The Optimal trigger speed of vehicle activated signs

The thesis aims to elaborate on the optimum trigger speed for Vehicle Activated Signs (VAS) and to study the effectiveness of VAS trigger speed on drivers’ behaviour. Vehicle activated signs (VAS) are speed warning signs that are activated by individual vehicle when the driver exceeds a speed threshold. The threshold, which triggers the VAS, is commonly based on a driver speed, and accordingly, is called a trigger speed. At present, the trigger speed activating the VAS is usually set to a constant value and does not consider the fact that an optimal trigger speed might exist. The optimal trigger speed significantly impacts driver behaviour. In order to be able to fulfil the aims of this thesis, systematic vehicle speed data were collected from field experiments that utilized Doppler radar. Further calibration methods for the radar used in the experiment have been developed and evaluated to provide accurate data for the experiment. The calibration method was bidirectional; consisting of data cleaning and data reconstruction. The data cleaning calibration had a superior performance than the calibration based on the reconstructed data. To study the effectiveness of trigger speed on driver behaviour, the collected data were analysed by both descriptive and inferential statistics. Both descriptive and inferential statistics showed that the change in trigger speed had an effect on vehicle mean speed and on vehicle standard deviation of the mean speed. When the trigger speed was set near the speed limit, the standard deviation was high. Therefore, the choice of trigger speed cannot be based solely on the speed limit at the proposed VAS location. The optimal trigger speeds for VAS were not considered in previous studies. As well, the relationship between the trigger value and its consequences under different conditions were not clearly stated. The finding from this thesis is that the optimal trigger speed should be primarily based on lowering the standard deviation rather than lowering the mean speed of vehicles. Furthermore, the optimal trigger speed should be set near the 85th percentile speed, with the goal of lowering the standard deviation.

A data driven approach for automating vehicle activated signs

Vehicle activated signs (VAS) display a warning message when drivers exceed a particular threshold. VAS are often installed on local roads to display a warning message depending on the speed of the approaching vehicles. VAS are usually powered by electricity; however, battery and solar powered VAS are also commonplace. This thesis investigated devel-opment of an automatic trigger speed of vehicle activated signs in order to influence driver behaviour, the effect of which has been measured in terms of reduced mean speed and low standard deviation. A comprehen-sive understanding of the effectiveness of the trigger speed of the VAS on driver behaviour was established by systematically collecting data. Specif-ically, data on time of day, speed, length and direction of the vehicle have been collected for the purpose, using Doppler radar installed at the road. A data driven calibration method for the radar used in the experiment has also been developed and evaluated. Results indicate that trigger speed of the VAS had variable effect on driv-ers’ speed at different sites and at different times of the day. It is evident that the optimal trigger speed should be set near the 85th percentile speed, to be able to lower the standard deviation. In the case of battery and solar powered VAS, trigger speeds between the 50th and 85th per-centile offered the best compromise between safety and power consump-tion. Results also indicate that different classes of vehicles report differ-ences in mean speed and standard deviation; on a highway, the mean speed of cars differs slightly from the mean speed of trucks, whereas a significant difference was observed between the classes of vehicles on lo-cal roads. A differential trigger speed was therefore investigated for the sake of completion. A data driven approach using Random forest was found to be appropriate in predicting trigger speeds respective to types of vehicles and traffic conditions. The fact that the predicted trigger speed was found to be consistently around the 85th percentile speed justifies the choice of the automatic model.

Data based Calibration System for Radar used by Vehicle Activated Signs

The accurate measurement of a vehicle’s velocity is an essential feature in adaptive vehicle activated sign systems. Since the velocities of the vehicles are acquired from a continuous wave Doppler radar, the data collection becomes challenging. Data accuracy is sensitive to the calibration of the radar on the road. However, clear methodologies for in-field calibration have not been carefully established. The signs are often installed by subjective judgment which results in measurement errors. This paper develops a calibration method based on mining the data collected and matching individual vehicles travelling between two radars. The data was cleaned and prepared in two ways: cleaning and reconstructing. The results showed that the proposed correction factor derived from the cleaned data corresponded well with the experimental factor done on site. In addition, this proposed factor showed superior performance to the one derived from the reconstructed data.

Speed prediction for triggering vehicle activated signs

Accurate speed prediction is a crucial step in the development of a dynamic vehcile activated sign (VAS). A previous study showed that the optimal trigger speed of such signs will need to be pre-determined according to the nature of the site and to the traffic conditions. The objective of this paper is to find an accurate predictive model based on historical traffic speed data to derive the optimal trigger speed for such signs. Adaptive neuro fuzzy (ANFIS), classification and regression tree (CART) and random forest (RF) were developed to predict one step ahead speed during all times of the day. The developed models were evaluated and compared to the results obtained from artificial neural network (ANN), multiple linear regression (MLR) and naïve prediction using traffic speed data collected at four sites located in Sweden. The data were aggregated into two periods, a short term period (5-min) and a long term period (1-hour). The results of this study showed that using RF is a promising method for predicting mean speed in the two proposed periods.. It is concluded that in terms of performance and computational complexity, a simplistic input features to the predicitive model gave a marked increase in the response time of the model whilse still delivering a low prediction error.

Review of the effectiveness of vehicle activated signs

This paper reviews the effectiveness of vehicle activated signs. Vehicle activated signs are being reportedly used in recent years to display dynamic information to road users on an individual basis in order to give a warning or inform about a specific event. Vehicle activated signs are triggered individually by vehicles when a certain criteria is met. An example of such criteria is to trigger a speed limit sign when the driver exceeds a pre-set threshold speed. The preset threshold is usually set to a constant value which is often equal, or relative, to the speed limit on a particular road segment. This review examines in detail the basis for the configuration of the existing sign types in previous studies and explores the relation between the configuration of the sign and their impact on driver behavior and sign efficiency. Most of previous studies showed that these signs have significant impact on driver behavior, traffic safety and traffic efficiency. In most cases the signs deployed have yielded reductions in mean speeds, in speed variation and in longer headways. However most experiments reported within the area were performed with the signs set to a certain static configuration within applicable conditions. Since some of the aforementioned factors are dynamic in nature, it is felt that the configurations of these signs were thus not carefully considered by previous researchers and there is no clear statement in the previous studies describing the relationship between the trigger value and its consequences under different conditions. Bearing in mind that different designs of vehicle activated signs can give a different impact under certain conditions of road, traffic and weather conditions the current work suggests that variable speed thresholds should be considered instead.

Triggering Solar-Powered Vehicle Activated Signs using Self Organising Maps with K-means

Solar-powered vehicle activated signs (VAS) are speed warning signs powered by batteries that are recharged by solar panels. These signs are more desirable than other active warning signs due to the low cost of installation and the minimal maintenance requirements. However, one problem that can affect a solar-powered VAS is the limited power capacity available to keep the sign operational. In order to be able to operate the sign more efficiently, it is proposed that the sign be appropriately triggered by taking into account the prevalent conditions. Triggering the sign depends on many factors such as the prevailing speed limit, road geometry, traffic behaviour, the weather and the number of hours of daylight. The main goal of this paper is therefore to develop an intelligent algorithm that would help optimize the trigger point to achieve the best compromise between speed reduction and power consumption. Data have been systematically collected whereby vehicle speed data were gathered whilst varying the value of the trigger speed threshold. A two stage algorithm is then utilized to extract the trigger speed value. Initially the algorithm employs a Self-Organising Map (SOM), to effectively visualize and explore the properties of the data that is then clustered in the second stage using K-means clustering method. Preliminary results achieved in the study indicate that using a SOM in conjunction with K-means method is found to perform well as opposed to direct clustering of the data by K-means alone. Using a SOM in the current case helped the algorithm determine the number of clusters in the data set, which is a frequent problem in data clustering.

Accident analysis - breakaway and nonbreakaway poles including sign and light standards along highways.

National Highway Traffic Safety Administration, Washington, D.C.

Accident analysis - breakaway and nonbreakaway poles including sign and light standards along highways.

National Highway Traffic Safety Administration, Washington, D.C.

Aeroelastic effects in a traffic sign panel induced by a passing vehicle

Here, a simple theoretical model of the vehicle induced flow and its effects on traffic sign panels is presented. The model is a continuation of a previous one by Sanz-Andrés and coworkers, now including the flexibility of the panel (and, therefore, the flow effects associated to the motion of the panel). Through the paper an aeroelastic one-degree-of-freedom model is developed and the flow effects are computed from unsteady potential theory. The influence of panel's mechanical properties (mass, damping ratio, and stiffness) in the motion induced forces are numerically analyzed.

Vehicle-induced loads on traffic sign panels

The determination of the loads on traffic sign panels in the current standards does not, in general, take into account the vehicle-induced loads, as explained by Quinn, Baker and Wright (QBW in what follows) (J. Wind Eng. Ind. Aerodyn. 89 (2001) 831). On the other hand, a report from Cali and Covert (CC) (J. Wind Eng. Ind. Aerodyn. 84 (2000) 87) indicates that in highway sign support structures, vehicle-induced loads have led to premature failures in some cases. The aim of this paper is to present a mathematical model for the vehicle-induced load on a flat sign panel, simple enough to give analytical results, but able to explain the main characteristics of the phenomenon. The results of the theoretical model help to explain the behaviour observed in the experiments performed in previous studies.

In vitro and in vivo studies on protease-activated receptor-2

Protease-activated receptor-2 (PAR2) is a G protein coupled receptor (GPCR) that is activated by proteolytic cleavage of its amino terminal domain by trypsin-like serine proteases. Cleavage of this receptor exposes a neoepitope, termed the tethered ligand (TL), which binds intramolecularly within the receptor to stimulate signal transduction via coupled G proteins. PAR2-mediated signal transduction is also experimentally stimulated by hexapeptides (agonist peptides; APs) that are homologous to the TL sequence. Due to the irreversible nature of PAR2 proteolysis, downstream signal transduction is tightly regulated. Following activation, PAR2 is rapidly uncoupled from downstream signalling by the post-translational modifications phosphorylation and ubiquination which facilitate interactions with â- arrestin. This scaffolding protein couples PAR2 to the internalisation machinery initiating its desensitisation and trafficking through the early and late endosomes followed by receptor degradation. PAR2 is widely expressed in mammalian tissues with key roles for this receptor in cardiovascular, respiratory, nervous and musculoskeletal systems. This receptor has also been linked to pathological states with aberrant expression and signalling noted in several cancers. In prostate cancer, PAR2 signalling induces migration and proliferation of tumour derived cell lines, while elevated receptor expression has been noted in malignant tissues. Importantly, a role for this receptor has also been suggested in prostate cancer bone metastasis as coexpression of PAR2 and a proteolytic activator has been demonstrated by immunohistochemical analysis. Based on these data, the primary focus of this project has been on two aspects of PAR2 biology. The first is characterisation of cellular mechanisms that regulate PAR2 signalling and trafficking. The second aspect is the role of this receptor in prostate cancer bone metastasis. In addition, to permit these studies, it was first necessary to evaluate the specificity of the commercially available anti-PAR2 antibodies SAM11, C17, N19 and H99. The evaluation of the four commercially available antibodies was assessed using four techniques: immunoprecipitation; Western blot analysis; immunofluorescence; and flow cytometry. These approaches demonstrated that three of the antibodies efficiently detect ectopically expressed PAR2 by each of these techniques. A significant finding from this study was that N19 was the only antibody able to specifically detect N-glycosylated endogenous PAR2 by Western blot analysis. This analysis was performed on lysates from prostate cancer derived cell lines and tissue derived from wildtype and PAR2 knockout mice. Importantly, further evaluation demonstrated that this antibody also efficiently detects endogenous PAR2 at the cell surface by flow cytometry. The anti-PAR2 antibody N19 was used to explore the in vitro role of palmitoylation, the post-translational addition of palmitate, in PAR2 signalling, trafficking, cell surface expression and desensitization. Significantly, use of the palmitoylation inhibitor 2-bromopalmitate indicated that palmitate addition is important in trafficking of PAR2 endogenously expressed by prostate cancer cell lines. This was supported by palmitate labelling experiments using two approaches which showed that PAR2 stably expressed by CHO cells is palmitoylated and that palmitoylation occurs on cysteine 361. Another key finding from this study is that palmitoylation is required for optimal PAR2 signalling as Ca2+ flux assays indicated that in response to trypsin agonism, palmitoylation deficient PAR2 is ~9 fold less potent than wildtype receptor with a reduction of about 33% in the maximum signal induced via the mutant receptor. Confocal microscopy, flow cytometry and cell surface biotinylation analyses demonstrated that palmitoylation is required for efficient cell surface expression of PAR2. Importantly, this study also identified that palmitoylation of this receptor within the Golgi apparatus is required for efficient agonist-induced rab11amediated trafficking of PAR2 to the cell surface. Interestingly, palmitoylation is also required for receptor desensitization, as agonist-induced â-arrestin recruitment and receptor degradation were markedly reduced in CHO-PAR2-C361A cells compared with CHO-PAR2 cells. Collectively, these data provide new insights on the life cycle of PAR2 and demonstrate that palmitoylation is critical for efficient signalling, trafficking, cell surface localization and degradation of this receptor. This project also evaluated PAR2 residues involved in ligand docking. Although the extracellular loop (ECL)2 of PAR2 is known to be required for agonist-induced signal transduction, the binding pocket for receptor agonists remains to be determined. In silico homology modelling, based on a crystal structure for the prototypical GPCR rhodopsin, and ligand docking were performed to identify PAR2 transmembrane (TM) amino acids potentially involved in agonist binding. These methods identified 12 candidate residues that were mutated to examine the binding site of the PAR2 TL, revealed by trypsin cleavage, as well as of the soluble ligands 2f-LIGRLO-NH2 and GB110, which are both structurally based on the AP SLIGRLNH2. Ligand binding was evaluated from the impact of the mutated residues on PAR2-mediated calcium mobilisation. An important finding from these experiments was that mutation of residues Y156 and Y326 significantly reduced 2f-LIGRLO-NH2 and GB110 agonist activity. L307 was also important for GB110 activity. Intriguingly, mutation of PAR2 residues did not alter trypsin-induced signalling to the same extent as for the soluble agonists. The reason for this difference remains to be further examined by in silico and in vitro experimentation and, potentially, crystal structure studies. However, these findings identified the importance of TM domains in PAR2 ligand docking and will enhance the design of both PAR2 agonists and potentially agents to inhibit signalling (antagonists). The potential importance of PAR2 in prostate cancer bone metastasis was examined using a mouse model. In patients, prostate cancer bone metastases cause bone growth by disrupting bone homeostasis. In an attempt to mimic prostate cancer growth in bone, PAR2 responsive 22Rv1 prostate cancer cells, which form mixed osteoblastic and osteolytic lesions, were injected into the proximal aspect of mouse tibiae. A role for PAR2 was assessed by treating these mice with the recently developed PAR2 antagonist GB88. As controls, animals bearing intra-tibial tumours were also treated with vehicle (olive oil) or the prostate cancer chemotherapeutic docetaxel. The effect of these treatments on bone was examined radiographically and by micro-CT. Consistent with previous studies, 22Rv1 tumours caused osteoblastic periosteal spicule formation and concurrent osteolytic bone loss. Significantly, blockade of PAR2 signalling reduced the osteoblastic and osteolytic phenotype of 22Rv1 tumours in bone. No bone defects were detected in mice treated with docetaxel. These qualitative data will be followed in the future by quantitative micro-CT analysis as well as histology and histomorphometry analysis of already collected tissues. Nonetheless, these preliminary experiments highlight a potential role for PAR2 in prostate cancer growth in bone. In summary, in vitro studies have defined mechanisms regulating PAR2 activation, downstream signalling and trafficking and in vivo studies point to a potential role for this receptor in prostate cancer bone metastasis. The outcomes of this project are that a greater understanding of the biology of PAR2 may lead to the development of strategies to modulate the function of this receptor in disease.

Driving simulator evaluation of the failure of an audio in-vehicle warning for railway level crossings

It is impracticable to upgrade the 18,900 Australian passive crossings as such crossings are often located in remote areas, where power is lacking and with low road and rail traffic. The rail industry is interested in developing innovative in-vehicle technology interventions to warn motorists of approaching trains directly in their vehicles. The objective of this study was therefore to evaluate the benefits of the introduction of such technology. We evaluated the changes in driver performance once the technology is enabled and functioning correctly, as well as the effects of an unsafe failure of the technology? We conducted a driving simulator study where participants (N=15) were familiarised with an in-vehicle audio warning for an extended period. After being familiarised with the system, the technology started failing, and we tested the reaction of drivers with a train approaching. This study has shown that with the traditional passive crossings with RX2 signage, the majority of drivers complied (70%) and looked for trains on both sides of the rail track. With the introduction of the in-vehicle audio message, drivers did not approach crossings faster, did not reduce their safety margins and did not reduce their gaze towards the rail tracks. However participants’ compliance at the stop sign decreased by 16.5% with the technology installed in the vehicle. The effect of the failure of the in-vehicle audio warning technology showed that most participants did not experience difficulties in detecting the approaching train even though they did not receive any warning message. This showed that participants were still actively looking for trains with the system in their vehicle. However, two participants did not stop and one decided to beat the train when they did not receive the audio message, suggesting potential human factors issues to be considered with such technology.

Traffic and Road Sign Recognition

This thesis presents a system to recognise and classify road and traffic signs for the purpose of developing an inventory of them which could assist the highway engineers’ tasks of updating and maintaining them. It uses images taken by a camera from a moving vehicle. The system is based on three major stages: colour segmentation, recognition, and classification. Four colour segmentation algorithms are developed and tested. They are a shadow and highlight invariant, a dynamic threshold, a modification of de la Escalera’s algorithm and a Fuzzy colour segmentation algorithm. All algorithms are tested using hundreds of images and the shadow-highlight invariant algorithm is eventually chosen as the best performer. This is because it is immune to shadows and highlights. It is also robust as it was tested in different lighting conditions, weather conditions, and times of the day. Approximately 97% successful segmentation rate was achieved using this algorithm.Recognition of traffic signs is carried out using a fuzzy shape recogniser. Based on four shape measures - the rectangularity, triangularity, ellipticity, and octagonality, fuzzy rules were developed to determine the shape of the sign. Among these shape measures octangonality has been introduced in this research. The final decision of the recogniser is based on the combination of both the colour and shape of the sign. The recogniser was tested in a variety of testing conditions giving an overall performance of approximately 88%.Classification was undertaken using a Support Vector Machine (SVM) classifier. The classification is carried out in two stages: rim’s shape classification followed by the classification of interior of the sign. The classifier was trained and tested using binary images in addition to five different types of moments which are Geometric moments, Zernike moments, Legendre moments, Orthogonal Fourier-Mellin Moments, and Binary Haar features. The performance of the SVM was tested using different features, kernels, SVM types, SVM parameters, and moment’s orders. The average classification rate achieved is about 97%. Binary images show the best testing results followed by Legendre moments. Linear kernel gives the best testing results followed by RBF. C-SVM shows very good performance, but ?-SVM gives better results in some case.

Intracellular mechanisms of hydroquinone toxicity on endotoxin-activated neutrophils

Circulating neutrophils promptly react to different substances in the blood and orchestrate the beginning of the innate inflammatory response. We have shown that in vivo exposure to hydroquinone (HQ), the most oxidative compound of cigarette smoke and a toxic benzene metabolite, affects circulating neutrophils, making them unresponsive to a subsequent bacterial infection. In order to understand the action of toxic molecular mechanisms on neutrophil functions, in vitro HQ actions on pro-inflammatory mediator secretions evoked by Escherichia coli lipopolysaccharide (LPS) were investigated. Neutrophils from male Wistar rats were cultured with vehicle or HQ (5 or 10 mu M; 2 h) and subsequently incubated with LPS (5 mu g/ml; 18 h). Hydroquinone treatment impaired LPS-induced nitric oxide (NO), tumour necrosis factor alpha (TNF-alpha), interleukin (IL)-1 beta and IL-6 secretions by neutrophils. The toxic effect was not dependent on cell death, reduced expression of the LPS receptor or toll-like receptor-4 (TLR-4) or cell priming, as HQ did not induce reactive oxygen species generation or beta(2)integrin membrane expression. The action of toxic mechanisms on cytokine secretion was dependent on reduced gene synthesis, which may be due to decreased nuclear factor kappa B (NF-kappa B) nuclear translocation. Conversely, this intracellular pathway was not involved in impaired NO production because HQ treatments only affected inducible nitric oxide synthase protein expression and activity, suggesting posttranscriptional and/or posttranslational mechanisms of action. Altogether, our data show that HQ alters the action of different LPS-activated pathways on neutrophils, which may contribute to the impaired triggering of the host innate immune reaction detected during in vivo HQ exposure.

Migration of immature mouse DC across resting endothelium is mediated by ICAM-2 but independent of beta2-integrins and murine DC-SIGN homologues

Immature dendritic cells (DC) reside in tissues where they initiate immune responses by taking up foreign antigens. Since DC have a limited tissue half-life, the DC pool in tissues has to be replenished constantly. This implies that precursor/immature DC must be able to cross non-activated endothelium using as yet unknown mechanisms. Here we show that immature, but not mature bone marrow-derived murine DC migrate across resting endothelial monolayers in vitro. We find that endothelial intercellular adhesion molecule-2 (ICAM-2) is a major player in transendothelial migration (TEM) of immature DC, accounting for at least 41% of TEM. Surprisingly, the ICAM-2-mediated TEM was independent of beta2-integrins, the known ICAM-2 ligands, since neither blocking of beta2-integrins with antibodies nor the use of CD18-deficient DC affected the ICAM-2-specific TEM. In humans, the C-type lectin DC-specific ICAM-3-grabbing nonintegrin (DC-SIGN) was shown to interact with ICAM-2, suggesting a similar role in mice. However, we find that none of the murine DC-SIGN homologues mDC-SIGN, murine DC-SIGN-related molecule-1 (mSIGN-R1) and mSIGN-R3 is expressed on the surface of bone marrow-derived mouse DC. Taken together, this study shows that ICAM-2 strongly supports transmigration of immature DC across resting endothelium by interacting with ligands that are distinct from beta2-integrins and DC-SIGN homologues.