Thesis (M.S.) University of Missouri-Columbia, 2004. / The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file viewed on (June 29, 2006) Vita. Includes bibliographical references.

Interlocking Concrete Pavements also known as block pavements are one of the integral parts of the pavement system in Europe. The use of ICP slowly extended to other countries including North America. As the usage increased the need for more scientific research was developed which resulted in the study of ICP design and analysis methods, construction practices and materials specifications. This thesis presents a research project involving the design, construction, instrumentation, performance modeling and other field tests of eight ICP crosswalks with four different design assemblies. The research projects were constructed at the Centre for Pavement and Transportation Technology (CPATT) Test Track and at the University of Waterloo Ring Road. Each of the test sections is instrumented with structural and environmental sensors of sensors to monitor the pavement performance under heavy truck traffic, typical municipal loadings and to quantify environmental effects. A database is generated and the measured stress, strain, temperature and moisture measurements are analysed to evaluate the expected long-term performance of the structural components of ICP crosswalk designs.

Interlocking Concrete Pavements also known as block pavements are one of the integral parts of the pavement system in Europe. The use of ICP slowly extended to other countries including North America. As the usage increased the need for more scientific research was developed which resulted in the study of ICP design and analysis methods, construction practices and materials specifications. This thesis presents a research project involving the design, construction, instrumentation, performance modeling and other field tests of eight ICP crosswalks with four different design assemblies. The research projects were constructed at the Centre for Pavement and Transportation Technology (CPATT) Test Track and at the University of Waterloo Ring Road. Each of the test sections is instrumented with structural and environmental sensors of sensors to monitor the pavement performance under heavy truck traffic, typical municipal loadings and to quantify environmental effects. A database is generated and the measured stress, strain, temperature and moisture measurements are analysed to evaluate the expected long-term performance of the structural components of ICP crosswalk designs.

<p>A large number of crosswalks are indicated by pavement markings and signs but are not signal-controlled. In this study, such a location is called “semi-controlled”. In locations where such a crosswalk has moderate amounts of pedestrian and vehicle traffic, pedestrians and motorists often engage in a non-verbal “negotiation”, to determine who should proceed first. </p> <p> </p> <p>In this study, 3400 pedestrian-motorist non-verbal interactions at such semi-controlled crosswalks were recorded by video. The crosswalk locations observed during the study underwent a conversion from one-way operation in Spring 2017 to two-way operation in Spring 2018. This offered a rare opportunity to collect and analyze data for the same location under two conditions.</p> <p> </p> <p>This research explored factors that could be associated with pedestrian crossing behavior and motorist <i>likelihood of decelerating</i>. A mixed effects logit model and binary logistic regression were utilized to identify factors that influence the likelihood of pedestrian crossing under specific conditions. The complementary motorist models used generalized ordered logistic regression to identify factors that impact a driver’s <i>likelihood of decelerating</i>, which was found to be a more useful factor than <i>likelihood of yielding to pedestrian</i>. The data showed that 56.5% of drivers slowed down or stopped for pedestrians on the one-way street. This value rose to 63.9% on the same street after it had been converted to 2-way operation. Moreover, two-way operation eliminated the effects of the presence of other vehicles on driver behavior.</p> <p> </p> <p>Also investigated were factors that could influence how long a pedestrian is likely to wait at such semi-controlled crosswalks. Two types of models were proposed to correlate pedestrian waiting time with various covariates. First, survival models were developed to analyze pedestrian wait time based on the first-event analysis. Second, multi-state Markov models were introduced to correlate the dynamic process between recurrent events. Combining the first-event and recurrent events analyses addressed the drawbacks of both methods. Findings from the before-and-after study can contribute to developing operational and control strategies to improve the level of service at such unsignalized crosswalks.</p> <p> </p> <p>The results of this study can contribute to policies and/or control strategies that will improve the efficiency of semi-controlled and similar crosswalks. This type of crosswalk is common, so the benefits of well-supported strategies could be substantial. </p>

Pedestrian safety is among one of the largest concerns in the transportation profession. Many treatments have been developed and implemented to improve pedestrian safety. This current research focuses on the efficiency of in-pavement warning lights systems and involves multiple objectives. The primary objective is to evaluate the yielding rates and crosswalk usage of existing and proposed in-pavement lights systems with comparisons including before and after data through a case study approach. A secondary objective is to evaluate where drivers are looking when they approach in-pavement lights systems and develop a model to evaluate their behavior. The research described herein formulated these objectives into two research hypotheses and used statistical evaluation methodologies to provide quantitative and/or qualitative responses to the developed hypotheses. Data on pedestrian and driver behavior in the field, and the interaction between, them was collected using video camera technology in the Amherst, Massachusetts area. Data regarding drivers scan patterns during the approach to a crosswalk with in-pavement warning light system was collected using a driving simulator and an eye tracker. In total, 1,949 non-staged pedestrians and 606 staged pedestrians were observed crossing at the seven crosswalk locations in the field experiment and a total of 32 drivers participated in 576 crosswalk scenarios in the driving simulator evaluation. The field evaluation resulted in increased yielding rates and crosswalk usage after installation of in-pavement warning lights, while driving simulator evaluation resulted in drivers not becoming accustomed to scanning for lights instead of a pedestrian. Recommendations include installation of in-pavement warning lights at traditional, midblock crosswalks and continued exploration of all crosswalks in the driving simulator evaluation.

A alta ocorrência de atropelamentos nas áreas urbanas acarreta altos custos econômicos e sociais. Por isso, é importante a adoção de medidas de segurança viária que visem previnir e mitigar os riscos de acidentes envolvendo pedestres. Para que essas medidas sejam eficazes, sua escolha deve estar embasada em informações sobre onde, como e porque os atropelamentos acontecem. Uma forma de obtenção dessas informações envolve as avaliações de risco. Este trabalho propõe um método de avaliação de risco potencial de atropelamentos em travessias urbanas em meio de quadra. O método proposto incorpora análises quantitativas e qualitativas através de técnicas de modelagem que relacionam a incidência de atropelamentos e a percepção de risco dos pedestres com os fatores de risco. A aplicação do método envolveu a análise dos dados de atropelamentos registrados na cidade de Porto Alegre durante o período de 1998 e 2006 e a identificação das travessias em meio de quadra onde ocorreu o maior número de atropelamentos nesse período. Foram identificadas e, então, analisadas 21 travessias em meio de quadra. A análise das travessias incluiu a coleta de dados referentes aos fatores de risco e uma simulação de vídeo, onde pedestres e especialistas avaliaram as travessias no que concerne a sua segurança. A partir dos dados coletados, foram construídos dois modelos de regressão, um embasado em dados de ocorrência de atropelamentos e outro em dados de percepção de risco. A análise desses modelos mostrou que o risco de atropelamento é influenciado por uma combinação de fatores de risco, entre os quais as características do transporte coletivo, a largura da via, o número de faixas de tráfego de veículos, o volume de pedestres e de veículos. Ressalta-se que os modelos construídos podem ser utilizados para relativizar o risco observado e percebido de travessias em meio de quadra de Porto Alegre e fornecer indicativos para o gerenciamento da segurança dos pedestres. O estudo de caso mostrou que a aplicação do método proposto é simples, sendo possível a sua transferência a realidades onde há escassez de dados e recursos para sua obtenção. / The high occurrence of pedestrian crashes in urban areas results in high social and economic costs. To address this problem, it is important to adopt countermeasures that aim to prevent and reduce the risk of pedestrian crash. In order to obtain efficient countermeasures, their selection must be based on information of where, when and why the pedestrian crashes occur. This information can be obtained through risk evaluation. This dissertation proposes a method to evaluate the potential risk of pedestrian crash at midblock crosswalks. The proposed method incorporates quantitative and qualitative analyses, using modeling techniques to understand the relationship of risk factors with pedestrian crash occurrence and the relationship of risk factors with pedestrian risk perception. The method application comprised the analysis of reported pedestrian crashes in the city of Porto Alegre, in southern Brazil, over the period of 1998 to 2006 and the identification of midblock crosswalks with the highest incidence of pedestrian crash. Twenty one midblock crosswalks were indentified and, then analyzed. The crosswalks’ analysis included data collection about risk factors and video simulations. During the video simulations, pedestrians and experts evaluated the crosswalks’ safety. Two regression models were developed using the data collected, one based on pedestrian crash occurrence and one based on risk perception data. The analysis of models showed that pedestrian crash risk is influenced by a combination of risk factors, such as public transportation characteristics, road width, number of through lanes, pedestrian and vehicle volumes. The developed models can be used to relativize the observed and perceived risk of midblock crosswalks in Porto Alegre and to provide information to the pedestrian safety management. The case study results showed that the application of the proposed method is simple and it is possible to use it on real world cases where data and resources to obtain such data are scarce.

A alta ocorrência de atropelamentos nas áreas urbanas acarreta altos custos econômicos e sociais. Por isso, é importante a adoção de medidas de segurança viária que visem previnir e mitigar os riscos de acidentes envolvendo pedestres. Para que essas medidas sejam eficazes, sua escolha deve estar embasada em informações sobre onde, como e porque os atropelamentos acontecem. Uma forma de obtenção dessas informações envolve as avaliações de risco. Este trabalho propõe um método de avaliação de risco potencial de atropelamentos em travessias urbanas em meio de quadra. O método proposto incorpora análises quantitativas e qualitativas através de técnicas de modelagem que relacionam a incidência de atropelamentos e a percepção de risco dos pedestres com os fatores de risco. A aplicação do método envolveu a análise dos dados de atropelamentos registrados na cidade de Porto Alegre durante o período de 1998 e 2006 e a identificação das travessias em meio de quadra onde ocorreu o maior número de atropelamentos nesse período. Foram identificadas e, então, analisadas 21 travessias em meio de quadra. A análise das travessias incluiu a coleta de dados referentes aos fatores de risco e uma simulação de vídeo, onde pedestres e especialistas avaliaram as travessias no que concerne a sua segurança. A partir dos dados coletados, foram construídos dois modelos de regressão, um embasado em dados de ocorrência de atropelamentos e outro em dados de percepção de risco. A análise desses modelos mostrou que o risco de atropelamento é influenciado por uma combinação de fatores de risco, entre os quais as características do transporte coletivo, a largura da via, o número de faixas de tráfego de veículos, o volume de pedestres e de veículos. Ressalta-se que os modelos construídos podem ser utilizados para relativizar o risco observado e percebido de travessias em meio de quadra de Porto Alegre e fornecer indicativos para o gerenciamento da segurança dos pedestres. O estudo de caso mostrou que a aplicação do método proposto é simples, sendo possível a sua transferência a realidades onde há escassez de dados e recursos para sua obtenção. / The high occurrence of pedestrian crashes in urban areas results in high social and economic costs. To address this problem, it is important to adopt countermeasures that aim to prevent and reduce the risk of pedestrian crash. In order to obtain efficient countermeasures, their selection must be based on information of where, when and why the pedestrian crashes occur. This information can be obtained through risk evaluation. This dissertation proposes a method to evaluate the potential risk of pedestrian crash at midblock crosswalks. The proposed method incorporates quantitative and qualitative analyses, using modeling techniques to understand the relationship of risk factors with pedestrian crash occurrence and the relationship of risk factors with pedestrian risk perception. The method application comprised the analysis of reported pedestrian crashes in the city of Porto Alegre, in southern Brazil, over the period of 1998 to 2006 and the identification of midblock crosswalks with the highest incidence of pedestrian crash. Twenty one midblock crosswalks were indentified and, then analyzed. The crosswalks’ analysis included data collection about risk factors and video simulations. During the video simulations, pedestrians and experts evaluated the crosswalks’ safety. Two regression models were developed using the data collected, one based on pedestrian crash occurrence and one based on risk perception data. The analysis of models showed that pedestrian crash risk is influenced by a combination of risk factors, such as public transportation characteristics, road width, number of through lanes, pedestrian and vehicle volumes. The developed models can be used to relativize the observed and perceived risk of midblock crosswalks in Porto Alegre and to provide information to the pedestrian safety management. The case study results showed that the application of the proposed method is simple and it is possible to use it on real world cases where data and resources to obtain such data are scarce.

A alta ocorrência de atropelamentos nas áreas urbanas acarreta altos custos econômicos e sociais. Por isso, é importante a adoção de medidas de segurança viária que visem previnir e mitigar os riscos de acidentes envolvendo pedestres. Para que essas medidas sejam eficazes, sua escolha deve estar embasada em informações sobre onde, como e porque os atropelamentos acontecem. Uma forma de obtenção dessas informações envolve as avaliações de risco. Este trabalho propõe um método de avaliação de risco potencial de atropelamentos em travessias urbanas em meio de quadra. O método proposto incorpora análises quantitativas e qualitativas através de técnicas de modelagem que relacionam a incidência de atropelamentos e a percepção de risco dos pedestres com os fatores de risco. A aplicação do método envolveu a análise dos dados de atropelamentos registrados na cidade de Porto Alegre durante o período de 1998 e 2006 e a identificação das travessias em meio de quadra onde ocorreu o maior número de atropelamentos nesse período. Foram identificadas e, então, analisadas 21 travessias em meio de quadra. A análise das travessias incluiu a coleta de dados referentes aos fatores de risco e uma simulação de vídeo, onde pedestres e especialistas avaliaram as travessias no que concerne a sua segurança. A partir dos dados coletados, foram construídos dois modelos de regressão, um embasado em dados de ocorrência de atropelamentos e outro em dados de percepção de risco. A análise desses modelos mostrou que o risco de atropelamento é influenciado por uma combinação de fatores de risco, entre os quais as características do transporte coletivo, a largura da via, o número de faixas de tráfego de veículos, o volume de pedestres e de veículos. Ressalta-se que os modelos construídos podem ser utilizados para relativizar o risco observado e percebido de travessias em meio de quadra de Porto Alegre e fornecer indicativos para o gerenciamento da segurança dos pedestres. O estudo de caso mostrou que a aplicação do método proposto é simples, sendo possível a sua transferência a realidades onde há escassez de dados e recursos para sua obtenção. / The high occurrence of pedestrian crashes in urban areas results in high social and economic costs. To address this problem, it is important to adopt countermeasures that aim to prevent and reduce the risk of pedestrian crash. In order to obtain efficient countermeasures, their selection must be based on information of where, when and why the pedestrian crashes occur. This information can be obtained through risk evaluation. This dissertation proposes a method to evaluate the potential risk of pedestrian crash at midblock crosswalks. The proposed method incorporates quantitative and qualitative analyses, using modeling techniques to understand the relationship of risk factors with pedestrian crash occurrence and the relationship of risk factors with pedestrian risk perception. The method application comprised the analysis of reported pedestrian crashes in the city of Porto Alegre, in southern Brazil, over the period of 1998 to 2006 and the identification of midblock crosswalks with the highest incidence of pedestrian crash. Twenty one midblock crosswalks were indentified and, then analyzed. The crosswalks’ analysis included data collection about risk factors and video simulations. During the video simulations, pedestrians and experts evaluated the crosswalks’ safety. Two regression models were developed using the data collected, one based on pedestrian crash occurrence and one based on risk perception data. The analysis of models showed that pedestrian crash risk is influenced by a combination of risk factors, such as public transportation characteristics, road width, number of through lanes, pedestrian and vehicle volumes. The developed models can be used to relativize the observed and perceived risk of midblock crosswalks in Porto Alegre and to provide information to the pedestrian safety management. The case study results showed that the application of the proposed method is simple and it is possible to use it on real world cases where data and resources to obtain such data are scarce.

The aim of this research was to analyze if current generation PC-driven virtual reality simulations can be used to accurately mimic and therefore, observe behavior at a crosswalk. Toward that goal, the following research tasks were carried out: a) Designing a 3D virtual crosswalk and recruiting volunteers to wear the HTC Vive headset and to walk across the street, b) Setting up cameras near the midblock crosswalk on University Drive at California Polytechnic State University, San Luis Obispo to observe pedestrians, and c) Comparing pedestrian behavior data from both the virtual and real midblock crosswalk. The comparison was based on the following criteria: a) Pedestrian walking speed, b) Observation patterns prior to crossing the road, characterized by glancing left and right to detect cars, and c) Pedestrians’ decisions as to where to cross, defined by if they chose to walk directly on or outside of the midblock crosswalk. Walking speed and the number of pedestrians who looked left and right before crossing were significantly different in both the virtual and real environments. On the other hand, the proportion of people who chose to walk on the crosswalk was similar in both environments. This result indicates that there is a future potential in using virtual reality to analyze pedestrian behavior at roundabouts. Although this study showed that PC-driven virtual reality is not effective in replicating pedestrian walking speeds or pedestrian observation patterns at a midblock crosswalk, researchers may expect PC-driven virtual reality to have greater applications within the transportation discipline once the technology improves over the years. Potential improvements in technology that would help include being wireless, allowing users to walk in a non-confining space, and making the equipment more affordable, allowing the technology to become more mainstream.

<p>  </p> <p>The research described in this dissertation began in response to frequent questions from users of several crosswalks near a university campus. At each crosswalk was a sign indicating that motorists should yield to pedestrians in the crosswalk. That this message was not being interpreted uniformly was a concern at locations where heterogeneous road users (pedestrians, cyclists, and motorists) were interacting. Instead of trying to impose a single interpretation on users of each crosswalk, it was decided to observe and analyze interactions between users of the crosswalk. </p> <p>Several hours of video were recorded of pedestrians and motorists “negotiating” the right of way at the crosswalk. Because these crossing locations were marked but not signalized, they were called “semi-controlled crosswalks”. The negotiations took place during what were called pedestrian-motorist interactions (PMIs). The PMIs observed on video can be characterized as a “zebra-crossing” game, as described in Chapter 4 of this dissertation. </p> <p>Recently, computer vision (CV) algorithms have been extensively used in road users’ detection and tracking at an unparalleled spatial-temporal scale. In this study, CV algorithms have been applied to convert the video recordings into a large-scale spatial-temporal trajectory dataset including 800 pedestrians and cyclists interacting with more than 500 vehicles. Utilizing the trajectory dataset, a spatial-temporal graph convolutional network-based sequence to sequence (ST-GCN-Seq2Seq) algorithm has been developed to reasonably forecast heterogeneous road users’ trajectories and behavior in real time. Combining CV and ST-GCN-Seq2Seq algorithms can help both design an intelligent tracking system and achieve a form of “smart” interaction at semi-controlled crosswalks for heterogeneous road users.</p> <p>Based on road users’ arrival patterns detected from CV algorithms, it is likely that a "smart" control strategy can minimize the delay of pedestrians and motorists at crosswalks.  Therefore, another branch of this study is to investigate the “smart” control strategies at crosswalks using traffic signal controllers. A reinforcement learning framework was proposed as the “smart” control strategy, and several experiments were conducted using microsimulation. The proposed reinforcement learning framework is able to reduce traffic delay (efficiency), considering real-time pedestrian flow rates and vehicle flow rates with appropriate sensors.</p>