An Intelligent Pedestrian Device (IPD) is a new concept in pedestrian safety. It is defined as a microprocessor based information device which detects the approach of oncoming vehicles and informs the pedestrian whether or not it is safe to cross. IPDs could be portable or fixed to a roadside station. They could help reduce pedestrian accidents, which cost £2681 million in the UK in 1994. This study aims to assess whether the concept is socially acceptable and what the design criteria might be. A study of social acceptance involved group interviews of 5-10 participants with 84 pedestrians in five categories: adults aged 18-60, elderly aged 65+, visually restricted, parents of children aged 5-9 and children aged 10-14. The results suggest that vulnerable pedestrians are more positive about the device than the more able-bodied. Theories that may help explain this are discussed and it is concluded that, with education and marketing, the IPD could gain a degree of social acceptance. Observation of more than 900 pedestrian crossing movements at four different sites showed a range of behaviours, and that people often take risks in order to reduce delay. IPDs will require pedestrians to change some of their behaviours, especially those that are risky. Legal acceptance will demand high levels of costly product research and development, and a portable device will not be technologically feasible until well into the next century. However, the wider social benefits of IPDs may be worth the costs. An outline of design criteria for basic and sophisticated portable IPDs is given, and alternative functions are suggested. It is recommended that further work concentrate on developing software and hardware for fixed modes of IPD. It is concluded that, ultimately, acceptance will probably depend on whether Government decides that the IPD has a place in the road environment of the future.

Sustainable Built Environments Senior Capstone Project / Sidewalk fragmentation in Tucson is the result of City Code Ordinance 25-12 that places the responsibility of sidewalk installation and maintenance on property owner. However, with an average household income 27% below the national average and 25% of Tucson residents living below poverty level sidewalk fragmentation has become a pedestrian safety concern. By using Google Earth to measure the percentage of paved, unpaved and not present sidewalks in four historic communities in central Tucson; this study found a directly proportional relationship between the length of time the neighborhood has been listed as a historic community and the percentage of paved sidewalks within the neighborhood.

The Child Pedestrian Injury Prevention Project (CPIPP) is a rigorous school- and community-based intervention trial delivered to 2,500 children in their second, third and fourth year of schooling in three communities in Perth, Western Australia, from 1995 to 1997. The CPIPP was designed to improve children's pedestrian safety knowledge, their road related behaviors - crossing and playing, and to reduce their risk in, and exposure to, traffic. This thesis addresses the process evaluation of the CPIPP school-based intervention. The Curtin University Human Research Ethics Committee provided ethics approval for this project.Evaluation of previous school-based pedestrian safety programs has focused mainly on assessing outcomes with little or no process evaluation. An absence of process evaluation increases the likelihood of Type III error, that is, incorrectly attributing null or weak outcomes to a program that has not been adequately implemented.In each of the three study years, following a teacher training, teachers were asked to implement the school-based intervention. Each year this comprised nine 40-minute pedestrian safety lessons and home activities. Lessons included road crossing practise on real and simulated roads.Data were collected from the student cohort (n=1049) and their Grade 2, 3 and 4 teachers. Four process evaluation instruments were developed and administered in each of the three study years. These included one student instrument (work samples) and three teacher instruments (lesson log, teacher post-implementation questionnaire and classroom observation). Student outcome data including their pedestrian-related knowledge and road crossing and playing behaviours were assessed using a pre- and post-test self report questionnaire.The majority of teachers (70-97%) and students (72-84%) responded positively to questions about their satisfaction with the ++ / CPIPP Grades 2, 3 and 4 curricular. Evidence in student work samples demonstrated that teachers taught 76% (seven of nine lessons) of the Grades 2 and 3 curricular, and 68% (six of the nine lessons) of the Grade 4 curricular. Teacher self-reported implementation rates using a 'lesson log' were 88%, 81% and 60% respectively for the three curricular. Teachers reported practising road crossing on a real road in 21% (one lesson) of six designated crossing practise lessons in 1996 and 36% (two lessons) in 1997.Multivariate analyses revealed students pedestrian safety knowledge was significantly associated with teacher implementation of the classroom curriculum. This relationship was one of dose-response. It demonstrated students who, each year, received at least 7 lessons (81% or more) of the three CPIPP curricular showed a greater improvement in pedestrian safety knowledge than those students who received a lower dose of the curriculum. Significant effects on pedestrian safety knowledge were also observed for students who, each year, practised crossing a real road in at least one lesson (17%) of the curriculum. The relationship between implementation and student road crossing and road playing behaviours was not one of dose-response.Student work samples, teacher lesson logs and to a lesser extent teacher self-report questionnaires, were found to be valid measures of curriculum implementation. This study also found that implementation of the CPIPP curriculum achieved a modest improvement in student pedestrian safety knowledge and possibly arrested the decline of safe road crossing behaviour. It also demonstrated that classroom pedestrian safety education alone, while necessary, is not sufficient to positively modify children's road crossing behaviours.The findings of this study demonstrate the importance of measuring teacher implementation. A process evaluation is ++ / essential to determine if an intervention has been implemented and to help explain the impact this level of implementation had on program outcomes. However, more research needs to explore the link between other factors in the process of curriculum delivery and program effects. Further research also needs to determine how to develop and measure an intervention that includes the key procedures and content that theoretically promote the desired behaviour, but also allows teachers to make adjustments to the program to suit their teaching style and the needs of their students.Child pedestrian injury is a complex problem that requires a multifaceted intervention, of which a classroom curriculum can form part.

Each day, approximately 25,000 GSU students, staff, and faculty are exposed to deadly hazards from fast-moving, high-volume traffic. Protecting Pedestrians on the Move (PPM), a collaboration of organizations in downtown Atlanta, has partnered with several groups to implement an action plan to improve pedestrian safety for Georgia State students and others in the downtown campus area. This study utilized the SWOT analysis evaluative tool to understand the team members’ and stakeholders’ perceptions of the project’s programming and implementation. Participants were asked to rate the extent to which the project’s goals were fulfilled, as well as to describe the strengths, weaknesses, opportunities and threats of five aspects of the project: people, program, effectiveness, resources, and growth. Seven participants completed the survey, and gave an overall rating of the completion of project objectives as 6.2 out of 10. Staff expertise and relationships were considered the greatest strengths, and PPM becoming a strong voice for pedestrian safety was viewed to be the primary opportunity of the PPM project. Overly ambitious goals and depleted funding were reported as the greatest weaknesses, and loss of objectives and no succession plan were considered the primary threats. Areas for future improvement included: finding a funding and personnel “home” for the PPM project, having a clear strategic plan, and developing plans for the future/sustainability. The insights gained from this SWOT analysis exercise provides direction for continued research and improved program implementation surrounding pedestrian safety issues.

People with vision impairment have various challenges in wayfinding, navigation, and crossing signalized intersections. They often face physical and information barriers that impede their mobility and undermine their safety along a trip. Visually impaired people usually use a white cane as their primary aid when crossing urban traffic intersections. In order to improve their mobility, safety and accessibility, it is important to provide an assistive system to help them in intersection navigation and to provide information regarding the surrounding environment. While assistive systems have been developed to help visually impaired pedestrians to navigate and find their way, using these systems may be inconvenient. Furthermore, none of the currently available systems provide communication between the users and traffic signal controller that can help them request pedestrian crossing signal timing. Emerging connected vehicle technologies can provide a solution to assist visually impaired people and address their challenges. Conflicts between vehicles and vulnerable road users (VRUs) often result in injuries and fatalities. A situational awareness system could be based on wireless communications between vehicles and VRUs for the exchange of situational awareness information. Compared to the radar-based and vision-based systems, the wireless-based system. can improve VRUs’ safety, especially in non-line-of-sight (NLOS) situations. In particular, it can be very helpful when drivers are making a right or left turn where there is a pedestrian in a crosswalk and visibility conditions are poor. The Smart Walk Assistant (SWA) system was designed, developed, and tested during the research of this dissertation. It includes two wireless communication pathways; pedestrian-to-infrastructure (P2I) and pedestrian-to-vehicle (P2V). The first communication pathway enables users to send a pedestrian signal request to the traffic signal controller and receive traffic signal status. The second communication pathway enables pedestrians and vehicles to exchange information, including location, speed, and heading, that can be used to detect possible conflict between pedestrian and vehicles and provide conflict alerts. The SWA system may be especially beneficial to pedestrians with disability (e.g., blind or visually impaired pedestrians) who would benefit from active support to safely cross streets at signalized intersections. Developing a reliable situational awareness system for pedestrians is much more challenging than for vehicles because a vehicle’s movement is more predictable and usually remains in the lane in the road. In order to provide better location-based services for pedestrians, a position accuracy is needed of, at most, the width of a crosswalk or sidewalk. The SWA system includes a method to estimate a pedestrian’s position. The algorithm is based on integrating Map-Matching and an Extended Kalman Filter (EKF) in a connected vehicle environment to provide precise location information. The system architecture for the SWA application was developed to be applicable for both a simulation environment and a real world traffic system. Hardware-in-the-loop (HIL) simulation environment is developed and calibrated to mimic the real world. Comprehensive testing and assessment of the system and algorithms are conducted in simulation as well as field test networks.

Indiana University-Purdue University Indianapolis (IUPUI) / Research on robust Pre-Collision Systems (PCS) requires new techniques that will allow a better understanding of the vehicle-pedestrian dynamic relationship, and which can predict pedestrian future movements. Our research analyzed videos from the Transportation Active Safety Institute (TASI) 110-Car naturalistic driving dataset to extract two dynamic pedestrian semantic features. The dataset consists of videos recorded with forward facing cameras from 110 cars over a year in all weather and illumination conditions. This research focuses on the potential-conflict situations where a collision may happen if no avoidance action is taken from driver or pedestrian. We have used 1000 such 15 seconds videos to find vehicle-pedestrian relative dynamic trajectories and pose of pedestrians. Adaptive structural local appearance model and particle filter methods have been implemented and modified to track the pedestrians more accurately. We have developed new algorithm to compute Focus of Expansion (FoE) automatically. Automatically detected FoE height data have a correlation of 0.98 with the carefully clicked human data. We have obtained correct tractography results for over 82% of the videos. For pose estimation, we have used flexible mixture model for capturing co-occurrence between pedestrian body segments. Based on existing single-frame human pose estimation model, we have introduced Kalman filtering and temporal movement reduction techniques to make stable stick-figure videos of the pedestrian dynamic motion. We were able to reduce frame to frame pixel offset by 86% compared to the single frame method. These tractographs and pose estimation data were used as features to train a neural network for classifying ‘potential conflict’ and ‘no potential conflict’ situations. The training of the network achieved 91.2% true label accuracy, and 8.8% false level accuracy. Finally, the trained network was used to assess the probability of collision over time for the 15 seconds videos which generates a spike when there is a ‘potential conflict’ situation. We have also tested our method with TASI mannequin crash data. With the crash data we were able to get a danger spike for 70% of the videos. The research enables new analysis on potential-conflict pedestrian cases with 2D tractography data and stick-figure pose representation of pedestrians, which provides significant insight on the vehicle-pedestrian dynamics that are critical for safe autonomous driving and transportation safety innovations.

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.

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The pedestrian is one of the most vulnerable road users. According to the World Health Organization (WHO), traffic accidents cause about 1.34 million fatalities annually across the world. This is the eighth leading cause of death across all age groups. Among these fatalities, pedestrians represent 23% (world), 27% (Europe), 40% (Africa), 34% (Eastern Mediterranean), and 22% (Americas) of total traffic deaths. In the United States, approximately 6,227 pedestrians were killed in road crashes in 2018, the highest number in nearly three decades. To protect pedestrians during Car-to-Pedestrian Collisions (CPC), subsystem impact tests, using impactors corresponding to the pedestrian's head and upper/lower leg were included in regulations. However, these simple impact tests cannot capture the complex vehicle-pedestrian interaction, nor the pedestrian injury mechanisms, which are crucial to understanding pedestrian kinetics/kinematics responses in CPC accidents. Numerous variables influence injury variation during vehicle-pedestrian interactions, but current test procedures only require testing in the limited scenarios that mostly focus on the anthropometry of the 50th percentile male subject. This test procedure cannot be applied to real-world accidents nor the entire pedestrian population due to the incredibly specific nature of the testing. To better understand the injury mechanisms of pedestrians and improve the test protocols, more pre-impact variables should be considered in order to protect pedestrians in various accident scenarios. In this study, simplified finite element (FE) models corresponding to 5th percentile female (F05), 50th percentile male (M50), and 95th percentile male (M95) pedestrians were developed and validated in order to investigate the kinetics and kinematics of pedestrians in a cost-effective study. The model geometries were reconstructed from medical images and exterior scanned data corresponding to a small female, mid-sized male, and tall male volunteers, respectively. These models were validated based on post mortem human surrogate (PMHS) test data under various loading including valgus bending at knee joint, lateral/anterior-lateral impact at shoulder, pelvis, thorax, and abdomen, and lateral impact during CPC. Overall, the kinetic/kinematic responses predicted by the pedestrian FE models showed good agreement against the corresponding PMHS test data. To predict injuries from the tissue level up to the full-body, detailed pedestrian models, including sophisticated musculoskeletal system and internal organs, were developed and validated as well. Similar validations were performed on the detailed pedestrian models and showed high-biofidelic responses against the PMHS test data. After model development and validation, the effect of pre-impact variables, such as anthropometry, pedestrian posture, and vehicle type in CPC impacts were investigated in different impact scenarios. The M50-PS model's posture was modified to replicate pedestrian gait posture. Five models were developed to demonstrate pedestrian posture in 0, 20, 40, 60, and 80 % of the gait cycle. In a sensitivity study, the 50th percentile male pedestrian simplified (M50-PS) model in gait predicted various kinematic responses as well as the injury outcomes in CPC impact with different vehicle type. The pedestrian FE models developed in this work have the capability to reproduce the kinetic/kinematic responses of pedestrians and to predict injury outcomes in various CPC impact scenarios. Therefore, this work could be used to improve the design of new vehicles and current pedestrian test procedures, which eventually may reduce pedestrian fatalities in traffic accidents. / Doctor of Philosophy / The pedestrian is one of the most vulnerable road users. According to the World Health Organization, traffic accidents cause about 1.34 million fatalities annually across the world. This is the eighth leading cause of death across all age groups. Among these fatalities, pedestrians represent 23% (world), 27% (Europe), 40% (Africa), 34% (Eastern Mediterranean), and 22% (Americas) of total traffic deaths. In the United States, approximately 6,227 pedestrians were killed in road crashes in 2018, the highest number in nearly three decades. To protect pedestrians in traffic accidents, subsystem impact tests, using impactors corresponding to the pedestrian’s head and upper/lower leg were included in regulations. However, these simple impact tests cannot capture the complex vehicle-pedestrian interaction, nor the pedestrian injury mechanisms, which are crucial to understanding pedestrian kinetics/kinematics responses in traffic accidents. Numerous variables influence injury variation during vehicle-pedestrian interactions, but current test procedures only require testing in the limited scenarios that mostly focus on the anthropometry of the average male subject. This test procedure cannot be applied to real-world accidents nor the entire pedestrian population due to the incredibly specific nature of the testing. To better understand the injury mechanisms of pedestrians and improve the test protocols, more pre-impact variables should be considered in order to protect pedestrians in various accident scenarios. In this study, simplified pedestrian computational models corresponding to small female, average male, and large male pedestrians were developed and validated in order to investigate the kinetics and kinematics of pedestrians in a cost-effective study. Overall, the kinetic/kinematic responses predicted by the pedestrian models showed good agreement against the corresponding test data. To predict injuries from the tissue level up to the full-body, detailed pedestrian computational models, including sophisticated musculoskeletal system and internal organs, were developed and validated as well. Similar validations were performed on the detailed pedestrian models and showed high-biofidelic responses against the test data. After model development and validation, the pre-impact variables were examined using the average male pedestrian model, which was modified the position to replicate pedestrian gait posture. In a sensitivity study, the average male pedestrian model in gait predicted various kinematic responses as well as the injury outcomes in lateral impact with different vehicle types. The pedestrian models developed in this work have the capability to reproduce the kinetic/kinematic responses of pedestrian and to predict injury outcomes in various pedestrian impact scenarios. Therefore, this work could be used to improve the design of new vehicles and current pedestrian test procedures, which eventually many reduce pedestrian fatalities in traffic accidents.

This thesis looked at traffic crashes in the emirate of Dubai in the United Arab Emirates (UAE) to establish the current situation in road safety and ways of improving it. A global overview of road safety literature revealed that standards of road safety vary widely by region. Key indicators like fatality rate and risk (Jacobs et al, 2000) were found to be higher in most neighbouring Gulf Cooperative Council (GCC) countries (10-25 fatalities/100,000 pop., 3-5 fatalities/10,000 motor vehicles) than in the best-performing Western countries (6 fatalities/100,000 pop., 1 fatality/10,000 motor vehicles). Interventions and countermeasures to tackle specific road safety issues were reviewed from international studies. Countermeasures were chosen with consideration for the local situation in Dubai within the categories of Human, Environmental and Vehicle factors. Examples of selected measures include offending driver punishment (Human), Electronic Stability Control (Vehicle) and central barriers (Environment). These measures were mostly studied in different environments to those in Dubai so the aspect of knowledge transfer between areas of different cultural and environmental conditions was discussed. Data from real world injury crashes (as collected by Dubai Police and the Roads & Transport Authority) over twelve years (1995 2006) were subject to macroanalysis in SPSS to identify the main issues over the past decade. 18,142 crashes involving 30,942 casualties and 48,960 vehicles were analysed at the outset. The following issues were among the main concerns: - High proportion of fatal crashes out of all injury crashes (13.5% compared to 1.4% in the UK); - Most fatal crashes involved a single vehicle hitting a pedestrian; - Most injury crashes involved a single vehicle; - Inconsiderate driving was the most common crash cause cited by the police. Countermeasures found in the literature to counteract these problems were then suggested for application and the estimated savings from applying them were calculated. Savings were quantified as either reductions in casualties or injury crashes. Furthermore, cost savings for the calculated reductions were estimated using existing UK crash costs due to the scarcity of UAE crash cost estimates. Calculation of the estimated improvement in safety if these countermeasures were applied retrospectively meant a reduction of 4,634 injury crashes and 1,555 casualties over the 12-year period with an estimated cost saving of approximately £368 million or 2.7 billion Dirhams. To refine this method more detailed data on crashes were required and collected from the dedicated crash investigation team files in Dubai Police for 2006 and part of 2007. This new dataset (300 crashes) was put into a purpose-built database with over 140 fields and subject to microanalysis to more accurately match the problems and interventions. Six interventions were matched to individual cases in the database where they would have positively altered the outcome. This process was verified by independent crash experts and investigators. The benefits from these six countermeasures were then weighted to calculate the benefits for the whole crash population over a year. Examples of specific interventions included guardrails along the roadside; grade-separated crossing facilities for pedestrians; Electronic Stability Control and speed cameras. The estimated total reduction in crashes was 2,412 annually with calculated savings of £40 million or 280 million Dirhams. This was the first time this geographical area was studied in such depth and detail to allow the calculation of benefits from interventions matched to known road safety issues. Various limitations were encountered such as the unavailability of GIS basemaps and the continuously changing infrastructure and population of Dubai. Numerous areas of further work were identified. Such work areas include hospital studies for collecting injury data to compare with police data; changing vehicle standards so that they are better suited to local crash types; the calculation of crash and injury costs based on local figures; vehicle fleet analysis for comparing different vehicle segments and exposure; and improved data collection and storage methods.