This page has only limited features, please log in for full access.
Francisco Soares has a master’s degree in Civil Engineering by the University of Minho, Guimarães, Portugal. He is currently developing his PhD thesis titled “Risk factors affecting pedestrian behaviour: Risk assessment in virtual environment”. In the last few years, he developed scientific research on pedestrian safety focused on pedestrian-vehicle interaction.
This paper identifies and analyzes variables that influence pedestrian safety based on the definition of models of pedestrian crash frequency for urban areas in Portugal. It considers three groups of explanatory variables, namely: (i) built environment; (ii) pedestrian infrastructure, and (iii) road infrastructure, as well as exposure variables combining pedestrian and vehicular traffic volumes. Data on the 16 variables considered were gathered from locations in the counties of Braga and Guimarães. The inclusion of pedestrian infrastructure variables in studies of this type is an innovation that allows for measuring the impacts of the dimensions recommended for this type of infrastructure and assessing the implementation of policies to support the mobility of vulnerable users, especially pedestrians. Examples of such variables are unobstructed space for pedestrian mobility and the recommendable distance separating regulated crossings. Zero-Truncated Negative Binomial Regression Models (ZTNB) and Generalized Estimation Equations (GEE) are used to develop crash prediction models. Results show that in addition to the variables identified in similar studies such as carriageway width, other statistically significant variables like longitudinal slope and distance between crosswalks have a negative influence on pedestrian safety. On-street parking places, one-way streets, and the existence of raised medians have an opposite contribution to safety.
Leidy Barón; Jocilene Otila da Costa; Francisco Soares; Susana Faria; Maria Prudêncio Jacques; Elisabete Fraga de Freitas. Effect of Built Environment Factors on Pedestrian Safety in Portuguese Urban Areas. Applied System Innovation 2021, 4, 28 .
AMA StyleLeidy Barón, Jocilene Otila da Costa, Francisco Soares, Susana Faria, Maria Prudêncio Jacques, Elisabete Fraga de Freitas. Effect of Built Environment Factors on Pedestrian Safety in Portuguese Urban Areas. Applied System Innovation. 2021; 4 (2):28.
Chicago/Turabian StyleLeidy Barón; Jocilene Otila da Costa; Francisco Soares; Susana Faria; Maria Prudêncio Jacques; Elisabete Fraga de Freitas. 2021. "Effect of Built Environment Factors on Pedestrian Safety in Portuguese Urban Areas." Applied System Innovation 4, no. 2: 28.
When crossing a road, pedestrians must detect traffic, combine data coming from different perceptual modalities, evaluate the time envelope for safely cross the street, and monitor the position of oncoming vehicles to perform corrective actions if needed. This study analyzed the influence of noise emitted by vehicles, or its absence, on pedestrians’ crossing decision-making. Experiments were performed in a virtual environment using two road scenarios. Participants were presented with stimuli of approaching vehicles that varied regarding speed, movement patterns, and auditory condition: one concerning the approaching of an electric vehicle, another regarding the approaching of a gasoline combustion vehicle, and, finally, a condition regarding the absence of auditory cues. Participants were tasked with indicating the moment when they decided to cross the street. The results show that, despite the noise variations caused by the type of vehicle and its speed pattern, the participants’ decision to cross was mostly based on vehicle distance. When a vehicle approaches the crosswalk from a short distance and with no occlusion to the pedestrian’s visibility, the sound does not seem to influence the pedestrians’ crossing decision-making.
Francisco Soares; Emanuel Silva; Frederico Pereira; Carlos César Loureiro Silva; Emanuel Sousa; Elisabete Freitas. The Influence of Noise Emitted by Vehicles on Pedestrian Crossing Decision-Making: A Study in a Virtual Environment. Applied Sciences 2020, 10, 2913 .
AMA StyleFrancisco Soares, Emanuel Silva, Frederico Pereira, Carlos César Loureiro Silva, Emanuel Sousa, Elisabete Freitas. The Influence of Noise Emitted by Vehicles on Pedestrian Crossing Decision-Making: A Study in a Virtual Environment. Applied Sciences. 2020; 10 (8):2913.
Chicago/Turabian StyleFrancisco Soares; Emanuel Silva; Frederico Pereira; Carlos César Loureiro Silva; Emanuel Sousa; Elisabete Freitas. 2020. "The Influence of Noise Emitted by Vehicles on Pedestrian Crossing Decision-Making: A Study in a Virtual Environment." Applied Sciences 10, no. 8: 2913.
The negative impact of noise on human health is well established and a high percentage of environmental noise is related with traffic sources. In this study, we compared annoyance judgments of real and virtual traffic sounds. Virtual sounds were generated through an auralization software with input from close proximity tyre/road noise measurements and real sounds were recorded through a Head and Torso Simulator. Both groups had sounds generated at two speeds and from three urban pavement surfaces (asphalt concrete, concrete blocks and granite cubes). Under controlled laboratory conditions, participants rated the annoyance of each real and virtual stimulus. It was found that virtual stimuli, based on close proximity tyre/road noise, can be used to assess traffic annoyance, in spite of systematic lower rates than those found for real stimuli. The effects of type of pavement and speed were the same for both conditions (real and virtualized stimulus). Opposed to granite cubes, asphalt concrete had lower annoyance rates for both test speeds and higher rate differences between real and virtual stimuli. Additionally, it was also found that annoyance is better described by Loudness than by LAmax. This evidence is stronger for the virtual stimuli condition than for the real stimuli one. Nevertheless, we should stress that it is possible to accurately predict real annoyance rates from virtual auralized sound samples through a simple transformation model. The methodology developed is clearly efficient and significantly simplifies field procedures, allowing the reduction of experimental costs, a better control of variables and an increment on the accuracy of annoyance ratings.This work was financed by FEDER grants through the Operational Competitiveness Program – COMPETE and ON.2 – Novo Norte (Programa Operacional Regional do Norte 2007/2013) integrated in the structural funds QREN and the project PEst-OE/ECI/UI4047/2014 supported by Portuguese Foundation for Science and Technology.info:eu-repo/semantics/publishedVersio
F. Soares; E. Freitas; C. Cunha; C. Silva; J. Lamas; S. Mouta; Ja. Santos. Traffic noise: Annoyance assessment of real and virtual sounds based on close proximity measurements. Transportation Research Part D: Transport and Environment 2017, 52, 399 -407.
AMA StyleF. Soares, E. Freitas, C. Cunha, C. Silva, J. Lamas, S. Mouta, Ja. Santos. Traffic noise: Annoyance assessment of real and virtual sounds based on close proximity measurements. Transportation Research Part D: Transport and Environment. 2017; 52 ():399-407.
Chicago/Turabian StyleF. Soares; E. Freitas; C. Cunha; C. Silva; J. Lamas; S. Mouta; Ja. Santos. 2017. "Traffic noise: Annoyance assessment of real and virtual sounds based on close proximity measurements." Transportation Research Part D: Transport and Environment 52, no. : 399-407.
This paper aims at developing a collision prediction model for three-leg junctions located in national roads (NR) in Northern Portugal. The focus is to identify factors that contribute for collision type crashes in those locations, mainly factors related to road geometric consistency, since literature is scarce on those, and to research the impact of three modeling methods: generalized estimating equations, random-effects negative binomial models and random-parameters negative binomial models, on the factors of those models. The database used included data published between 2008 and 2010 of 177 three-leg junctions. It was split in three groups of contributing factors which were tested sequentially for each of the adopted models: at first only traffic, then, traffic and the geometric characteristics of the junctions within their area of influence; and, lastly, factors which show the difference between the geometric characteristics of the segments boarding the junctionsâ area of influence and the segment included in that area were added. The choice of the best modeling technique was supported by the result of a cross validation made to ascertain the best model for the three sets of researched contributing factors. The models fitted with random-parameters negative binomial models had the best performance in the process. In the best models obtained for every modeling technique, the characteristics of the road environment, including proxy measures for the geometric consistency, along with traffic volume, contribute significantly to the number of collisions. Both the variables concerning junctions and the various national highway segments in their area of influence, as well as variations from those characteristics concerning roadway segments which border the already mentioned area of influence have proven their relevance and, therefore, there is a rightful need to incorporate the effect of geometric consistency in the three-leg junctions safety studies.The authors would like to thank for the financial support provided by "Fundacao para a Ciencia e a Tecnologia" (FTC), Portugal, through Doctor grant SFRH/BD/62458/2009 and project UI 4047 - 2014: PEst-OE/ECI/UI4047/2014
Jocilene Otilia da Costa; Maria Alice Prudêncio Jacques; Francisco Emanuel Cunha Soares; Elisabete Fraga Freitas. Integration of geometric consistency contributory factors in three-leg junctions collision prediction models of Portuguese two-lane national highways. Accident Analysis & Prevention 2016, 86, 59 -67.
AMA StyleJocilene Otilia da Costa, Maria Alice Prudêncio Jacques, Francisco Emanuel Cunha Soares, Elisabete Fraga Freitas. Integration of geometric consistency contributory factors in three-leg junctions collision prediction models of Portuguese two-lane national highways. Accident Analysis & Prevention. 2016; 86 ():59-67.
Chicago/Turabian StyleJocilene Otilia da Costa; Maria Alice Prudêncio Jacques; Francisco Emanuel Cunha Soares; Elisabete Fraga Freitas. 2016. "Integration of geometric consistency contributory factors in three-leg junctions collision prediction models of Portuguese two-lane national highways." Accident Analysis & Prevention 86, no. : 59-67.
The research aimed to establish tyre-road noise models by using a Data Mining approach that allowed to build a predictive model and assess the importance of the tested input variables. The data modelling took into account three learning algorithms and three metrics to define the best predictive model. The variables tested included basic properties of pavement surfaces, macrotexture, megatexture, and unevenness and, for the first time, damping. Also, the importance of those variables was measured by using a sensitivity analysis procedure. Two types of models were set: one with basic variables and another with complex variables, such as megatexture and damping, all as a function of vehicles speed. More detailed models were additionally set by the speed level. As a result, several models with very good tyre-road noise predictive capacity were achieved. The most relevant variables were Speed, Temperature, Aggregate size, Mean Profile Depth, and Damping, which had the highest importance, even though influenced by speed. Megatexture and IRI had the lowest importance. The applicability of the models developed in this work is relevant for trucks tyre-noise prediction, represented by the AVON V 4 test tyre, at the early stage of road pavements use. Therefore, the obtained models are highly useful for the design of pavements and for noise prediction by road authorities and contractors.
Elisabete Freitas; Joaquim Tinoco; Francisco Soares; Jocilene Costa; Paulo Cortez; Paulo Pereira. Modelling Tyre-Road Noise with Data Mining Techniques. Archives of Acoustics 2015, 40, 547 -560.
AMA StyleElisabete Freitas, Joaquim Tinoco, Francisco Soares, Jocilene Costa, Paulo Cortez, Paulo Pereira. Modelling Tyre-Road Noise with Data Mining Techniques. Archives of Acoustics. 2015; 40 (4):547-560.
Chicago/Turabian StyleElisabete Freitas; Joaquim Tinoco; Francisco Soares; Jocilene Costa; Paulo Cortez; Paulo Pereira. 2015. "Modelling Tyre-Road Noise with Data Mining Techniques." Archives of Acoustics 40, no. 4: 547-560.
The identification of contributory factors to crash frequencies observed in different highway facilities can aid transportation and traffic management agencies to improve road traffic safety. In spite of the strategic importance of the national Portuguese road network, there are no recent studies concerned with either the identification of contributory factors to road crashes or Crash Prediction Models (CPMs) for this type of roadway. This study presents an initial contribution to this problem by focusing on the national roads NR-14, NR-101 and NR-206, which are located in Northern region of Portugal. They are two-lane single carriageway rural roads. This study analysed the crash frequencies, Average Annual Daily Traffic (AADT) and geometric characteristics of 88 two-lane road segments. The selected segments were 200-m-long and did not cross through urbanized areas. The fixed length of 200 meters corresponds to the road length used in Portugal to define a critical point. Data regarding the annual crash frequency and the AADT were available from 1999 to 2010. Due to the high number of zero-crash records in the initial database, the data were explored to identify the best statistical modelling approach to be adopted. The Generalized Estimating Equations (GEE) procedure was applied to 10 distinctive databases formed by grouping the original data in time and space. The results show that the different observations within each road segment present an exchangeable correlation structure type. This paper also analyses the impact of the sample size on the model’s capability of identifying the contributing factors to crash frequencies. The major contributing factors identified for the two-lane highways studied were the traffic volume (expressed in AADT), lane width, vertical sinuosity, and Density of Access Points (DAP). Acceptable CPM was identified for the highways considered, which estimated the total number of crashes for 400-m-long segments for a cumulative period of two years.
Jocilene Otilia Da Costa; Alice Prudêncio Jacques Maria; Paulo Pereira; Elisabete Freitas; Francisco Emanuel Cunha Soares. Portuguese two-lane highways: modelling crash frequencies for different temporal and spatial aggregation of crash data. Transport 2015, 33, 92 -103.
AMA StyleJocilene Otilia Da Costa, Alice Prudêncio Jacques Maria, Paulo Pereira, Elisabete Freitas, Francisco Emanuel Cunha Soares. Portuguese two-lane highways: modelling crash frequencies for different temporal and spatial aggregation of crash data. Transport. 2015; 33 (1):92-103.
Chicago/Turabian StyleJocilene Otilia Da Costa; Alice Prudêncio Jacques Maria; Paulo Pereira; Elisabete Freitas; Francisco Emanuel Cunha Soares. 2015. "Portuguese two-lane highways: modelling crash frequencies for different temporal and spatial aggregation of crash data." Transport 33, no. 1: 92-103.