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.

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.

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.

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.

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.

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.

Moose-vehicle collisions (MVC) in the State of Maine from 1992-2004

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ESTIMATED NUMBER AND LOCATION OF FUTURE MOOSE-VEHICLE COLLISIONS (MVC) IN MAINE

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Estimated Number and Location of Future Moose-Vehicle Collisions (MVC) in Maine

Moose (Alces alces) are a keystone herbivore in Maine. Because of the large number of rural roads in Maine, there is a high rate of moose-vehicle collisions (MVCs), which is increasing. On-road encounters with animals resulted in 231 fatalities in the United States in 1999. Because of the fatality of MVCs, it is important to know where they are most likely to occur. I used GIS analysis to estimate where future MVCs would occur, factoring in the variables of land cover suitability for moose, distance from water bodies, locations of past MVCs, and speed limits on the roads. I ran four different analyses, each one weighting the variables equally. I also ran a regression to determine if increasing road speed was associated with the increase in the number of MVCs per length of road. There was not a strong positive relationship between the number of MVCs per length of road and the speed limit, but it was interesting to note that there were more MVCs per length of road on 35mph and 40mph roads than on 45, 50, 55 or 65mph roads. Future research on MVCs would benefit from the inclusion of include moose population density and road traffic data.

Avaliação da genotoxicidade induzida por emissões de veículos automotores - Ctenomys minutus como organismo bioindicador

Existe um número crescente de componentes químicos lançados ao meio ambiente, muitos dos quais são capazes de induzir efeitos danosos adversos à saúde de animais e humanos, representando uma causa importante de preocupação por seus possíveis efeitos a longo prazo. O impacto ecológico e os riscos a saúde dos organismos associados com a exposição a poluentes ambientais são extremamente difíceis de se avaliar devido a muitos desses componentes serem parte de misturas complexas. Os gases produzidos pelos motores dos veículos à combustão contém diversos poluentes sabidamente genotóxicos, como óxidos de nitrogênio (NOX), monóxido de carbono (CO), óxidos de enxofre (SOx), hidrocarbonetos (HC) e seus derivados, bem como particulados, e metais (cádmio, cromo, cobre, níquel, vanádio, zinco e chumbo). Todos esses compostos isolados ou associados a outros elementos são tóxicos ou de efeito danoso aos organismos, de forma não totalmente esclarecida. Este estudo teve como objetivo verificar o possível efeito genotóxico das emissões dos automóveis em roedor nativo Ctenomys minutus cronicamente exposto, através do Ensaio Cometa (EC), comparando os resultados com o Teste de Micronúcleos (MN), ambos em sangue periférico. Levando em consideração alguns fatores que pudessem influenciar os resultados dos testes de genotoxicidade, este trabalho ainda teve como objetivos: identificar a presença de alguns agentes envolvidos na poluição gerada pelos veículos; verificar possíveis diferenças sazonais, como temperatura e ventos; e se existe influência da idade e sexo dos roedores. Os C. minutus (Octodontidae-Rodentia), foram capturados em dois campos diferentes, ambos ao lado da estrada RS/030, na cidade de Osório, Estado do Rio Grande do Sul (RS): (a) Amaral, e (b) Weber. Animais para controle externo foram capturados no Campo Maribo à cerca de 3 km de distância de outra estrada (RS/389-Osório/RS), conseqüentemente afastada das emissões dos veículos. No final do período desse estudo, foram capturados 123 animais (73 fêmeas e 50 machos).

Aerial line transect survey to estimate abundance of marsh deer (Blastocerus dichotomus) (Illiger, 1815)

A população de cervo-do-pantanal (Blastocerus dichotomus) está drasticamente reduzida no Brasil. O nosso objetivo foi o de estimar a abundância do cervo-do-pantanal na bacia do Rio Paraná e discutir a metodologia aplicada. Os resultados darão suporte para uma análise do impacto do enchimento da represa de Porto Primavera sobre essa população. Sessenta e nove animais foram registrados através de sobrevôo utilizando-se a metodologia de transecção linear com amostragem das distâncias. Os dados não corrigidos resultaram em uma densidade estimada de 0,0035ind/ha e uma população de 636 indivíduos. A correção de g para os animais que não foram vistos apresentou uma densidade de 0,0049 ind/ha e uma abundância de 896 (CV=0,27) indivíduos. A metodologia foi aplicada com sucesso na estimativa de cervo-do-pantanal. Esse resultado é importante para avaliarmos a população do cervo-do-pantanal na área e para futuramente analisarmos o impacto do enchimento da represa.

Anti-leishmanial effects of purified compounds from aerial parts of Baccharis uncinella C. DC. (Asteraceae)

Species of Baccharis exhibit antibiotic, antiseptic, wound-healing, and anti-protozoal properties, and have been used in the traditional medicine of South America for the treatment of several diseases. In the present work, the fractionation of EtOH extract from aerial parts of Baccharis uncinella indicated that the isolated compounds caffeic acid and pectolinaringenin showed inhibitory activity against Leishmania (L.) amazonensis and Leishmania (V.) braziliensis promastigotes, respectively. Moreover, amastigote forms of both species were highly sensible to the fraction composed by oleanolic + ursolic acids and pectolinaringenin. Caffeic acid also inhibited amastigote forms of L. (L.) amazonensis, but this effect was weak in L. (V.) braziliensis amastigotes. The treatment of infected macrophages with these compounds did not alter the levels of nitrates, indicating a direct effect of the compounds on amastigote stages. The results presented herein suggest that the active components from B. uncinella can be important to the design of new drugs against American tegumentar leishmaniases.

Evaluation of anti-inflammatory activity of derivatives from aerial parts of Baccharis uncinella

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The breathing pattern and the ventilatory response to aquatic and aerial hypoxia and hypercarbia in the frog Pipa carvalhoi

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Systems of aerial spraying for soybean rust control

A ferrugem asiática da soja, causada pelo fungo Phakopsora pachyrhizi, é considerada a principal doença da soja, e, portanto, a escolha e o uso adequado dos equipamentos de pulverização são essenciais para seu controle. O objetivo deste trabalho foi avaliar o desempenho de diferentes equipamentos de pulverização aérea para o controle curativo da ferrugem da soja, utilizando o fungicida Impact 125 SC (flutriafol) a 0,5 L p c ha-1. Os seguintes tratamentos foram avaliados: atomizador Micronair AU 5000 (10 L ha-1 com óleo e 20 L ha-1 sem óleo na calda); atomizador Stol ARD (10 e 20 L ha-1 ambos com óleo) e o sistema eletrostático Spectrum (10 L ha-1 sem óleo a 64 e 71% de umidade relativa). Utilizou-se óleo de algodão (1,0 L ha-1) acrescido de emulsificante BR 455 a 0,025 L ha-1. O ensaio foi realizado na terceira aplicação de fungicidas, quando foram analisadas quatro repetições nas áreas aplicadas e quatro testemunhas não aplicadas para cada tratamento, avaliando-se a severidade da ferrugem, os depósitos de flutriafol nas folhas de soja e o percentual de redução de ferrugem. A análise dos depósitos nas folhas mostrou que não houve diferenças significativas entre os tratamentos. Os melhores controles da ferrugem foram obtidos com os tratamentos Micronair (10 L ha-1 com óleo), Stol (20 L ha-1 com óleo) e o sistema elestrostático (10 L ha-1) com a menor umidade relativa do ar (64 %).