the details in the energy profile can be extracted from shot-noise measurements in the Coulomb interaction regime, but cannot be obtained from time-averaged quantities or shot-noise measurements in the absence of interactions.

Microcontroller-based interface circuit for inductive sensors

This work proposes a fully-digital interface circuit for the measurement of inductive sensors using a low-cost microcontroller (µC) and without any intermediate active circuit. Apart from the µC and the sensor, the circuit just requires an external resistor and a reference inductance so that two RL circuits with a high-pass filter (HPF) topology are formed. The µC appropriately excites such RL circuits in order to measure the discharging time of the voltage across each inductance (i.e. sensing and reference) and then it uses such discharging times to estimate the sensor inductance. Experimental tests using a commercial µC show a non-linearity error (NLE) lower than 0.5%FSS (Full-Scale Span) when measuring inductances from 1 mH to 10 mH, and from 10 mH to 100 mH.