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Traffic violation is one of the leading causes of traffic crashes. In the context of global aging, it is important to study traffic violations by elderly drivers for improving traffic safety in preparation for a worldwide aging population. In this study, a hybrid approach of Latent Class Analysis (LCA) and XGBoost based SHAP is proposed to identify hidden clusters and to understand the key contributing factors on the severity of traffic violations by elderly drivers, based on the police-reported traffic violation dataset of Beijing (China). First, LCA is applied to segment the dataset into several latent homogeneous clusters, then XGBoost based SHAP is established on each cluster to identify feature contributions and the interaction effects of the key contributing factors on the severity of traffic violations by elderly drivers. Two comparison groups were set up to analyze factors, which are responsible for the different severities of traffic violations. The results show that elderly drivers can be classified into four groups by age, urban or not, license, and season; factors such as less annual number of traffic violations, national & provincial highway, night and winter are key contributing factors for higher severity of traffic violations, which are consistent with common cognition; key contributing factors for all clusters are similar but not identical, for example, more annual number of traffic violations contribute to more severe violation for all clusters except for Cluster 2; some factors which are not key contributing factors may affect the severity of traffic violations when they are combined with other factors, for example, the combination of lower annual number of traffic violations and county & township highway contributes to more severe violation for Cluster 1. These findings can help government to formulate targeted countermeasures to decrease the severity of traffic violations by specific elderly groups and improve road service for the driving population. [ABSTRACT FROM AUTHOR]

Trade-offs are central to life history theory and play a role in driving life history diversity. They arise from a finite amount of resources that need to be allocated among different functions by an organism. Yet covariation of demographic rates among individuals frequently do not reflect allocation trade-offs because of variation in resource acquisition. The covariation of traits among individuals can thus vary with the environment and often increases in benign environments. Surprisingly, little is known about how such context-dependent expression of trade-offs among individuals affect population dynamics across species with different life histories. To study their influence on population stability, we develop an individual-based simulation where covariation in demographic rates varies with the environment. We use it to simulate population dynamics for various life histories across the slow-fast pace-of-life continuum. We found that the population dynamics of slower life histories are relatively more sensitive to changes in covariation, regardless of the trade-off considered. Additionally, we found that the impact on population stability depends on which trade-off is considered, with opposite effects of intraindividual and intergenerational trade-offs. Last, the expression of different trade-offs can feed back to influence generation time through selection acting on individual heterogeneity within cohorts, ultimately affecting population dynamics. [ABSTRACT FROM AUTHOR]

In the realm of conditionally automated driving, understanding the crucial transition phase after a takeover is paramount. This study delves into the concept of post-takeover stabilization by analyzing data recorded in two driving simulator experiments. By analyzing both driving and physiological signals, we investigate the time required for the driver to regain full control and adapt to the dynamic driving task following automation. Our findings show that the stabilization time varies between measured parameters. While the drivers achieved driving-related stabilization (winding, speed) in eight to ten seconds, physiological parameters (heart rate, phasic skin conductance) exhibited a prolonged response. By elucidating the temporal and cognitive dynamics underlying the stabilization process, our results pave the way for the development of more effective and user-friendly automated driving systems, ultimately enhancing safety and driving experience on the roads. [ABSTRACT FROM AUTHOR]

In 1996, the Supreme Court announced in Whren v. United States that a traffic stop is constitutional if there is probable cause to believe a traffic infraction has occurred. So long as the officers who stop an individual can point--even after the fact--to any violation of the traffic laws, their actual, subjective motivations for initiating a stop are legally irrelevant. Case-by-case determination of reasonableness is unnecessary in the traffic stop context, the Court concluded, because the balancing of interests has already been done. Unlike warrantless entries into homes, the use of deadly force, or unannounced warranted entries, a traffic stop is not an "extreme practice," and therefore the existence of probable cause invariably outweighs an individual's interest in avoiding police contact. In this Article, I argue that the Court was half right in Whren: there is little need for case-by-case adjudication of the reasonableness of traffic stops. Given that the government interest in these stops is relatively low, that such stops can result in harm to both the officer and those stopped, and that other, less intrusive means are nearly always available to serve the government's stated interest in traffic enforcement, courts should presume that the use of sworn officers to conduct traffic stops is unreasonable. While there may be some situations in which the use of armed police officers to make traffic stops is reasonable, the government should bear the burden of demonstrating that fact in each individual case. This straightforward legal change would significantly reduce needless police stops, thereby increasing overall safety for both officers and the public. [ABSTRACT FROM AUTHOR]

• Traffic, vehicle type, platoon, and pavement condition influenced passing distance. • Vehicles with opposing traffic passed the bicyclist significantly closer. • The Log-normal distribution was found to best fit lateral passing distance. • Bicyclist risk estimates contribute to assess the implementation of countermeasures. • Minimum passing distance should be mandated according to urban and rural areas. In the United States, 91.4 cm (3.0 ft) has been considered a safe lateral distance when passing bicyclists; however, this threshold may be more suitable to urban environments where most bicycle safety research has originated—limited research is available on rural roadways. In this study, a road bicycle was instrumented to collect naturalistic data and analyze vehicle-bicycle lateral passing distances (LPD) on high-speed rural two-lane roadways with paved shoulders. The bicycle was ridden in the center of the shoulder. Overall, 2,119 observations of vehicles passing the instrumented bicycle were obtained from a study segment. The impacts of different variables on distributions of vehicle-bicycle LPD measurements were analyzed. Passing vehicles with opposing traffic passed the bicyclist significantly closer than passing vehicles without opposing traffic. More predominant with opposing traffic, heavy vehicles passed the bicyclist closer than passenger vehicles. Similarly, following vehicles passed the bicyclist closer than leading vehicles. The study segment was repaved during the data collection period, so data before and after the roadway improvement was available. Vehicles with old pavement/marking passed the bicyclist closer than vehicles with new pavement/marking conditions. Distribution of LPD measurements was skewed to the left towards smaller values and had a long tail to the right towards larger values. Through maximum likelihood estimation, the Log-normal distribution was found to best fit the data distribution. Using empirical and theoretical density distributions, LPD was formally specified as a function of opposing traffic with a theoretical mixture distribution and generalized to estimate the probability of vehicles passing bicyclists below a certain threshold. [ABSTRACT FROM AUTHOR]

• We provide a list of road elements that may reduce driving speed for inner and outer city roads. • We provide a new method to estimate the effects of road measures on driving speed. • We show that the lay-out of the environment immediately generates an estimation of a credible speed choice. • The results are consistent with the notion of Self-Explaining Roads. One of the leading principles for road design is the notion of Self-Explaining Roads (SER). According to this notion, the design and layout of the road environment should automatically elicit behavior that is appropriate for that type of road. The current study investigated the effects of the road environment (i.e., the presence of particular road elements such as the presence/absence of edge lines, and a physical separation between driving lanes) on driving speed choice in the Netherlands for roads in- and outside the city limits (ICL and OCL). A total of 462 participants (all car drivers) were exposed to either 152 ICL or 152 OCL pictures of road environments for either a short (300 ms in Experiment 1, 200 ms in Experiment 2) or long duration (1500 ms) and indicated as fast as possible which speed they would drive given the road environment they viewed. All images were labeled with respect to the presence or absence of particular road elements. A linear mixed model was used to determine the effects of road elements on speed choice and response time. The results showed that the presence of certain road elements impacted the speed chosen. For example, inside the city limits, relative to no bicycle lane, a bicycle lane painted on the road reduced driving speed while a separate bike lane increased the speed chosen. Also, central line markings (relative to no line marking) and a road made of asphalt (relative to pavers) were associated with higher speeds. Outside city limits, having multiple lanes (versus one lane) was related to higher speeds and having two driving directions without separation (versus a one-way road) was related to lower speed choices. Importantly, exposure duration (200 /300 ms versus 1500 ms) only had a marginal effect, indicating that road users generally only need a brief glimpse of the road to be able to decide what speed to drive. Consistent with the principles of SER, we conclude that categorization and the associated speed decision is fast, operating within a single glance and is impacted by the road elements present in the environment. Finally, we believe our method constitutes a valuable tool in road design, as it allows one to efficiently and effectively gauge the impact of various road elements in large population samples. [ABSTRACT FROM AUTHOR]

• We examined the impact of peer presence on adolescent pedestrian risk-taking intentions whereby a traffic scenario-based experimental research. • Adolescents' behavioral intentions in traffic were safer when there were peers present than when there were no peers present. • Adolescents were less safe when crossing the street with familiar peer(s) than with unfamiliar peer(s). • Peer familiarity didn't effect adolescents' safety when walking on the sidewalk. • Adolescents' safety in traffic was higher with multiple familiar peers than with multiple unfamiliar peers. Adolescence is a high-risk period for traffic injury. One factor that may impact adolescent safety in traffic is the presence of peers. We conducted a quasi-experimental research study to examine the impact of peer presence, peer familiarity, and peer group size on adolescent pedestrian risk-taking intentions in both sidewalk and street-crossing settings. 607 students aged 12–18 years from Nantong city, China, completed a questionnaire that presented 20 traffic scenarios. The scenarios varied based on a 3 (peer group size: no peer vs. one peer vs. multiple peers) x 2 (peer familiarity: familiar vs. unfamiliar) x 2 (traffic setting: crossing the street vs. walking on the roadside) experimental design. Adolescents' responses indicated safer vs riskier intentions in each situation. (1) Adolescents were safer when walking on the sidewalk than when crossing the street; (2) Whether crossing the street or walking on the sidewalk, adolescents' behavioral intentions were safer when there were peers present than when there were no peers present; (3) Adolescents' safety tended to be higher overall with unfamiliar peers than with familiar peers; (4) Adolescents were less safe when crossing the street with familiar peer(s) than with unfamiliar peer(s), but no differences emerged when walking on the sidewalk. Adolescents report safer behavior when walking with a peer or peers compared with walking alone. Familiar peers reduce adolescents' safety of behavior intentions in traffic, especially when crossing the street. [ABSTRACT FROM AUTHOR]

• Vehicle, cyclist & pedestrian count data from 44 neighboring or collocated stations were analyzed. • Pre & post-pandemic datasets showed pattern changes due to Covid-19 restrictions were mode-specific. • Land-use restrictions and altered trip purposes impacted daily and weekly travel patterns. • Cross-correlation, clustering, and Bayesian change-point analyses showed congruent inferences. • Timeline of pandemic restrictions could be matched using statistical analyses on traffic counts. The spread of Covid-19 and implementation of various restrictions changed how and why people travel. The present study analyzed three different modes of transportation, to understand the impact of Covid-19 mobility and land-use restrictions on chosen neighbourhoods in Dublin City, Ireland. Classification analysis, Spatial correlation analysis, and Bayesian change point analysis had been conducted using vehicle, cyclist & pedestrian count data from 44 neighbouring or collocated stations to explore the statistical changes in the traffic system characteristics. Apart from reduction in traffic counts, the other impacts were modal shift, rise in cyclist numbers, and similarity between weekday & weekend patterns observed. Analyses could identify that changes in the statistical aspects of traffic system are congruent with the changes in lockdown measures. Overall, this study presented a set of tools to identify the existence and degree of changes in traffic patterns over time due to any mobility or land-use policy changes. [ABSTRACT FROM AUTHOR]

Wildlife roadkill studies need to cope with a mismatch among recorded carcasses and actual road mortality, because of the existence of three biases: crippling, carcass‐persistence, and observer bias. Here, we focused on the often overlooked crippling bias, suggesting that it should be called carcass‐location bias and disentangling the related three possible outcomes for affected wildlife: injured animal escaping and dying away from road, animal rebounding off the road after vehicle collision, and animal retained by vehicle. Such outcomes can probably be affected by different species traits, and, in order to make a first evaluation of this hypothesis, we opportunistically collected 150 direct observations on the ultimate fate of roadkilled vertebrates. Approximately one third of them were affected by carcass‐location bias, so extremely difficult to be recorded through typical roadkill surveys, entailing a considerable and overlooked source of error for roadkill studies and mitigation actions based on them. [ABSTRACT FROM AUTHOR]

We test whether the presence of police body-worn camera (BWC) evidence impacts case filing, processing, and outcomes, using data from over 50,000 misdemeanor cases charged in the Tempe, Arizona municipal city court (2014–2017). BWCs did not affect case flow but did affect processing and outcomes for most cases. Traffic and drug/alcohol cases involving a BWC were processed more quickly, while traffic and person offense cases with a BWC were less likely to be adjudicated guilty. Defendant and officer demographics were correlated with case processing time and outcomes, but BWCs did not reduce racial/ethnic disparities for any outcomes. BWCs appear to affect case processing and outcomes for some case types, but effects are not straightforward and warrant further research. [ABSTRACT FROM AUTHOR]

The article explains the importance of enforcing minor traffic violations for public safety. Topics discussed include the Fourth Amendment and traffic stops, inconsistencies in traffic enforcement, measures taken by jurisdictions to restrict law enforcement from pursuing minor traffic offenses, benefits that accompany enforcement of traffic violations, and alternative reforms suggested for implementation to address racial disparity in traffic enforcement and policing practices.

A railway level crossing is a risk area despite installations of the warning signal and arm gate that indicate a train approach. Accidents may nevertheless occur if vehicle drivers violate or fail to conform to the rules. Such action is considered a risk behavior that may cause severe collision, injury, and death. Thus, the driver behaviors are the key factors causing accidents. The objective of this study was thus to investigate the risk behaviors and the factors influencing above behaviors. These behaviors were recorded by a high-resolution video camera and the initial data analysis was based on descriptive statistics. An in-depth analysis of the factors influencing the risk behaviors was performed by using Pearson Chi-square technique and Binary Logistic Regression Analysis. The results showed that the railway crossing behaviors of more than half of the drivers under the study were the risk-taking, followed by opportunistic violation. Most violations occurred during the beginning of the warning signal. Overall, the motorcycle riders were found to be the group with greater chance of violating across the railway during the warning signal than the 4-wheeled vehicle drivers. Especially, during the period between the beginning of the warning signal and the complete arm gate closure, as well as the greater width of the crossing road. This could be due to the higher agility and evasive capability of motorcycle riders than 4-wheeled drivers. Additionally, this study recommends approaches to initially prevent or reduce this risky behavior and can serve as a guideline for enhancing areas with physical characteristics similar to the study area. [ABSTRACT FROM AUTHOR]

• KDE and DBSCAN were used in spatial distribution analysis of ICH. • The overall and various types of ICH in the YRB showed a agglomeration distribution. • ICH mainly concentrated in the middle-lower reaches and cultural areas of the YRB. • Socioeconomic factors had the most significant influence on the distribution of ICH. Given the background of ecological protection and high-quality development strategies in the Yellow River Basin (YRB), studying the spatial distribution characteristics and influencing mechanisms of intangible cultural heritage (ICH) in the YRB is of great significance for objectively understanding the entire process of cultural occurrence, evolution, protection, and development in the YRB. Considering 787 counties in nine provincial areas of the YRB as the research area, this study adopted density-based spatial clustering of applications with noise (DBSCAN), kernel density estimation (KDE), and GeoDetector, and explored the spatial distribution characteristics and influencing mechanisms of 892 national-level ICH items. The results showed that the entire ICH was spatially agglomerated in the YRB. Concurrently, regional differences were apparent, mainly concentrated in the middle–lower reaches and several cultural areas. Although all 10 ICH types showed spatial gathering characteristics, the degree of agglomeration of folk art and literature, traditional sports recreation, and acrobatics was relatively low. DBSCAN clustering showed that the middle and lower reaches of the Yellow River were the core areas of ICH and various types of ICH clustering. The kernel density also showed an agglomeration distribution trend and formed a "3 + 4 + 5" kernel density hierarchy, exhibiting prominent "center–periphery" characteristics. Among the natural environmental, socioeconomic, and historical–cultural factors, the socioeconomic factors significantly affected ICH spatial distribution, whereas natural environmental factors were less influential. The gross domestic product (GDP), national historical and culturally famous towns and villages, populations, and museums strongly influenced ICH spatial distribution. The factor interaction explanatory force was greater than that of a single factor, indicating synergistic effects between the factors. The explanatory force of GDP, urbanization level, population, minority population, and traffic interaction with other factors on ICH spatial distribution significantly improved. [ABSTRACT FROM AUTHOR]

Road traffic mortalities (RTMs) and injuries are among the leading causes of human fatalities worldwide, particularly in low-and middle-income countries like Iran. Using an interrupted time series analysis, we investigated three interventional points (two government-mandated fuel price increases and increased traffic ticket fines) for their potential relation to RTMs. Our findings showed that while the overall trend of RTMs was decreasing during the study period, multiple individual provinces showed smaller reductions in RTMs. We also found that both waves of government-mandated fuel price increases coincided with decreases in RTMs. However, the second wave coincided with RTM decreases in a smaller number of provinces than the first wave suggesting that the same type of intervention may not be as effective when repeated. Also, increased traffic ticket fines were only effective in a small number of provinces. Potential reasons and solutions for the findings are discussed in light of Iran's Road Safety Strategic Plan. [ABSTRACT FROM AUTHOR]

Drawing on the core idea of Propensity Score Matching, this study proposes a new concept named Historical Traffic Violation Propensity to describe the driver's historical traffic violations, and combines the new concept with an improved mutual information-based feature selection algorithm to construct a method for screening key traffic violations from the perspective of expressing driver's accident risk. The validation analysis based on the real data collected in Shenzhen demonstrated that drivers' state of Historical Traffic Violation Propensity on 19 key traffic violations screened have a stronger predictive ability of their subsequent accidents compared to the level in existing research. The positive state of Historical Traffic Violation Propensity on 'Drinking', 'Parking in dangerous areas', 'Wrong use of turn lights', 'Violating prohibited and restricted traffic regulations', and 'Disobeying prohibition sign' will increase the probability of a driver's subsequent accident by more than 1.7 times. The research provides directions to more efficiently and accurately capture the driver's accident risk through historical traffic violations, which is valuable for identifying high-risk drivers as well as the key psychological or physical risk factors that manifest in daily driving activities and lead to subsequent accidents. [ABSTRACT FROM AUTHOR]

• The orchids plant diversity is assessed in the western Himalaya of Pakistan. • Orchids plant species are linked to seven distinct vegetation types. • Relatively moist and moderately warm microhabitats are important. • The higher relative abundance of woody plant species support orchids. • Increasing deforestation will affect the orchids diversity and abundance. Orchid species require unique microhabitat conditions and are globally distributed from the tropics to alpine regions. These plant species are important both ecologically and economically but are facing multiple threats, especially habitat destruction, climate change, and overexploitation. Therefore, documenting species richness, diversity, distribution, and important driving factors is crucial for biodiversity conservation. The orchid species distribution patterns and order of importance of the main driving environmental factors in the western Himalayas of Azad Jammu and Kashmir remain unclear. The main aims of this study were to explore the richness and distribution of orchids and neighboring vascular flora and to identify the principal driving environmental factors, as no study has yet targeted these plant species specifically in the study area. Field data collection surveys were conducted from August 2018 to July 2021 using the vegetation sampling method. The presence of ≥ two individuals belonging to any orchid species in a 20 × 20 m² land area criterion was used to select the study sites along the elevation gradient for data collection. Multivariate statistical tools, such as hierarchical classification and ordination, were used to analyze the data. A total of 32 orchid species belonging to 18 different Orchidaceae genera were recorded at the 57 study sites. Only one individual each of Herminium monorchis, Habenaria furcifera , and Malaxis muscifera was collected, depicting these orchids as extremely rare in the study area. A total of 324 vascular plant species (including orchids and their neighboring plant species in the studied plots) were classified into seven significantly (p < 0.05) different plant associations, each with a unique species composition. The results of canonical correspondence analysis showed that temperature variability was the most influential among the 28 environmental factors considered. Different microhabitats with an elevation range of ≥1500–3500 m a.s.l. in the central part of the study area are moister and richer in organic matter and support high orchid diversity. It was observed that a higher density of co-existing tree and shrub species and a higher geographic slope were supporting the growth and survival of orchid species as well. Conversely, higher deforestation activities and potassium levels in the soil were observed as negatively influencing factors. The influence of non-native plant species on orchid species distribution was not significant, indicating that the local orchid species were not remarkably affected when growing in microhabitats with optimal conditions. This study concluded that the central part of the study area is richer in orchid abundance and diversity and needs effective conservation and management planning. [ABSTRACT FROM AUTHOR]

The interviewing of suspects is a key component in the investigation process. Although a great deal of research on interrogation and interviewing techniques has been conducted in the past, much of this work has been undertaken outside South East Asia. This new study examined Malaysian police officers' reported rate of use of a large variety of investigative interviewing techniques categorised into six domains: rapport and relationship building, context manipulation, emotion provocation, confrontation/competition, collaboration and presentation of evidence. Eighty-eight police officers primarily from the criminal investigation department, narcotics crime investigation department, commercial crime investigation department, and traffic enforcement and investigation department participated in a pen-and-paper survey. Findings revealed that many police officers in the current study report adopting investigative interviewing techniques that are largely in line with ethical, non-coercive guidelines. [ABSTRACT FROM AUTHOR]

Countdown timers impact driver behavior significantly and are widely used at signalized intersections in many countries. Literature shows potential vehicle class-specific temporal and spatial variations in driver behavior in the presence of timer. Therefore, first, this paper analyzed the temporal, spatial, and vehicle class-specific impacts of timer on driver behavior in heterogeneous traffic conditions based on variations in acceleration. Second, a Long Short-Term Memory model was developed to model vehicle discharge, incorporating the heterogeneity of traffic and impacts of timer. The performance of the model was compared with that of the Intelligent Driver Model using field trajectory data from three signalized intersections in Kerala, India. The model accurately predicts the following behavior with mixed spacing errors of 0.24 to 0.35 and an average mean squared error of spacing of 1.23. The results were better than, or comparable to, results from recent data-driven car-following models and significantly better than IDM. [ABSTRACT FROM AUTHOR]

The number of vehicles is increasing every year, and along with it, the number of traffic violations is also rising.. Traffic violations are one of the causes of traffic accidents. Currently, traffic violation detection still uses conventional methods, involving the police to take action. Preliminary research on traffic violation detection by several researchers mostly uses the Yolo Method. The study aims to design a traffic violation detection system for two-wheeled vehicles using the Convolutional Neural Network (CNN). In this research, the CNN method was used with the Faster RCNN architecture. Faster R-CNN is composed of convolution layers, Relu, and pooling layers which are used to extract features from images. An image in the size of 3264 x 1836 pixels, with the type of marking violation and helmet use was used as a sample. The number of images used was 660 images with 600 images for training and 60 images for testing. The system will detect traffic violations on two-wheeled vehicles, namely helmet use violations and road marking violations. This traffic violation detection system for two-wheeled vehicles produces the highest accuracy, namely 85% with a maxpooling kernel size value of 1x1, stride 1 and a learning rate of 0.003. This research has the potential to be applied to areas that are less accessible to the police, because the system will record and analyze violations. [ABSTRACT FROM AUTHOR]

A variety of takeover scenarios will happen in conditionally automated driving. Previous studies presented mixed results regarding the effects of scenarios on takeover performance. According to drivers' strategies for takeover requests, this study selected eight representative takeover scenarios and categorized them into lane keeping and lane changing scenarios. To investigate the effects of scenario type and road environment (highway vs. urban) on drivers' takeover performance and physiological responses, a driving simulation study was conducted as a mixed design with 40 participants (average age = 22.8 years). The results showed that in lane changing scenarios, with the same sensing capability, drivers on highways had deteriorated takeover performance in the form of harsher takeover maneuvers and higher collision risk, as well as higher arousal and stress, compared to urban areas. However, such effects disappeared or even reversed in lane keeping scenarios on the curves, where drivers on highways had smoother takeover maneuvers and lower arousal and stress. These findings will help us understand the vital roles scenario type and road environment play during takeover transitions. Our findings have implications for the design of advanced driver-assistance systems and will improve driving safety in conditionally automated driving. • Effects of scenario type and road environment on takeover responses were examined. • Takeover scenarios were categorized into lane keeping and lane changing scenarios. • Highway takeovers performed worse than urban takeovers in lane changing scenarios. • Urban takeovers performed worse than highway ones in curved lane keeping scenarios. [ABSTRACT FROM AUTHOR]

• Visual behaviour of distracted and non-distracted pedestrians was examined. • Post-encroachment time was used to assess risk of pedestrians-vehicle interactions. • Mobile phone usage increased chances of unsafe pedestrian-vehicle interactions. • Visual metrics parameters showed a significant impact on unsafe interactions. Use of mobile phones while crossing the road has become a growing safety concern among pedestrians. Though recently, some studies have attempted to understand risky behaviour of distracted pedestrians by analyzing impacts of distraction on pedestrians' walking and visual characteristics, the impacts were measured individually. Moreover, most of the existing findings are based on lab-based experiments, whereas the real-world conditions are quite dynamic in nature. Hence, to overcome these gaps, the current study aims to understand to what extent different potential factors (such as distraction, walking characteristics, visual behaviour, etc.) affect the risk of unsafe pedestrian-vehicle interactions in real-world settings. For this purpose, a field experiment was designed to understand the impact of distraction on pedestrians' risky behaviour using an eye-tracker at an unsignalized intersection in Delhi. The risk assessment was done using Post-Encroachment Time (PET) measure. The results indicate that the use of mobile phone while crossing the road increased the chances of unsafe (PET < 1.5 s) pedestrian-vehicle interactions by approximately eight folds. Surprisingly, pedestrians who crossed the intersection at high speed had higher chances of unsafe interactions, whereas their increased crossing initiation time reduced the probability of unsafe interactions. Moreover, increased pupil diameter and fixating more on vehicles approaching from the right side resulted in a reduced probability of unsafe interactions. However, the high frequency of saccades and higher fixations on the crosswalk's right side negatively affected unsafe interactions. This study highlights that it is important to consider visual characteristics along with demographic and walking and traffic characteristics as they can provide in-depth insights into pedestrians' road crossing behaviour that are required to design and implement effective countermeasures and policies. [ABSTRACT FROM AUTHOR]

• Cargo bike sharing contributes considerably to car ownership reduction. • Motives to use cargo bikes are compared with motives to use cars. • Cargo bike sharing users tend to rate cargo bikes superior on most attributes. • On some instrumental attributes, cars are still rated superior to cargo bikes. • Structural measures could increase competitiveness of cargo bikes compared to cars. The transport sector and especially private cars pose environmental, economic, and social challenges. For this reason, cargo bikes and shared mobility are considered viable alternatives for road transport. In order to understand the potential and barriers of alternative transport modes, it is essential to analyze underlying motives. Moreover, comparing sustainable alternatives (such as public transport) to cars in terms of motives has been established as a research approach (Steg, 2003). Despite increasing interest in cargo bikes and cargo bike sharing, research on this topic is relatively rare. Particularly, there exists a lack of research addressing the impact of cargo bike sharing on car ownership. Against this background, this study quantifies the car ownership reduction effect of cargo bike sharing. In addition, it is investigated how cargo bikes differ from cars with regard to the underlying motives of users which also helps understanding potential barriers. To answer these research questions, this study is based on a large-scale survey with n = 2,590 cargo bike sharing users. The results imply that cargo bike sharing has a notable impact on car ownership. In general, cargo bikes are rated superior in regard to affective, symbolic, and environmental motives as well as on flexibility and price. However, discrepancies to cars do exist in terms of other instrumental aspects (traffic safety, travel speed, comfort, weather-independence). Notably, users who reduced car ownership tend to rate cargo bikes superior compared to car-dependent users. The results imply that cargo bikes can play a marked role in reducing car dependency. Improving infrastructure and cargo bike technology as well as stimulating favorable social norms for cargo bikes have been identified as beneficial conditions that could help to leverage this potential. [ABSTRACT FROM AUTHOR]

• This works confirms the interest of differentiating car drivers and motorcyclists. • The results show an effect of both the type of vehicle and the health crisis on the rules respected. • This wok allows for theoretical reflection on the construction of the relationship to social and legal rule. The aim of this article is to examine the construction of the relationship with rules, their links in individuals throughout their lives and their possible interactions. More precisely, this paper looks at the impact of the health crisis, COVID 19, on compliance with road rules among three categories of road user: car drivers, motorcyclists with a cylinder capacity of no more or more than 125 cm3. A questionnaire was designed and distributed to 4382 car users, motorcyclists with a cylinder ca-pacity of more or no more than 125 cm3. representative of the French population. The results show an effect of both the type of vehicle and the health crisis on the frequency and number of safety rules respected. These results confirm the value of differentiating the road-user population by showing the differences between motorists and motorcyclists, which are not due solely to the mode of travel used. In terms of road safety policy, they show the importance of prevention campaigns targeting different modes of travel, and taking into account the specificities of their users in terms of perception of rules and the factors involved in their observance. [ABSTRACT FROM AUTHOR]

• In young drivers of both sexes traffic offences are rare while under supervision. • Offence rates increase greatly after the first provisional phase (P1) is attained. • Excluding GDLS offences there are small increases after reaching the next phases. • Novices aged 17 at first licensure had the highest rates in the provisional phases. • Speeding was most common but unsafe driving was common shortly after reaching P1. This paper aims to add to the sparse research on patterns of traffic offending in young novice drivers by examining the trajectories of young Australian novices throughout the graduated driving licensing system (GDLS). Data on licensing, crashes and traffic offences for all persons aged under 25 years first licensed from July 2007 to June 2008 in New South Wales were supplied by transport authorities, with follow-up to January 2014. Eight hierarchical categories of offence were defined by seriousness. Total numbers of offences per month were plotted for one year after initial licensure while under supervision (L), after transitions to the first (P1) and second (P2) provisional licence phases and to unrestricted licensure (U). After excluding novices not transiting to P1, 75,470 novices (51.5 % male, 77.7 % 16 years old at L) remained. Of these 63,070 had a year of follow-up after P2 (52.5 % male, 82.3 % 16 years old at L) and 28,861 had a year of follow-up after U (55.5 % males, 91.7 % 16 years old at L), Offences were uncommon under at L but spiked after P1 and again after P2. Omitting GDLS offences there was a small increase after U. Patterns were broadly similar by age at L and time in L. Novices aged at least 18 years at L had the highest offence rates in the learner phase; those aged 17 years at L had the highest rates in P1 and P2. The longer novices spent in the supervised driving phase the lower their subsequent offence rates even allowing for age at P1. Urban or regional residence had little influence on offence rates but lower aggregate socio-economic status as measured by a census-derived index was associated with appreciably higher offence rates. Speeding was the most common offence type; dangerous/negligent driving was common immediately after P1, declining thereafter. These results are in broad agreement with previous research in noting the increase in offending as GDLS restrictions eased. They highlight the need for better understanding of the function of a GDLS in improving the safety of young drivers. They may also inform future enforcement and education policies for novice drivers. For example, rehabilitative interventions should occur coupled with enforcement soon after citation. Visible display of GDLS status would assist their identification. [ABSTRACT FROM AUTHOR]

When we hear about a transgression, we may consider whether the perpetrator's individual circumstances make their transgression more understandable or excusable. Mitigating circumstances may reduce the severity of punishment that is deemed appropriate, both intuitively and legally. But importantly, in courts of public opinion and of law, mitigating information is typically presented only after information about a perpetrator's transgression. We explore whether this sequence influences the force of mitigating evidence. Specifically, in two studies, we examined whether presenting evidence about a perpetrator's background before or after evidence of their violation influenced how severely U.S. participants punished perpetrators. In Study 1 (N = 132), evidence about the perpetrator's mitigating circumstances reduced punishment only when it was presented before evidence about the perpetrator's violation. Study 2 (N = 316) additionally revealed this moderating effect of presentation order across a variety of premeditated and impulsive violations. These findings are consistent with person-centered theories of punishment and with the Story Model of adjudication. [ABSTRACT FROM AUTHOR]

The diversity of parasite communities is mainly driven by evolutionary history, as well as the ecology of the host species. To test whether the diversity of the parasite community of four related Stromateidae (Pisces: Scombriformes) is related to evolutionary history (the host phylogeny) or the host's geographical distribution, we analyzed the metazoan parasite fauna of four species of fishes of this family, from the Pacific and Atlantic coasts of South America. Studied species were Peprilus snyderi (samples from Callao, Perú, and Antofagasta, Chile), Peprilus medius (Chorrillos, Perú), Peprilus paru (Rio de Janeiro, Brazil) and Stromateus stellatus (Talcahuano, Chile). Our multivariate analysis strongly suggests that the diversity of the parasite fauna of the studied fishes is driven mainly by the host's geographical distribution and not the host phylogeny. [ABSTRACT FROM AUTHOR]

Objectives: This study tests the relative timing of inmate infractions in the weeks before and after a visit. Method: Our sample is a cohort of 823 male inmates who participated in the Dutch Prison Visitation Study (DPVS) (2017) and had visitation and misconduct data. Using two-level random effects logistic regression models, we examined week-to-week associations between infractions and prison visits, including visits from partners, family, friends, and official visitors. Results: The probability of an infraction is comparable to average levels in anticipation of visits, increases up to 18 percent in the weeks immediately following visits, and then returns to baseline levels. This pattern is found for contraband infractions, but no effects were found for aggressive infractions. Strongest effects were found for family and official visits. When inmates are visited frequently, the risk of infractions postvisit is similar to average levels. Conclusions: The findings show that visits can have harmful effects on inmate infractions. These effects seem to stem from increases in contraband infractions. More research is needed to further understand the mechanism behind visits' effects. [ABSTRACT FROM AUTHOR]

The article emphasizes the enduring and escalating influence of artificial intelligence (AI) in economic development, highlighting its potential to significantly enhance efficiency for practitioners across various job roles. Topics explored also encompass the critical interplay between AI and environmental, social, and governance (ESG) factors in shaping industry strategies and decision-making, underscoring the need for economic developers to grasp and leverage these dynamics effectively.

This paper was written as part of the research project "Research of public opinion on the state of safety, behaviour and habits of participants in road traffic in the Republic of Croatia". The goal of this research is to determine the frequency of violations of traffic regulations related to drivers, pedestrians and passengers in vehicles, and to determine whether there is a connection between the experience of suffering of the aforementioned road users and their punishable behaviour. For this purpose, a quantitative research was conducted in which a multi-method approach was used in field data collection, a combination of telephone research (CATI) - 60% of the sample and online research (CAWI) - 40% of the sample. Respondents from the entire territory of the Republic of Croatia (N=2072) over the age of 16 were included in the research. In general, it can be concluded that the violation of traffic regulations is very frequent and present among the majority of different road users, and that road users who have recently experienced a traffic accident in any capacity, very rarely violate traffic regulations, as car drivers. Conversely, involvement in traffic accidents has not been shown to deter pedestrians and vehicle occupants from repeating traffic violations. The obtained results have a practical value, especially in the context of planning preventive programs and strategies, while the limitations of the research are reflected in the fact that only one independent variable was included in the correlation with committing traffic violations, regardless of other known predictors of punishable behaviour in traffic. [ABSTRACT FROM AUTHOR]

The Dula Dangerous Driving Index (DDDI) is a widely used questionnaire that measures the tendency to drive dangerously on the road through three different types of behaviors: aggressive driving, risky driving, and experiencing negative emotions while driving. This study aimed to develop a Spanish version of the DDDI and verify the reliability and validity of this questionnaire in the Spanish population. A community sample of 2174 Spanish participants (51.1% male; age range: 18–79 years) completed the 28‐item Spanish version of the DDDI. Confirmatory factor analysis revealed that a three‐factor model fitted adequately to the data. Analysis of internal consistency, test–retest reliability, and convergent validity showed that the Spanish adaptation of the DDDI had good psychometric properties and retains the theoretical consistency of the original scale. Gender and age differences were observed. The Spanish version of the DDDI can be considered a good instrument for assessing dangerous driving behavior, thus contributing to the cross‐cultural study of these types of behaviors and the possible development of intervention programs aimed at reducing road traffic accidents. [ABSTRACT FROM AUTHOR]

• Personal vehicle and pedestrian mode share increased during the pandemic. • Alcohol and cannabis use increased during the pandemic. • Risky driving behaviors increased in Canada during the pandemic. • Driving after using alcohol or drugs and speeding showed largest pandemic increases. The COVID-19 pandemic is one of the most disruptive events in recent history, which resulted in the widespread implementation of unprecedented public health measures (Polisena et al., 2021; De Vos, 2020). The implications of these lockdowns on road safety are not yet fully understood, however, available data have consistently revealed increases in risky driving behaviors despite reductions in traffic volumes (Thomas et al., 2020; Wagner et al., 2020). The objective of the present study was to compare self-reported data on travel modes and risky driving behaviors (speeding, distracted driving, drinking and driving, drugged driving, fatigued driving, and seatbelt use) before and during the pandemic in Canada. Data were collected using the Road Safety Monitor (RSM), an annual online public opinion survey investigating key road safety issues administered to a representative sample of road users. Respondents were asked about the frequency of travel using various modes, use of impairing substances, and frequency of engaging in risky driving during the pandemic, as compared to before the pandemic. Results showed increases in personal vehicle and pedestrian travel, with large declines in public transit use during the pandemic. A significant proportion of respondents reported drinking more alcohol during the pandemic (14.9%) or using more THC-containing cannabis (12.2%). With respect to risky driving behaviors, the results indicated the majority of respondents reported no change in their behavior, and most positively, a small proportion said they less often engaged in risky driving behaviors. However, notable proportions did engage in risky driving behaviors more often during the pandemic as compared to before it. The behaviors mainly reported as occurring with higher frequency during the pandemic were driving when likely over the limit for alcohol (6.6% of respondents) and driving within two hours of using drugs (5.2% of respondents). Logistic regression results showed respondents with preferred pronouns of she/her had lower odds of reporting they were more likely to engage in these risky driving behaviors. Age also had a significant effect, as increasing age was associated with lower odds of reporting that these risky driving behaviors were more likely during the pandemic. Overall, the current findings suggested a small proportion of drivers reported being more likely to engage in risky driving behaviors. However, given the large number of licensed drivers, even small percentages are concerning. The findings have important implications for transportation and public health policies and can inform strategies to reduce road risks during future lockdowns. [ABSTRACT FROM AUTHOR]

• Public transport users were interviewed during Covid-19 pandemic in Ankara, Türkiye. • Thematic analysis revealed 4 overarching and 15 sub-themes. • Changes in transportation patterns during Covid-19 habits were reported. • Future directions for better transport planning were noted. • Transportation inequity that becomes more visible after the pandemic has been discussed. Due to the COVID-19 outbreak, people refrained from crowded places; public transport is one of them. The need for movement was restricted as part of governmental precautions. However, some people continue to go to workplaces as usual, and the ones who do not have personal vehicles continue using public transportation. The current study aims to investigate the experiences of public transport users (i.e., passengers) in Türkiye during the COVID-19 pandemic. Semi-structured interviews were conducted with ten people living in Ankara. As a result of thematic analysis, four overarching themes and fifteen sub-themes were determined. These overarching themes include changes in travel behavior during COVID-19, factors influencing transportation preferences, suggestions for better planning of public transport services, and suggestions for better crisis management. The results suggest significant policy implications at the municipal and governmental level, emphasizing the need for transparent risk communication, timely measures, and enforcement. Additionally, the study highlights transportation inequity, which becomes visible after the pandemic. We believe that qualitative data provided valuable insight to road authorities about road users' transportation experiences during the pandemic and, thus, how to manage better the pandemic's effect on the transport system based on the mobility needs of the citizens. We hope the results could benefit road authorities in developing effective policies and plans for all countries in the world, especially for the ones having a specific need to improve safety in traffic settings. [ABSTRACT FROM AUTHOR]

• This study assesses the effectiveness of specific disability warning signs for autism at multiple locations in New Jersey. • Video and speed data were collected and analyzed. • Two proxies, i.e., following the speed limit and applying brakes to show caution, were considered for the assessment. • Results showed a high rate of non-compliance events for both proxies. In 2018, the Centers for Disease Control and Prevention (CDC) found that the prevalence rate for children identified with autism spectrum disorder (ASD) in New Jersey is 1 in 35 children, the second highest rate of ASD diagnosis in the country. Children with autism face numerous obstacles, including learning road safety and interacting with road elements that could raise the risk of their traffic crash involvement. Many agencies across the nation have used disability warning signs as a tool to eliminate such risks. However, the effectiveness of these signs has not been explored yet. This study assesses the effectiveness of specific disability warning signs for autism at multiple locations in New Jersey using video and speed data. To investigate all drivers' responses to the ASD warning signs, the study defined two proxies of following the speed limit and applying brakes to show caution, where the events that did not correspond with the defined proxies were recorded as non-compliance events. Additionally, the Mann-Whitney U test was employed to evaluate the effectiveness during the presence and absence of ASD sign. Study results showed a high rate of non-compliance events for both proxies, and no significant difference in the driving speed was observed during the presence and absence of ASD sign. Additionally, the estimated relative risk/rate ratio revealed that the drivers that did not follow the speed limit were 1.5 times more likely not to apply brakes than the drivers who followed the speed limit, representing careless driving behavior in the area with ASD individuals. [ABSTRACT FROM AUTHOR]

This article proposes two exploratory methods for analyzing event patterns. Events in this article refer to zero‐dimensional objects in the spatiotemporal dimension, such as crimes, earthquakes, and traffic accidents. One method detects the peaks in event patterns, evaluates the degree of event concentration at the peaks, and visualizes its spatial variation. Another method evaluates the similarity between different event patterns and visualizes its spatial variation. The methods help us understand events' properties, consider their underlying mechanisms, and permit us to prevent events if they represent undesirable phenomena such as crimes and traffic accidents. The proposed methods are applied to analyze the population distribution in the central area of Tokyo in May 2019. The application revealed the spatial variation of population peaks in this area and the differences in population patterns between different types of days. [ABSTRACT FROM AUTHOR]

Vehicle-involved road crashes, mainly caused by traffic violations, result in major property damage and life losses annually. Thus, it is of vital importance to clarify the heterogeneities of various factors in traffic violation severities. This study quantifies the heterogeneities across different clusters. It selects 15 potential factors from six perspectives based on 40,161 police-reported traffic violations at intersections. An unsupervised learning algorithm combining latent class clustering analysis and partial proportional odds model, as well as marginal effects, is applied to clarify the differences. Four clusters are identified as the optimal based on the Akaike information criterion, Bayesian information criterion (BIC), sample-sized adjusted BIC, and entropy-based approach. The results evidenced that the top five influential factors in traffic violations at intersections were legs of entrance, driver age, road type, area type, and signal control. Their maximum absolute values of their marginal effects were more than 35%. Furthermore, there were great heterogeneities across the clusters, especially between cluster 2 and cluster 3. Findings could provide some insightful information to prioritize effective countermeasures to mitigate the losses of traffic violations and improve road safety. [ABSTRACT FROM AUTHOR]

By investigating a one thousandth national execution quota issued in the Campaign to Suppress Counterrevolutionaries (1950–1953), the article explores an aspect of Maoist politics that has largely escaped mainstream scholarship on Mao, the CCP, and PRC history. It shows how the newly created Maoist regime sought to eliminate its political enemy based on a specific demographic estimate of one thousandth. Tracing the roots of this quantification of political enemies into Mao's class-analysis theory back to the 1920s and explaining other political campaigns throughout the 1950s as continuations of the party's use of this method, the article argues that quantitative concepts and relations were important instruments in Maoist ideology, the CCP's political strategy and the working of the party-state. By proposing a concept of "quotacide," the article identifies an ignored type of large-scale, ideologically based, and politically driven homicide in the history of political violence. The article also brings in similar quantitative policies of political suppression in other authoritarian party-states such as the Soviet Union (the 1930s) and North Vietnam (the 1950s) in this context. [ABSTRACT FROM AUTHOR]

Motorized Two-Wheeler (MTW) drivers significantly contribute to road fatalities due to their vulnerability and the higher severity of crashes. Risky driving behavior, such as violations and errors, is a key precursor to road crashes. Understanding the factors that influence such risky behavior can shed light on opportunities for risk management. In this investigation, data from 460 motorized two-wheeler drivers were collected through an online questionnaire, exploring Red Light Running (RLR), lane sharing, and turning without indicating driving tendencies, latent psychological factors, and demographic attributes of the participants. The analysis was conducted in two steps: (a) decision trees were developed to classify risky driving behavior, and (b) binary logistic regression models were developed to quantify risky driving choices based on demographic and latent psychological variables, as well as interaction variables. The results showed that as driver anxiety increased, the probability of lane sharing rose from 76.3% to 87.9% in normal driving situations and from 80.3% to 96.6% in time-pressure driving situations, respectively. Furthermore, the results revealed that the odds of running red lights and lane sharing decreased to 0.57 and 0.68, respectively, for older drivers compared to young drivers. Overall, this study quantified the impact of underlying psychological factors and demographic parameters, as well as their combined effects, on assessing traffic violations, traffic errors, and non-illegal dangerous driving behaviors among motorized two-wheeler drivers. Additionally, the study discusses the implications and policy interventions related to the legalization of lane sharing and the risks associated with time-pressure driving in online food delivery systems. These findings can inform evidence-based policymaking to achieve road safety goals. • Anxious drivers are more likely for lane sharing especially in time constrained situations. • Older drivers are less likely to indulge in red-light running and lane sharing. • Impunctual drivers are more prone to turning without indicating. • The acceptance of traffic violation by pillion rider motivated drivers to violate traffic rules. [ABSTRACT FROM AUTHOR]