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Copyright of Journal of Modern Science is the property of Alcide De Gasperi University of Euroregional Economy and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Advanced Driving Assistance System (ADAS) can predict pedestrian's trajectory, in order to avoid traffic accidents and guarantee driving safety. A few current pedestrian trajectory prediction methods use a pedestrian's historical motion to predict the future trajectory, but the pedestrian's trajectory is also affected by the vehicle using the ADAS for prediction (target vehicle). Other studies predict the pedestrian's and vehicle's trajectories separately, and use the latter to adjust the former, but their interaction is a continuous process and should be considered during prediction rather than after. Therefore, we propose PVII, a pedestrian-vehicle interactive and iterative prediction framework for pedestrian's trajectory. It makes prediction for one iteration based on the results from previous iteration, which essentially models the vehicle-pedestrian interaction. In this iterative framework, to avoid accumulation of prediction errors along with the increased iterations, we design a bi-layer Bayesian en/decoder. For each iteration, it not only uses inaccurate results from previous iteration but also accurate historical data for prediction, and calculates Bayesian uncertainty values to evaluate the results. In addition, the pedestrian's trajectory is affected by both target vehicle and other vehicles around it (surrounding vehicle), so we include into the framework a pre-trained speed estimation module for surrounding vehicles (SE module). It estimates the speed based on pedestrian's motion and we collect data from pedestrian's view for training. In experiments, PVII can achieve the highest prediction accuracy compared to the current methods. [ABSTRACT FROM AUTHOR]

Objectives: Child pedestrian injuries represent a significant public health challenge. Understanding the most complex cognitive skills required to cross streets helps us understand, improve, and protect children in traffic, as underdeveloped cognitive skill likely impacts children's pedestrian safety. One complex component of street-crossing is the cognitive-perceptual task of judging time-to-arrival of oncoming traffic. We examined capacity of 7- and 8-year-olds to judge time-to-arrival for vehicles approaching from varying distances and speeds, as well as improvement in those judgments following intensive street-crossing training in a virtual reality (VR) pedestrian simulator. Methods: 500 seven- and eight-year-olds participated in a randomized trial evaluating use of a large kiosk VR versus smartphone-based VR headset to teach street-crossing skills. Prior to randomization into VR training condition and also prior to initiation of any training, children engaged in a video-based vehicle approach estimation task to assess ability to judge traffic time-to-arrival. They then engaged in multiple VR-based pedestrian safety training sessions in their randomly assigned condition until achieving adult functioning. Soon after training and again 6 months later, children repeated the vehicle estimation task. Results: Prior to randomization or training, children were more accurate judging time to arrival for closer versus farther traffic, and rapidly-moving versus slower-moving traffic, but those results were subsumed by a speed x distance interaction. The interaction suggested distance cues were used more prominently than speed cues, and speed had varying effects at different distances. Training group had minimal effect on learning and all children became significantly better at judging vehicle arrival times following training. Conclusions: Children tend to underestimate vehicle arrival times. Distance cues are more impactful on time-to-arrival judgments than speed cues, but children's estimations based both on manipulations of vehicle speed and manipulations of vehicle distance improved post-training. Improvements were retained six months later. This finding is consistent with psychophysics research suggesting vehicle approach judgments rely on optical size and looming, which are impacted both by vehicle speeds and distances. Implementation of VR-based training for child pedestrian safety is recommended, as it may improve children's judgment of vehicle time-to-arrival, but it must be conducted cautiously to avoid iatrogenic effects. [ABSTRACT FROM AUTHOR]

Recent advancements in autonomous vehicle (AV) technology have the potential to reduce road accidents caused by human error. However, to enhance their safety and performance, it is crucial to understand the patterns of AV collisions. This study examines AV collisions by analyzing their temporal and spatial patterns. Based on reports from the California DMV between 2014 and 2022, the analysis reveals that rear-end collisions are the most common type, while incidents involving pedestrians and overturned vehicles are rare. The majority of collisions involve mid-sized vehicles, and AVs are responsible for a minority of accidents. The study also identifies clusters of incidents in San Francisco, San Jose, Los Angeles, and San Diego, with San Francisco having largest concentration. Specific areas within San Francisco, like Mission District, Japantown, Union Square, and North Beach neighborhoods, show high incident rates. These findings highlight safety concerns, and aid in integration of AVs into transportation infrastructure. [ABSTRACT FROM AUTHOR]

AbstractEven though accidents with pedestrians are more likely to have a severe or fatal outcome, most research concentrates on the vehicle part of the accidents. To make better policies and infrastructure decisions it is crucial to understand how and why such accidents happen. In this article, 2.588 pedestrian accidents from the year 2018 that resulted in injury or death in the city of Ankara, Türkiye are considered, and different attributes are analyzed co-location-wise. Three types of analysis will be undertaken for these accidents: temporal, natural environment, and pedestrian characteristics. The season of the year, weekend-weekday, and time of day will be explored for the temporal analysis. Visibility (daylight, twilight, and darkness) and rain are the natural surroundings of interest. The analyzed pedestrian characteristics are age group, gender, clothing colour, and nationality. Generally, the accident properties are evenly distributed and mostly the higher co-locations occur with themselves. Three important results stand out in this study. Firstly, the type of precaution appropriate to different time periods of the day should be applied, taking into account the locations that have the strongest co-location with themselves. Secondly, a seasonal approach should be adopted in determining places where pedestrian safety needs to be increased in the city. Lastly, pedestrian safety measures targeting especially both ‘0–14 and 65 + age groups’ and ‘foreign citizenship’ should be prioritized in the identified locations. The results show that the co-location methodology is a good fit for analyzing pedestrian accidents and a wider use of this methodology for other accident types and in general might be beneficial. [ABSTRACT FROM AUTHOR]

Investigating pedestrian safety disparities across sociodemographic groups is essential for enhancing traffic safety. This study examines the impact of sociodemographic and built environment characteristics on pedestrian crashes. It introduces a comprehensive macro spatial analysis framework that includes a global regression model, spatial autoregressive models, and a local spatial regression model. Three measures of pedestrian injury are analyzed. The findings reveal that a higher percentage of the high-income population significantly correlates with lower rates of pedestrian injuries across all three measures. Conversely, a higher percentage of the low-income population shows a significant positive correlation with the proportion of crashes involving the Black population, and with the proportion of severe pedestrian crashes involving the Black population. Pedestrian-oriented network density is negatively associated with fatal or severely injurious crashes involving the Black population. These results emphasize the need to account for spatial variations and equity when addressing pedestrian safety disparities. • A comprehensive spatial modeling framework using OLS, SAR, and MGWR explores spatial autocorrelation and non-stationarity in pedestrian crashes. • The research analyzes disparities in pedestrian safety and evaluates pedestrian crash rates and Black population involvement in total and severe crashes. • Higher-income areas have lower pedestrian injury rates, while low-income areas see more severe crashes involving the Black population. [ABSTRACT FROM AUTHOR]

• Association between vehicle front-end profiles and pedestrian fatality risk was examined. • A large crash sample and measurements of the vehicles involved were used. • Tall/blunt, tall/sloped, and medium-height/blunt front ends were associated with increased pedestrian fatality risk. • A relatively flat hood was associated with higher pedestrian fatality risk. • Automakers should design front ends lower and more sloped for pedestrian safety. Introduction: Vehicles play an important role in pedestrian injury risk in crashes. This study examined the association between vehicle front-end geometry and the risk of fatal pedestrian injuries in motor vehicle crashes. Method: A total of 17,897 police-reported crashes involving a single passenger vehicle and a single pedestrian in seven states were used in the analysis. Front-end profile parameters of vehicles (2,958 vehicle makes, series, and model years) involved in these crashes were measured from vehicle profile photos, including hood leading edge height, bumper lead angle, hood length, hood angle, and windshield angle. We defined a front-end-shape indicator based on the hood leading edge height and bumper lead angle. Logistic regression analysis evaluated the effects of these parameters on the risk that a pedestrian was fatally injured in a single-vehicle crash. Results: Vehicles with tall and blunt, tall and sloped, and medium-height and blunt front ends were associated with significant increases of 43.6%, 45.4%, and 25.6% in pedestrian fatality risk, respectively, when compared with low and sloped front ends. There was a significant 25.1% increase in the risk if a hood was relatively flat as defined in this study. A relatively long hood and a relatively large windshield angle were associated with 5.9% and 10.7% increases in the risk, respectively, but the increases were not significant. Conclusions: Vehicle front-end profiles that were significantly associated with increased pedestrian fatal injury risk were identified. Practical Applications: Automakers can make vehicles more pedestrian friendly by designing vehicle front ends that are lower and more sloped. The National Highway Traffic Safety Administration (NHTSA) can consider evaluations that account for the growing hood heights and blunt front ends of the vehicle fleet in the New Car Assessment Program or regulation. [ABSTRACT FROM AUTHOR]

There has been a concerning rise in pedestrian fatalities resulting from traffic accidents. This study conducts an in-depth analysis of the factors that contribute to the injury severity of pedestrians considering human, vehicle, roadway, and environmental characteristics of the crashes. A novel approach is proposed by combing a data mining technique and mixed logit models. First, the Apriori algorithm is employed to uncover patterns between fatal and incapacitating injury outcomes and their influencing factors. Then, mixed logit models are developed to investigate heterogeneity across all observations under two different lighting conditions. It is found that eight variables show heterogeneity affecting the injury severity of crash outcomes. Results also indicate that drivers older than 65 years old will increase the probability of pedestrian injury severity at dark-unlighted roads. Additionally, the present of signal and double yellow line has could increase the injury severity. Creating optimal lighting conditions at pedestrian crossings during nighttime hours and enhancing safety education initiatives for pedestrians are critical factors to improve pedestrian safety. The finding of this study will benefit policymakers and road safety professionals develop more effective strategies for preventing pedestrian injuries in vehicle crashes. [ABSTRACT FROM AUTHOR]

This study examines the impact of urban form and street infrastructure on pedestrian safety in Atlanta, Georgia, and Boston, Massachusetts. With a significant rise in pedestrian fatalities over the past decade, understanding how cities' built environments influence safety is critical. We conducted geospatial analyses and statistical tests, revealing unique patterns in each city. Atlanta's sprawling, motorist-oriented layout is associated with increased pedestrian accidents, particularly at crosswalks, due to limited land use diversity, arterial roads, and streets with high speed limits and multiple lanes. In contrast, Boston's compact, pedestrian-oriented design leads to improved safety, featuring safer pedestrian crossings, greater land use diversity, reduced arterial roads and lower speed limits on single-lane streets. This study also highlights the importance of diverse urban forms and pedestrian infrastructure in shaping pedestrian safety. While population density and land use diversity impact accident rates, the presence of crosswalks and street configurations play crucial roles. Our findings underscore the urgency for urban planners to prioritize pedestrian safety through targeted interventions, such as enhancing crosswalks, reducing speed limits and promoting mixed land use. Future research should explore additional variables, alternative modelling techniques and non-linear approaches to gain a more comprehensive understanding of these complex relationships. [ABSTRACT FROM AUTHOR]

As the elderly population grows, there is a greater concern for their safety on the roads. This is particularly important for elderly pedestrians who are more vulnerable to accidents. In Spain, one of the most aged countries in the world, the elderly accounted for 70% of all pedestrian deaths in 2019. In this study, the focus was on analysing the occurrence of elderly pedestrian-vehicle collisions in Spanish municipalities and how it is related to the built environment. The study used the hurdle negative binomial model to analyse the number of elderly and non-elderly pedestrian accidents per municipality in 2016-2019. The exploratory analysis showed that cities above 50,000 inhabitants were safer for the elderly, and larger provincial capitals had lower elderly pedestrian traffic accident rates. The occurrence of all pedestrian traffic accidents was linked to the socio-demographic features. For elderly pedestrians, land use was found to be influential, with a lower proportion of land covered by manufacturing and service activities linked to a smaller number of accidents. Results showed that improving road safety for older pedestrians may not necessarily compromise the situation for the rest of population. Hence, policymakers should focus on infrastructure improvements adapted to the needs of elderly pedestrians. [ABSTRACT FROM AUTHOR]

The study primarily seeks to investigate the behavioral attribution of distraction in pedestrian road crossing. A distraction-themed questionnaire survey was conducted across Kolkata city, India, to understand the contribution of distraction to near-misses and injuries. The survey response showed that among all reported respondents, 13.7% (61) encountered at least one near-miss and 4.5% (20) experienced at least one accident in the past. The video-based observational field study of 2,360 pedestrians revealed that 28.7% of the pedestrians were distracted while crossing the road. Pedestrians who text walked relatively slowly and 7.9% more likely to violate signal. Additionally, mobile phone talkers were observed to be 4.5% more likely to nearly hit/bump into another oncoming pedestrian. The present study constitutes vital information for planners and policymakers and plays a pivotal role in identifying critical intersections and developing countermeasures to minimize the impact or occurrence of pedestrian distraction and unsafe behavior. [ABSTRACT FROM AUTHOR]

The objective of this study was to describe fatal pedestrian injury patterns in youth aged 15 to 24 years old and correlate them with motor vehicle collision (MVC) dynamics and pedestrian kinematics using data from medicolegal death investigations of MVCs occurring in the current Canadian motor vehicle (MV) fleet. Based on a systematic literature review, MVC–pedestrian injuries were collated in an injury data collection form (IDCF). The IDCF was coded using the Abbreviated Injury Scale (AIS) 2015 revision. The AIS of the most frequent severe injury was noted for individual body regions. The Maximum AIS (MAIS) was used to define the most severe injury to the body overall and by body regions (MAISBR). This study focused on serious to maximal injuries (AIS 3–6) that had an increasing likelihood of causing death. The IDCF was used to extract collision and injury data from the Office of the Chief Coroner for Ontario (OCCO) database of postmortem examinations done at the Provincial Forensic Pathology Unit (PFPU) in Toronto, Canada, and other provincial facilities between 2013 and 2019. Injury data were correlated with data about the MVs and MV dynamics and pedestrian kinematics. The study was approved by the Western University Health Science Research Ethics Board (Project ID: 113440; Lawson Health Research Institute Approval No. R-19-066). There were 88 youth, including 54 (61.4%) males and 34 (38.6%) females. Youth pedestrians comprised 13.1% (88/670) of all autopsied pedestrians. Cars (n = 25/88, 28.4%) were the most frequent type of vehicle in single-vehicle impacts, but collectively vehicles with high hood edges (i.e., greater distance between the ground and hood edge) were in the majority. Forward projection (n = 34/88, 38.6%) was the most frequent type of pedestrian kinematics. Regardless of the type of vehicle, there was a tendency in most cases for the median MAISBR ≥ 3 to involve the head and thorax. A similar trend was seen in most of the pedestrian kinematics involving the various frontal impacts. Of the 88 cases, at least 63 (71.6%) were known to be engaged in risk-taking behaviors (e.g., activity on roadway). At least 12 deaths were nonaccidental (8 suicides and 4 homicides). Some activities may have been impairment related, because 26/63 (41.3%) pedestrians undertaking risk-taking behavior on the roadway were impaired. Toxicological analyses revealed that over half of the cases (47/88, 53.4%) tested positive for a drug that could have affected behavior. Ethanol was the most common. Thirty-one had positive blood results. A fatal dyad of head and thorax trauma was observed for pedestrians struck by cars. For those pedestrians hit by vehicles with high hood edges, which were involved in the majority of cases, a fatal triad of injuries to the head, thorax, and abdomen/retroperitoneum was observed. Most deaths occurred from frontal collisions and at speeds more than 35 km/h. [ABSTRACT FROM AUTHOR]

With the acceleration of urbanization and the growing demand for traffic safety, developing intelligent systems capable of accurately recognizing and tracking pedestrian trajectories at night or under low-light conditions has become a research focus in the field of transportation. This study aims to improve the accuracy and real-time performance of nighttime pedestrian-detection and -tracking. A method that integrates the multi-object detection algorithm YOLOP with the multi-object tracking algorithm DeepSORT is proposed. The improved YOLOP algorithm incorporates the C2f-faster structure in the Backbone and Neck sections, enhancing feature extraction capabilities. Additionally, a BiFormer attention mechanism is introduced to focus on the recognition of small-area features, the CARAFE module is added to improve shallow feature fusion, and the DyHead dynamic target-detection head is employed for comprehensive fusion. In terms of tracking, the ShuffleNetV2 lightweight module is integrated to reduce model parameters and network complexity. Experimental results demonstrate that the proposed FBCD-YOLOP model improves lane detection accuracy by 5.1%, increases the IoU metric by 0.8%, and enhances detection speed by 25 FPS compared to the baseline model. The accuracy of nighttime pedestrian-detection reached 89.6%, representing improvements of 1.3%, 0.9%, and 3.8% over the single-task YOLO v5, multi-task TDL-YOLO, and the original YOLOP models, respectively. These enhancements significantly improve the model's detection performance in complex nighttime environments. The enhanced DeepSORT algorithm achieved an MOTA of 86.3% and an MOTP of 84.9%, with ID switch occurrences reduced to 5. Compared to the ByteTrack and StrongSORT algorithms, MOTA improved by 2.9% and 0.4%, respectively. Additionally, network parameters were reduced by 63.6%, significantly enhancing the real-time performance of nighttime pedestrian-detection and -tracking, making it highly suitable for deployment on intelligent edge computing surveillance platforms. [ABSTRACT FROM AUTHOR]

In the real world, the severity of traumatic injuries is measured using the Abbreviated Injury Scale (AIS) and is often estimated, in finite element human computer models, with the maximum principal strains (MPS) tensor. MPS can predict when a serious injury is reached, but cannot provide any AIS measures lower and higher from this. To overcome these limitations, a new organ trauma model (OTM2), capable of calculating the threat to life of any organ injured, is proposed. The OTM2 model uses a power method, namely peak virtual power, and defines brain white and grey matters trauma responses. It includes human age effect (volume and stiffness), localised impact contact stiffness and provides injury severity adjustments for haemorrhaging. The focus, in this case, is on real-world pedestrian brain injuries. OTM2 model was tested against three real-life pedestrian accidents and has proven to reasonably predict the post mortem (PM) outcome. Its AIS predictions are closer to the real-world injury severity than the standard maximum principal strain (MPS) methods currently used. This proof of concept suggests that OTM2 has the potential to improve forensic predictions as well as contribute to the improvement in vehicle safety design through the ability to measure injury severity. This study concludes that future advances in trauma computing would require the development of a brain model that could predict haemorrhaging. [ABSTRACT FROM AUTHOR]

Road accidents involving pedestrians are frequent at urban signalised intersections predominantly due to unsafe pedestrian crossings. A good proportion of these accidents are occurring at T-intersection. This study aims at analysing pedestrian crossing behaviour at signalised T-intersections. Data is collected from five signalised T-intersections in Delhi, India, by using video recordings and a perception based questionnaire survey. Data is analysed using Chi-square, student t-test and Kendall's W hypothesis testing techniques. Significant variables are used to develop binary and ordinal logistic regression models. Results show that only a small percentage of pedestrians are abiding by the law to cross the road. Further a host of significant variables such as pedestrian demographics, trip purpose and state of the journey are significantly affecting crossing behaviour. The findings would be useful to improve pedestrians' safety and enrich the knowledge of pedestrian crossing behaviour at signalised T-intersections. [ABSTRACT FROM AUTHOR]

• Young and older pedestrians report more falls than middle-aged pedestrians. • Women report more frequent involvement in falls than males. However, the risk of getting injured in a fall is not higher than that of men. • Prevalence of falls and injuries seems to be weakly related to pedestrians' risky behaviour, thus other factors such as safety infrastructure probably play an important role. • The more a person walks, the less he or she falls. Many factors are associated with pedestrian injuries and accidents. If a pedestrian is injured in an outdoor public space, we are talking about a "pedestrian fall". Pedestrian falls are a more common cause of pedestrian injuries than traffic crashes but have received less attention and the literature on this topic is scarce. The aim of this work is to describe at a general level the prevalence and consequences of pedestrian falls and injuries, to make international comparisons of pedestrian falls and to identify risk factors and not least to examine the relationships between the prevalence of falls and pedestrian risk behaviour. A total of 6,373 participants from 15 different countries were recruited to take part in this study. To collect data a questionnaire was used. To cover the risky behaviour of pedestrians we used a short version of Pedestrians Behaviour Scale (PBS). In order to identify groups of countries with a similar pedestrian transport situation, a hierarchical cluster analysis was performed. The analysis produced four groups of countries based on pedestrians' safety level, popularity of walking and GDP. As for the results, we can conclude that young people and older people are more frequently involved in falls and that women report more frequent involvement in falls than males. However, the risk of getting injured in a fall is not higher than that of men. Frequent walking is associated with a lower risk of falling while walking. In contrast to this, physical activity increases such risk. The prevalence of falls and injuries seems to be weakly related to pedestrians' risky behaviour, thus other factors such as safety infrastructure probably play an important role. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Beijing University of Civil Engineering & Architecture is the property of Journal of Beijing University of Civil Engineering & Architecture Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Road Traffic Injuries are one of the world's leading cause of death, with greatest burden falling on nations with lower and moderate incomes. They are consistently ranked in top 10 leading causes of mortality worldwide for persons of all ages. The biggest advantage of classifying victim degree of injuries in road accidents can pave a way for safer roads and reduced accident rates. This article employs California based SWITRS dataset to propose a novel approach namely Stacked DCL-X model for classifying ' ' v i c t i m _ d e g r e e _ o f _ i n j u r y ′ ′ . It classifies injuries that might take place due to collisions occurring between vehicles and near by pedestrians, obstacles etc. on roads. To verify the superiority of our proposed model, several Machine Learning algorithm-based classification models are stacked together to classify ' ' v i c t i m _ d e g r e e _ o f _ i n j u r y ′ ′ . A total of 1 27 000 accidents are considered from SWITRS dataset when determining the ' ' v i c t i m _ d e g r e e _ o f _ i n j u r y ′ ′ . Machine Learning classifiers implemented in this article includes XGBoost, CatBoost, LightGBM, Decision Tree, Random Forest, Gradient Boosting and Stacked DCL-X. In addition, the algorithm used at feature selection step is Harris Hawk Optimization algorithm, a Nature Inspired Algorithm to select the best features. Prediction results shows that the proposed Stacked DCL-X model provides good stability, fewer hyper-parameters, and highest accuracy under different levels of training data volume. The values of Accuracy, Mean Square Error, and ROC-Auc in Stacked DCL-X model are 87.52, 0.5677 and 97.43, respectively. Moreover, confusion matrix and evaluation metrics of the proposed model provides better results than state-of-the-art classifiers. Statistical analysis has also been performed using Friedman's rank test on different datasets to ensure the superiority of our proposed Stacked DCL-X model. The findings of this study would be helpful in classifying the ' ' v i c t i m _ d e g r e e _ o f _ i n j u r y ′ ′ . These findings are highly significant in smart city projects to effectively establish timely proactive strategies and improve road traffic safety. [ABSTRACT FROM AUTHOR]

Safety concern among electric scooter riders drives them onto sidewalks, endangering pedestrians and making them uncomfortable. Regulators' solutions are inconsistent and conflicting worldwide. Widely accepted pedestrian safety metrics may lead to converging solutions. Adapting the time-to-collision from car traffic safety, we define projected time-to-collision and experimentally study pedestrians' objective and subjective safety. We design isolated and crowd experiments using e-scooter-to-pedestrian interactions to assess the impact of various factors on objective safety. In addition, we conducted a pedestrian survey to relate the subjective safety and the metric. We report a strong correlation between subjective safety and the projected time-to-collision when agents face each other and no relation when the e-scooter overtakes a pedestrian. As a near-miss metric correlated with pedestrian comfort, projected time-to-collision is implementable in policy-making, urban architecture, and e-scooter design to enhance pedestrian safety. Regulators' approach to electric scooters on sidewalks is inconsistent and conflicting worldwide. Maintaining a minimum projected time-to-collision as a near-miss metric provides a sufficient condition for pedestrian safety as well as improving pedestrian subjective perceived safety. [ABSTRACT FROM AUTHOR]

Decentralized traffic signal controls, such as max-pressure (MP) control, also known as back-pressure (BP) control, have received increased attention recently. MP signal control has been analytically proven to maximize the network throughput and stabilize vehicle queue lengths whenever possible. However, previous work on MP signal control with cyclic and noncyclic phases did not include pedestrian access, which may increase pedestrians’ travel time, and delay or even encourage some dangerous behaviors like jaywalking. Because the movement of pedestrians is a nonnegligible factor in traffic management, and many urban planning researchers have found that walking space and walking continuously have significant health, safety, and environmental impacts, a pedestrian-friendly MP signal control policy is needed. Here, we propose a novel pedestrian-friendly MP signal control, Ped-MP, that considers pedestrian access in an urban network to achieve both maximum stability for private vehicles and a comfortable, safe walking experience. This study modifies the original MP control to include pedestrians’ access for the first time. Furthermore, this policy still inherits the decentralized property of original MP control, which means it only relies on the local information of individual intersections. Simulation studies are implemented on a popular benchmark network, the Sioux Falls network, with added pedestrians network. The results indicate that, although considering pedestrians’ access may reduce the stable region for vehicles, the pedestrians’ travel time and delay can be reduced significantly. [ABSTRACT FROM AUTHOR]

Traumatic heterotopic ossification (HO) of the lower extremity is relatively rare but is of major importance in clinical practice. They are defined as posttraumatic abnormal formations of bone within soft tissue outside of the skeletal system. This article describes the clinical case of a 31-year-old male patient who suffered 2 traumatic events within 12 months—a gunshot wound in the lumbar spine/gluteal region followed by a severe traumatic brain injury with intracranial hemorrhage in a traffic accident as a pedestrian. Clinically, the patient was bedridden because of complete stiffening of the lumbar spine, both hip joints, and the left knee joint. After preoperative diagnosis, 3 surgical ablations of the HO were performed on both the hip joints and the left knee joint. In addition, physiotherapeutic exercise, postoperative nonsteroidal anti-inflammatory drug administration (25 mg of indomethazine for 6 weeks, 3 times a day), and perioperative radiation with 7 Gy for each operation were advised. After 4 years of follow-up, the patient showed significant improvement. In HO treatment, prophylactic local radiotherapy (pre- and postoperative radiation with a local single dose of 7 Gy) and postoperative administration of nonsteroidal anti-inflammatory drugs are often recommended. For therapeutic purposes, surgical resection is still indicated for pronounced cases. [ABSTRACT FROM AUTHOR]

Congenital nephrogenic diabetes insipidus (CNDI) is a rare disorder. The condition is characterised by an inability of distal nephron segments to respond to normal or raised concentrations of serum antidiuretic hormone. In this report, we describe the case of a 13‐year‐old male known with CNDI who experienced a pedestrian vehicle accident leading to coma following a head injury. Intra‐operatively, severe hypernatraemia and polyuria were observed. Following an inadequate response to conventional therapy, acetazolamide was prescribed resulting in an immediate response to therapy. To the best of our knowledge, acetazolamide has not been previously documented as a therapeutic option for CNDI. Additional research is necessary before considering the recommendation of acetazolamide for cases of NDI that do not respond adequately to conventional treatments. [ABSTRACT FROM AUTHOR]

Transport demand has been increasing in most third-world countries. However, poorly maintained facilities and poor planning exposed pedestrians to hightraffic accidents. This paper aims to evaluate pedestrian facilities using the pedestrian level of service to enhance pedestrian safety in Addis Ababa. Relevant data was collected through field measurement and direct observation from 13 purposively identified pedestrian sites across the Piyasa to Bole bridge and Megenagna to Torihayloch road corridors. Pedestrian level of service derivation considered capacity, traffic, comfort, safety, and security conditions and their sub-components. The weight of each criterion and sub-factor was decided according to the Saaty scale using the judgment of experts under the analytical hierarchical process. The result of the study strongly stipulates the presence of the problem of pedestrian facilities in Megenagna, Mexico, Urael Church, and Golagol which can affect the level of pedestrian safety. However, Denibel City, Legahare, Torhayloch, and National Theater sites have scored better Pedestrian level of service for the walking population. Finally, the study recommended the requirement of prior attention for the sites with very poor and poor pedestrian levels of service by the concerned sectors. [ABSTRACT FROM AUTHOR]

Jaywalking is an important cause of pedestrian-related automobile accidents. Exploring the factors that influence jaywalking behavior and suggesting appropriate improvement measures are critical for reducing automobile accidents involving pedestrians. This study divided traffic situations into high-risk and low-risk situations. Each situation contained three visual attention cues: vehicle, traffic light, and group behavior. Based on this, the role of visual cues in guiding pedestrians' attention and influencing their decisions during jaywalking was examined. Sixty participants, with an average age of 19, were recruited. They were shown 84 crosswalk videos randomly while their crossing decisions and eye movement data were recorded. In low-risk situations, pedestrians spent more attention on group behavioral cues when making jaywalking decisions. The rate of jaywalking increased with the number of other jaywalking pedestrians. In high-risk situations, the pedestrians' total fixation duration at vehicle hazard cues was longer when making jaywalking decisions, and the jaywalking rate decreased. The results indicate that pedestrians' jaywalking decisions were based on other pedestrians' illegal crossing cues and automatic associative processes in low-risk situations. The higher the number of people crossing the street, the higher the number of pedestrians illegally crossing the road. In high-risk situations, pedestrians paid more attention to vehicle hazard cues before making jaywalking decisions, and fewer illegal crossings. The jaywalking decisions were based on a risk assessment, a controlled analytical process. The results verify the effect of visual cues on pedestrians' attentional guidance and decision-making in different traffic situations, as well as the effectiveness of visual attention in predicting decision intention. The findings provide a theoretical basis and data reference for pedestrian safety education and constructing an intelligent driving pedestrian trajectory prediction model. [ABSTRACT FROM AUTHOR]

Hit-and-run crashes often have severe consequences for vulnerable road users. In light of governmental efforts to promote pedestrian-friendly urban environments, the significance of these crashes cannot be overstated. In this study, we assessed the factors that influence the injury severity of pedestrians involved in hit-and-run crashes in Ghana. Historical crash data (1469 observations) spanning from 2013 to 2020 was used in this study. An injury-severity model was developed using random parameters logit approach to assess what crash factors significantly affect the injury outcome of the crashes. It was observed that hit-and-run crashes that occur on dark and unlit roadways were more likely to result in fatal injuries. Also, female pedestrians were less likely to be killed in hit-and-run crashes. These findings provide the basis for developing and implementing appropriate countermeasures, such as punitive laws for drivers who leave the crash scene and protective laws for those who help their victims. [ABSTRACT FROM AUTHOR]

The purpose of this study is to determine the safety effectiveness of an intervention on an existing road by using predictive methods. Predictive methods allow the benefit of the intervention to be quantified in terms of crash reduction. Currently, the most widely used model is reported in the Highway Safety Manual, developed in the US. The HSM model is adapted to the Italian context through a calibration procedure. The model is then applied to two future scenarios: in the absence and presence of intervention. The redesign intervention consists of rehabilitating some road sections and constructing five tunnel bypasses to avoid crossing residential areas. The comparison between the 'with' and 'without' scenario estimated an overall reduction in the number of accidents of around 45%. The variant scenario is based on reasonable assumptions that allowed the determination of the proportion of traffic that will be diverted to the variant. In addition, several alternative future scenarios are considered to assess a possible different trend in assumed traffic distribution. Moreover, a possible overall increase or reduction in total traffic affecting the road is taken into account. The results showed that the intervention provided significant benefits even with increased traffic, proving the resilience of the intervention. [ABSTRACT FROM AUTHOR]

Pedestrians are the most vulnerable road users and they are highly susceptible to conflicts at mid-block cross-walk locations. They are prone to a high risk of injury from vehicular impact incidents and their decision making behaviour at unmarked cross-walks (UCWs) is more critical than at marked cross-walks (MCWs). The objective of this study was to determine level of safety thresholds and warrants for both marked and unmarked pedestrian crossing facilities at urban mid-block sections under mixed traffic conditions. Data were collected at MCWs and UCWs in four different locations in Trivandrum city, India. The crossing behaviours of pedestrians at both types of cross-walks were compared by analysing characteristics such as gap acceptance, a surrogate safety measure (post-encroachment time (PET)), waiting time, crossing time, platoon size, type of critical vehicle and critical gap. The multiple linear regression technique was used to develop gap acceptance models for MCWs and UCWs. The pedestrian level of safety (PLS) criterion is proposed; the PLS describes the safety of pedestrians at cross-walks and warrants for crossings based on PETs. The developed PLS thresholds and the pedestrian–vehicle interaction values were correlated to the PETs to develop the pedestrian crossing warrants. [ABSTRACT FROM AUTHOR]

This study aims to assemble and present the status of the published information available regarding pedestrian safety near crosswalks and bus stops through a comprehensive search of various databases. It focuses on the influence of crossing environment and bus stops, underlining land-use components, crosswalk quality, traffic control, placement of facilities, and other aspects of pedestrian crossing safety. It also offers a detailed discussion of various study designs and statistical modeling techniques implemented in this context over the years, followed by the suggested interventions to improve safety at such high-risk locations. The existing literature elucidates that traffic management strategies and designs have often prioritized the movement of motorized vehicles, resulting in higher risk to pedestrians. This is especially true for low- and middle-income countries. Also, previous research is mostly aligned with offering solutions with limited reference to the reported crash data. Thus, a holistic approach is needed to identify the contributing factors associated with fatal crashes, assess the safety performance at such locations, and thereby offer sustainable planning and design for pedestrian facilities. [ABSTRACT FROM AUTHOR]

• What is already known on this topic: During the early pandemic phase, some cities experienced a drop in nonfatal road traffic collisions but a surge in fatalities, potentially linked to increased speeding in lighter traffic with reduced law enforcement. • What this study adds : Over an extended period beyond the first year of the COVID-19 pandemic, the findings show a decrease in pedestrian injuries since April 2020, and an increase in non-MVC bicyclist injuries leading to more ED visits and hospitalizations. • How this study might affect research, practice or policy : Non-MVC bicyclist injuries increased, raising important questions for further investigation. Background : The COVID-19 pandemic altered traffic patterns worldwide, potentially impacting pedestrian and bicyclists safety in urban areas. In Toronto, Canada, work from home policies, bicycle network expansion, and quiet streets were implemented to support walking and cycling. We examined pedestrian and bicyclist injury trends from 2012 to 2022, utilizing police-reported killed or severely injured (KSI), emergency department (ED) visits and hospitalization data. Methods: We used an interrupted time series design, with injury counts aggregated quarterly. We fit a negative binomial regression using a Bayesian modeling approach to data prior to the pandemic that included a secular time trend, quarterly seasonal indicator variables, and autoregressive terms. The differences between observed and expected injury counts based on pre-pandemic trends with 95% credible intervals (CIs) were computed. Results: There were 38% fewer pedestrian KSI (95%CI: 19%, 52%), 35% fewer ED visits (95%CI: 28%, 42%), and 19% fewer hospitalizations (95%CI: 2%, 32%) since the beginning of the COVID-19 pandemic. A reduction of 35% (95%CI: 7%, 54%) in KSI bicyclist injuries was observed, but However, ED visits and hospitalizations from bicycle-motor vehicle collisions were compatible with pre-pandemic trends. In contrast, for bicycle injuries not involving motor vehicles, large increases were observed for both ED visits, 73% (95% CI: 49%, 103%) and for hospitalization 108% (95% CI: 38%, 208%). Conclusion: New road safety interventions during the pandemic may have improved road safety for vulnerable road users with respect to collisions with motor vehicles; however, further investigation into the risk factors for bicycle injuries not involving motor vehicles is required. [ABSTRACT FROM AUTHOR]

• Crash-related driver aberrant behaviours were explored based on an urban crash dataset. • Several relationships between other crash factors and driver aberrant behaviours were found. • A variability between different cities in the same country was found only for inattention crashes. • Crash factors affect the injury severity level of vehicle occupants and involved pedestrians. Introduction : Crash data analyses based on accident datasets often do not include human-related variables because they can be hard to reconstruct from crash data. However, records of crash circumstances can help for this purpose since crashes can be classified considering aberrant behavior and misconduct of the drivers involved. Method: In this case, urban crash data from the 10 largest Italian cities were used to develop four logistic regression models having the driver-related crash circumstance (aberrant behaviors: inattentive driving, illegal maneuvering, wrong interaction with pedestrian and speeding) as dependent variables and the other crash-related factors as predictors (information about the users and the vehicles involved and about road geometry and conditions). Two other models were built to study the influence of the same factors on the injury severity of the occupants of vehicles for which crash circumstances related to driver aberrant behaviors were observed and of the involved pedestrians. The variability between the 10 different cities was considered through a multilevel approach, which revealed a significant variability only for the inattention-related crash circumstance. In the other models, the variability between cities was not significant, indicating quite homogeneous results within the same country. Results: The results show several relationships between crash factors (driver, vehicle or road-related) and human-related crash circumstances and severity. Unsignalized intersections were particularly related to the illegal maneuvering crash circumstance, while the night period was clearly related to the speeding-related crash circumstance and to injuries/casualties of vehicle occupants. Cyclists and motorcyclists were shown to suffer more injuries/casualties than car occupants, while the latter were generally those exhibiting more aberrant behaviors. Pedestrian casualties were associated with arterial roads, heavy vehicles, and older pedestrians. [ABSTRACT FROM AUTHOR]

• Survey study (N = 1011) on sign messaging and design for pedestrian-rail crossings. • Action-conveying and emotionally-motivated more effective than information signs. • Square and black on yellow signs perceived as most effective in conveying safety. • Pedestrians who frequently cross railroad tracks exhibit higher risk-taking tendencies. • Relationship between likelihood to walk across tracks and risk-taking propensity. Introduction : Train-pedestrian conflicts result in a substantial number of serious and fatal injuries annually. Signs indicating safe and permissible behaviors near railroad rights of way are commonly relied upon to mitigate collisions. However, the effectiveness of these signs in preventing accidents often depends on clarity and interpretation of the sign. The objective of this study was to evaluate the (1) effectiveness of sign messaging strategies and designs at pedestrian-railroad crossings, and (2) effects of context and risk-taking propensity on decisions to cross tracks. Method : A survey study (N = 1011) was conducted comparing likeliness to cross for a variety of pedestrian-railroad scenarios. The DOSPERT scale was included to estimate an individuals' risk-taking. Results : Findings reveal that action-conveying and emotionally-motivated signs are more effective in discouraging railroad crossing in high-risk situations (i.e., train present, crossing gates down, or warning lights flashing), compared to information-only signs. However, decisions to cross are primarily influenced by the presence of a train and crossing gates' status, followed by sign type. MaxDiff analysis show that yellow signs with black symbols and square shaped signs are perceived as the clearest in conveying safety information, compared to black on white, red on white, and circular signs. Additionally, individuals who cross railroad tracks as pedestrians more frequently exhibit higher risk-taking tendencies, while there is no relationship between driving across tracks and risk-taking propensity. Males and younger individuals also have higher risk-taking tendencies. Conclusions and Practical Applications : These findings have implications for policy and practice, such as revising manuals to incorporate more effective sign designs and targeted educational campaigns for high-risk groups. It is also crucial to conduct ongoing monitoring of implemented interventions, which could follow the framework presented in this paper. The study emphasizes collaboration across sectors to improve overall safety at pedestrian-railroad crossings, contributing to safer transportation infrastructure for all. [ABSTRACT FROM AUTHOR]

The prediction of pedestrian trajectory is conducive to reducing traffic accidents and protecting pedestrian safety, which is crucial to the task of intelligent driving. The existing methods mainly use the past pedestrian trajectory to predict the future deterministic pedestrian trajectory, ignoring pedestrian intention and trajectory diversity. This paper proposes a multimodal trajectory prediction model that introduces pedestrian intention. Unlike previous work, our model makes multi-modal goal-conditioned trajectory pedestrian prediction based on the past pedestrian trajectory and pedestrian intention. At the same time, we propose a novel Gate Recurrent Unit (GRU) to process intention information dynamically. Compared with traditional GRU, our GRU adds an intention unit and an intention gate, in which the intention unit is used to dynamically process pedestrian intention, and the intention gate is used to control the intensity of intention information. The experimental results on two first-person traffic datasets (JAAD and PIE) show that our model is superior to the most advanced methods (Improved by 30.4% on MSE0.5s and 9.8% on MSE1.5s for the PIE dataset; Improved by 15.8% on MSE0.5s and 13.5% on MSE1.5s for the JAAD dataset). Our multi-modal trajectory prediction model combines pedestrian intention that varies at each prediction time step and can more comprehensively consider the diversity of pedestrian trajectories. Our method, validated through experiments, proves to be highly effective in pedestrian trajectory prediction tasks, contributing to improving traffic safety and the reliability of intelligent driving systems. [ABSTRACT FROM AUTHOR]

The notion of "spatial vulnerability" is present in most disaster studies with a strong geographical connotation and accordingly is adopted at all scales, including the urban. While enabling mapping and visualizing risk patterns at macroscales, this geocentric foundation fails to capture disaster risk dynamics associated with the urban spatial network—an element that plays a significant role in the everyday and emergency functioning of cities, enabling users' movement and interaction. Yet, urban vulnerability assessment overlooks this aspect and thus leaves urban disaster risk mechanisms partially unexplored. This study investigated the role of the network of urban public open spaces (UPOS) in the creation and progression of urban disaster risk in earthquake-prone settlements. Through a multimethod approach that integrates quantitative and qualitative methods and explores spatial configuration, planning policies, and practices of use of UPOS in everyday and emergency scenarios, our study demonstrated that UPOS configuration plays an active role in urban disaster risk. Urban public open spaces impact risk by influencing the exposure of pedestrians and their capacity for self-protection. The study further reconceptualized spatial vulnerability at the urban scale, as the fraction of vulnerability associated to the spatial network, highlighting the interplay of planning policies and spatial practices in its production and progression. Our findings make the notion of spatial vulnerability less ambiguous at the urban scale, by viewing the variable as an imbalance in capacities and exposure that generates spatially unsafe conditions. This refined conceptualization of spatial vulnerability becomes a lens for a more granular approach to urban disaster risk reduction and city planning by identifying and integrating sociospatial considerations. [ABSTRACT FROM AUTHOR]

The advent of the sixth-generation (6G) wireless communication technology brings forth immense opportunities for enhancing Intelligent Transportation Systems (ITS). We investigate the potential of 6G in revolutionizing transportation systems by analyzing the standards, technologies, and challenges associated with its implementation. Building upon the advancements of 5G, 6G introduces unprecedented capabilities, including ultra-high data rates, ultra-low latency, massive connectivity, and intelligent network orchestration. Leveraging these capabilities, 6G can facilitate seamless connectivity among vehicles, infrastructure, and pedestrians, enabling novel applications such as autonomous driving, smart traffic management, and cooperative collision avoidance. However, realizing the full potential of 6G for ITS entails addressing several challenges, including spectrum allocation, network security, resource management, and interoperability with existing infrastructures. We present a comprehensive overview of the latest developments in 6G standards and technologies, including mmWave communications, terahertz spectrum, visible light communication, Artificial Intelligence, and edge computing, emphasizing their relevance to ITS. We also describe these technologies in the context of ITS. Furthermore, we explore the potential benefits and impacts of 6G on transportation systems, highlighting the opportunities for improved safety, efficiency, and sustainability. Finally, we conclude by discussing the key challenges and research directions that must be addressed to effectively deploy 6G for ITS, thereby paving the way for the next generation of intelligent and connected transportation systems. [ABSTRACT FROM AUTHOR]

Traffic-related pedestrian deaths in the United States reached a 40-year high in 2021. Each year, pedestrians also suffer nonfatal traffic-related injuries requiring medical treatment. Near real-time emergency department visit data from CDC's National Syndromic Surveillance Program during January 2021-December 2023 indicated that among approximately 301 million visits identified, 137,325 involved a pedestrian injury (overall visit proportion = 45.62 per 100,000 visits). The proportions of visits for pedestrian injury were 1.53-2.47 times as high among six racial and ethnic minority groups as that among non-Hispanic White persons. Compared with persons aged =65 years, proportions among those aged 15-24 and 25-34 years were 2.83 and 2.61 times as high, respectively. The visit proportion was 1.93 times as high among males as among females, and 1.21 times as high during September-November as during June-August. Timely pedestrian injury data can help collaborating federal, state, and local partners rapidly monitor trends, identify disparities, and implement strategies supporting the Safe System approach, a framework for preventing traffic injuries among all road users. [ABSTRACT FROM AUTHOR]

Large passenger vehicles have consistently demonstrated an outsized injury risk to pedestrians they strike, particularly those with tall, blunt front ends. However, the specific injuries suffered by pedestrians in these crashes as well as the mechanics of those injuries remain unclear. The current study was conducted to explore how a variety of vehicle measurements affect pedestrian injury outcomes using crash reconstruction and detailed injury attribution. We analyzed 121 pedestrian crashes together with a set of vehicle measurements for each crash: hood leading edge height, bumper lead angle, hood length, hood angle, and windshield angle. Consistent with past research, having a higher hood leading edge height increased pedestrian injury severity, especially among vehicles with blunt front ends. The poor crash outcomes associated with these vehicles stem from greater injury risk and severity to the torso and hip from these vehicles' front ends and a tendency for them to throw pedestrians forward after impact. The combination of vehicle height and a steep bumper lead angle may explain the elevated pedestrian crash severity typically observed among large vehicles. [ABSTRACT FROM AUTHOR]

This study explored differences in patient characteristics, injury characteristics, treatment modalities, and treatment outcomes among patients who presented to the Emergency Department (ED) following traffic crashes during the COVID-19 period (from March 15, 2020 to March 15, 2022) in comparison to the previous corresponding period between 2017 and 2019. The study is a retrospective chart review study. The study included a random sample of 610 patients who presented to the ED of a major hospital located in northern-central Israel following traffic crashes: 305 patients who presented during the COVID-19 period (from March 15, 2020 to March 15, 2022) and 305 patients who presented during the previous corresponding period (from March 15, 2017 to March 15, 2019). Socio-demographic data, data regarding the traffic crashes, and medical data of the patients were collected from their medical records, and the data were compared. In the context of the COVID-19 period, a notable surge in the percentage of cyclist victims was evident, marking an increase from 7.5% to 19% compared to the corresponding period. Conversely, the incidence of pedestrian victims during the COVID-19 period dropped to 19.7%, in contrast to 30.8% in the corresponding period. Notably, patients involved in pedestrian crashes amid the COVID-19 period exhibited a shorter hospital stay (M = 2.8 days, SD = 3.3) compared to the corresponding period (M = 4.3 days, SD = 7.1) [t = 1.8 (df = 141), p < 0.05]. However, a higher fatality rate was observed among these patients during the COVID-19 period compared to the corresponding period (6.7% vs. 0%) [χ2 = 6.4 (df = 1), p < 0.05]. The study reveals significant changes in traffic crashes characteristics during the pandemic period, including a notable increase in cyclist victims and a decrease in pedestrian incidents. These shifts may be attributed to factors such as changes in transportation patterns, increased use of bicycles for essential travel. Despite these changes, the proportion of severe crashes remained relatively consistent. These findings underscore the importance of understanding the underlying causes behind these shifts and highlight the ongoing need for public education and awareness initiatives to promote traffic safety, particularly for vulnerable road users, during pandemic periods. [ABSTRACT FROM AUTHOR]

Ensuring pedestrian safety is one of the most significant challenges for autonomous driving systems in urban scenarios due to the non-cooperative and unpredictable nature of pedestrian movements. To tackle this problem, firstly, we propose a collision avoidance strategy based on entropy-increasing risk perception in a vehicle–pedestrian reaction space. Our approach combines a limited range of reaction space regions with entropy to quantify the risk of pedestrian–vehicle collision. Then, multi-vehicle candidate trajectories are generated using the path and speed sequence method, and the uncertain states of pedestrians are predicted based on the social force model and Markov model accordingly. Finally, to determine the optimal collision avoidance trajectory, we use quantitative reaction-space entropy as a new "cost function" to measure potential risk and perform multi-objective trajectory optimization based on the elitist non-dominated-sorting genetic algorithm region-focused (NSGA-RF) approach. Simulation results show that our proposed strategy can enhance the safety of the planned trajectory interaction between vehicles and pedestrians for autonomous driving under normal and emergency conditions. [ABSTRACT FROM AUTHOR]

This study presents a thorough numerical evaluation of the crashworthiness properties of a new bio-inspired DNA tubes (BIDNATs) with circular, elliptical, and rectangular cross-sections. Deformation and crashworthiness behaviors are evaluated using axial quasi-static crushing simulations by ABAQUS/Explicit (Abaqus 6.14, https://www.3ds.com/products-services/simulia/products/abaqus/). The study compares the performance of conventional tubes with rectangular and elliptical cross-sections to DNA-inspired tubes. Increasing the rotation angle leads to more helices and a pronounced helix angle, resulting in lower initial peak force (IPF). However, lower cross-section aspect ratios generally have higher IPF and specific energy absorption (SEA) values. BIDNATs with rectangular cross-sections and a 540° rotation angle have the lowest SEA and IPF values across all aspect ratios. Notably, for the 110/100 aspect ratio, the SEA of E110/100 is 71% higher than the conventional tube. Overall, BIDNATs with elliptical cross-sections and a 360° rotation angle exhibit higher SEA values and lower IPF values, particularly for a width (W) of 100 mm. Conventional circular and elliptical tubes generally have SEA values exceeding 6 J/g, with only E110/100 surpassing this among DNA-inspired tubes. The NE110/100 tube has the highest SEA, surpassing E110/100 by 54%, while its IPF is 10% greater than DNA-inspired E110/100. It's worth noting that conventional circular and elliptical tubes have higher IPF values compared to their DNA-inspired counterparts. These findings offer valuable insights for engineers and researchers in the design of crash tubes to improve overall vehicle safety for both occupants and pedestrians. [ABSTRACT FROM AUTHOR]

The reduction in the effective dose of evacuated injured persons through contaminated areas of nuclear accidents is an essential emergency services requirement. In this context, there appeared a need to develop a dose-optimised route finding method for firefighting rescue vehicles, which includes the development of a real-time decision support measurement and evaluation system. This determines and visualises the radiation exposure of possible routes in a tested area. The system inside and outside of the vehicle measures the ambient dose equivalent rate, the gamma spectra, and also the airborne radioactive aerosol and iodine levels. The method uses gamma radiation measuring NaI(Tl) scintillation detectors mounted on the outside of the vehicle, to determine the dose rate inside the vehicle using the previously recorded attenuation conversation function, while continuously collecting the air through a filter and using an alpha, beta, and gamma radiation measuring NaI(Tl)+ PVT + ZnS(Ag) scintillator to determine the activity concentration in the air, using these measured values to determine the effective dose for all routes and all kinds of vehicles. The energy-dependent shielding effect of the vehicle, the filtering efficiency of the collective protection equipment, and the vehicle's speed and travel time were taken into account. The results were validated by using gamma point sources with different activity and energy levels. The measurement results under real conditions and available real accident data used in our simulations for three different vehicles and pedestrians proved the applicability of the system. During a nuclear accident based on our model calculations, the inhalation of radioactive aerosols causes a dose almost an order of magnitude higher than the external gamma radiation caused by the fallout contamination. The selection of the appropriate vehicle and its route is determined by the spectrum that can be measured at the accident site but especially by the radioactive aerosol concentration in the air that can be measured in the area. In the case of radiation measuring detectors, the shielding effect of the carrier vehicle must be taken into account, especially in the case of heavy shielding vehicles. The method provides an excellent opportunity to reduce the damage to the health of accident victims and first responders during rescue operations. [ABSTRACT FROM AUTHOR]

The location of curb ramps, crosswalk markings, and curb radius are important contributors to pedestrian safety at intersections, particularly for conflicts and crashes involving right turns. Drivers tend to have higher turning speeds at locations with larger curb radii, which also requires greater stopping sight distance. If the crosswalk is placed further away from the intersection corner (i.e., offset or setback from the intersection corner), it could potentially provide drivers better visibility of pedestrians and increase the available stopping distance. However, no study has previously been conducted to investigate the relationship between crosswalk location and curb radius. This paper presents the results of research that quantifies the relationship between the offset of crosswalks (setback crosswalk) and indirect safety measures (driver stopping, yielding, and speed selection) at intersections with the consideration of other characteristics during simulated driving. The study included field-based observations and driving simulator experiments. A driving simulator experiment with 50 participants was conducted to determine how setback distances, sharpness of curb radii, and presence of pedestrians affect driver stopping decision and position, and speed choice. Approximately 12 h of video (7:00 a.m.-7:00 p.m.) were collected at nine study sites that closely matched the designs tested in the driving simulator. Comparisons of drivers' speed in a similar scenario obtained from field and simulator data were performed to benchmark the observations from the driving simulator against field data. Stop line speeds were found to be consistent between experiments and turning speeds were found to be slightly higher in the driving simulator experiment. The research results suggest that curb radius should be smaller [less than 9 m (30 ft)] to control driver speed. Additionally, a setback distance of 6 m (20 ft) is a suitable upper bound for crosswalk placement when reconstructing intersections. [ABSTRACT FROM AUTHOR]

Background: The number of accidents due to distracted pedestrian is on the rise and many governments and institutions are enacting public policies which restrict texting while walking. However, pedestrians do more than just texting when they use their mobile devices on the go. Objective: Exploring pedestrian multitasking, this paper aims to examine the effects of mobile device task type on pedestrian performance outcomes. Method: We performed two studies in lab simulations where 78 participants were asked to perform different tasks on a mobile device (playing a game, reading, writing an email, texting one person, group texting) while performing a pedestrian visual discrimination task while either standing or walking on a treadmill. Behavioral performance as well as neurophysiological data are collected. Results: Results show that compared to a no-phone control, multitasking with any of the tasks on a mobile device leads to poor performance on a pedestrian visual discrimination task. Playing a game is the most cognitively demanding task and leads to the greatest performance degradation. Conclusion: Our studies show that multitasking with a mobile device has the potential to negatively impact pedestrian safety, regardless of task type. However, the impacts of different mobile device tasks are not all equivalent. More research is needed to tease out the different effects of these various tasks and to design mobile applications which effectively and safely capture pedestrians' attention. Application: Public policy, infrastructure, and smart technologies can be used to mitigate the negative effects of mobile multitasking. A more thorough understanding of mobile device task-specific factors at play can help tailor these counter-measures to better aid distracted pedestrians. [ABSTRACT FROM AUTHOR]