DSRC-based rear-end collision warning system – An error-component safety distance model and field test

Dedicated short-range communication (DSRC) technology can provide drivers with information about other vehicles that are beyond the normal range of vision and enables the development of driving support systems such as the rear-end collision warning system (ReCWS). However, technology constraints such as communication delays and GPS error affect the accuracy of a DSRC-based ReCWS. This paper proposes a ReCWS design that explicitly represents functional specifications of DSRC technology, including transmission delay specifications that describe the information transmission process and an error-component safety distance specification used to represent the effect of GPS error and the information propagation delay. We propose three collision warning strategies each with different deceleration requirements. The system is assembled with off-the-shelf DSRC and mobile technology that can be readily installed into test vehicles. To test the effectiveness of the proposed ReCWS, we ran a variety of controlled scenarios on a test track. The results show a high degree of warning accuracy. These field test results also provide calibrated system parameter values for future studies and designs of DSRC-based ReCWSs

Applying Markov decision process to understand driving decisions using basic safety messages data

While a number of studies have investigated driving behaviors, detailed microscopic driving data has only recently become available for analysis. Through Basic Safety Message (BSM) data from the Michigan Safety Pilot Program, this study applies a Markov Decision Process (MDP) framework to understand driving behavior in terms of acceleration, deceleration and maintaining speed decisions. Personally Revealed Choices (PRC) that maximize the expected sum of rewards for individual drivers are obtained by analyzing detailed data from 120 trips and the application of MDP. Specifically, this paper defines states based on the number of objects around the host vehicle and the distance to the front object. Given the states, individual drivers’ reward functions are estimated using the multinomial logit model and used in the MDP framework. Optimal policies (i.e. PRC) are obtained through a value iteration algorithm. The results show that as the number of objects increases around a host vehicle, the driver prefer to accelerate in order to escape the crowdedness around them. In addition, when trips are segmented based on the level of crowdedness, increased levels of trip crowdedness results in a fewer number of drivers accelerating because the traffic conditions constrain them to maintaining constant speed or deceleration. One potential application of this study is to generate short-term predictive driver decision information through historical driving performance, which can be used to warn a host vehicle driver when the person substantially deviates from their own historical PRC. This information could also be disseminated to surrounding vehicles as well, enabling them to foresee the states and actions of other drivers and potentially avoid collisions

Bioavailability in soils

The consumption of locally-produced vegetables by humans may be an important exposure pathway for soil contaminants in many urban settings and for agricultural land use. Hence, prediction of metal and metalloid uptake by vegetables from contaminated soils is an important part of the Human Health Risk Assessment procedure. The behaviour of metals (cadmium, chromium, cobalt, copper, mercury, molybdenum, nickel, lead and zinc) and metalloids (arsenic, boron and selenium) in contaminated soils depends to a large extent on the intrinsic charge, valence and speciation of the contaminant ion, and soil properties such as pH, redox status and contents of clay and/or organic matter. However, chemistry and behaviour of the contaminant in soil alone cannot predict soil-to-plant transfer. Root uptake, root selectivity, ion interactions, rhizosphere processes, leaf uptake from the atmosphere, and plant partitioning are important processes that ultimately govern the accumulation ofmetals and metalloids in edible vegetable tissues. Mechanistic models to accurately describe all these processes have not yet been developed, let alone validated under field conditions. Hence, to estimate risks by vegetable consumption, empirical models have been used to correlate concentrations of metals and metalloids in contaminated soils, soil physico-chemical characteristics, and concentrations of elements in vegetable tissues. These models should only be used within the bounds of their calibration, and often need to be re-calibrated or validated using local soil and environmental conditions on a regional or site-specific basis.Mike J. McLaughlin, Erik Smolders, Fien Degryse, and Rene Rietr

Comparison of experimental and simulated K alpha yield for 400 nm ultrashort pulse laser irradiation

Ti K alpha emission yields from foils irradiated with similar to 45 fs, p-polarized pulses of a frequency-doubled Ti:sapphire laser are presented. A simple model invoking vacuum heating to predict absorption and hot electron temperature was coupled with the cross section for K-shell ionization of Ti and the Bethe-Bloch stopping power equation for electrons. The peak predicted K alpha emission was in generally good agreement with experiment. This contrasts strongly with previous work at the fundamental frequency. Similar predictions using particle-in-cell (PIC) code simulation to estimate the number and temperature of hot electrons also gave good agreement for yield

Evaluating the effects of information reliability on travellers’ route choice

This paper analyses travellers' behaviour with respect to route choice in a context where an Advanced Traveller Information System (ATIS) is in place. ATIS are important applications in the field of intelligent transportation systems (ITS). However, the practical impact of ATIS is still a matter for debate, and identification of expected route choice behaviour under ATIS is one of the main ways to assess their practical importance. Travellers' choices are frequently explored by means of stated preference (SP) approaches. In this paper we discuss some issues to be addressed when an SP survey is carried out, with particular reference to cases where a repeated choice approach is employed in the survey. Our analysis concerns an application of the SP approach in a pilot study aimed at identifying the effects of ATIS accuracy on travellers’ compliance with information. This paper aims to make two major contributions. First of all, empirical analyses based on proper indicators and statistical tests are suggested in order to evaluate how the collected data have to be handled in order to eliminate transient route-choice observations. These are due to the warm-up phase inherently associated with the survey method adopted, dealing with repeated choices. Secondly, we analyse (stationary) route choice in order to assess the effects of information reliability (and the kind of information) on both route choice and compliance