Promote Road Safety Research Articles

Over-speeding trend across self-reported driving aberrant behaviors: A simulator study.

The aim of the present study is to investigate the relation between self-reported aberrant behaviors as measured by using the Italian version of the Manchester Driver Behavior Questionnaire (DBQ) and actual driving performance during a virtual simulation, focusing particularly on over-speeding. Individual variables are considered based on participants’ behavior, and driving styles are derived from both the self-report questionnaire and the kinematic variables obtained through a moped simulator after the simulated driving task. The experiment was carried out on an Italian sample of 79 individuals aged between 18 and 35 who had to drive throughout virtual road environments. A cluster analysis of the kinematic variables provided by the simulator was used to individuate two different groups of drivers: 45 fell into the cluster named “Prudent” and 34 participants fell into the “Imprudent” cluster. The Prudent participants were characterized by lower acceleration, lower speed, better overall evaluations, and a smaller number of accidents. Correlations showed that self-report responses correlated positively with performance variables in terms of acceleration, speed, and over-speeding. Furthermore, the results from a MANOVA supported and complemented this evidence by emphasizing the usefulness of the integrated approach employed. Overall, these results reflect the suitability of experimental sample-splitting into two clusters, pointing out the appropriateness and relevance of self-report DBQ use with particular emphasis on Ordinary Violations and Lapses. The integrated use of the driving simulator and the self-report DBQ instrument with reference to driving behavior made it possible to support previous theoretical considerations regarding the relations between on-road aberrant behaviors and over-speeding behaviors. It also enabled the addition of evidence on the effectiveness of the simulator in detecting drivers’ actual performance. These results are relevant to allow the integration of useful information to expand intervention and training designs that can be used to reduce risky behavior and promote road safety.

Road safety education for schools with ZoSS facilities in Bandung City, Jawa Barat

West Java is the province in Indonesia with the third greatest number of accidents. Accidents are caused by dangerous traffic behavior. In order to save Indonesia's productive generation, changing traffic behavior is a top concern. Several schools in accident-prone areas have been designated as Safe School Zones (ZoSS) by the government. However, it is vital to teach students and their support systems how to drive safely. This program seeks to promote road safety knowledge and behavior, support changes in traffic safety behavior, and increase traffic safety knowledge and behavior among students, teachers, and the public. On December 22, 2021, the activity was held in 5 elementary schools (SD) and 5 junior high schools (SMP), with theoretical and practical road safety training. The activities resulted in the development of young fighters' capacity, the formation of Road Safety Ambassadors and Safety Awareness Community Groups (KMSK), and the emergence of a sustainable program by advocating to the government and designating the Bandung City Transportation Office as the Adopting Father of Ambassadors and KMSK.

STUDY ON ROAD TRAFFIC MULTIMODAL SIMULATION, COMPARITIVE STUDY ON SIMULATION SOFTWARES ON INTERSECTION AND ITS ROAD SAFETY AUDIT

In today’s world of advancements transportation engineering is the most focused branch in terms of software development. In order to provide a small part to this branch a comparative study is a must to identify the most efficient software for providing this work is important. To do this study in the project we need to identify the best software for simulations of vehicles in multimodal means is also of that importance. This also suggests the need of this softwares in use also. To do this designing a intersection is optimum. Also the Ministry of Works, Housing and Communications has a duty of care to all road users, and so has always been concerned with the safety of its roads. However, the significant increase in road crashes in recent years has prompted the Ministry to intensify its efforts to promote road safety. One small part of this effort are new procedures to ensure that the safety of all road schemes is checked by specialists before construction this is called safety auditing. demand for transportation, safety is an issue of major social concern and an area of extensive research work. The rate of Crashes in developing countries like India increases year by year. A Crash is an unplanned and uncontrolled event, which occurred on a road open to a public traffic resulting in personal injury, damages to the property and loss of life in which at least one moving vehicle was involved. In the world, India has world’s largest heavy traffic and accidents also. It is necessary to provide the safety to roads. Lack of infrastructure, interaction of vulnerable road users (VRU) with high-speed traffic, and faulty geometric design are some of the most alarming safety deficiencies identified through the audit process. The insights obtained from the RSA report could not have been gained from the Crash reports alone. Finally, countermeasures need to be suggested based on the observations made during the RSA.

Smart Diagnosis: Deep Learning Boosted Driver Inattention Detection and Abnormal Driving Prediction

Inattentive driving is one of the high-risk factors that causes a large number of traffic accidents every year. In this article, we aim to detect driver inattention leveraging on large-scale vehicle trajectory data while at the same time explore how do these inattentive events affect driver behaviors and what following reactions they may cause, especially, for commercial vehicles. Specifically, the proposed system targets four most commonly occurring critical inattentive events, including smoking, phone call, turning back, and yawning. By applying a deep convolutional neural network (CNN) (Inception v3) with two data augmentation routines—Mixup and synthetic minority oversampling technique (Smote), we are able to balance the training data distribution and improve the generalization of the classification model. Then, based on the output derived from the inattention detection combining with point of interest (POI) and climate data, a long short-term memory (LSTM)-based model is deployed to predict driver upcoming abnormal operations on road (due to inattention) which may result in potential dangerous driving conditions, such as sudden acceleration/deceleration, aggressive left/right lane change, etc. To evaluate our proposed system, we collect more than 120000 real-world driving traces from over 200 drivers. The experimental results show that our model achieves a weight accuracy (WA) of 92.27% for inattentive driving detection and a WA of 91.67% for abnormal driving prediction, demonstrating its great potential of shaping good driving habits and promoting road safety.

French drivers’ behavior: Do psychological resources and vulnerabilities matter?

Introduction: Driving is a risky activity, and road users’ behavior is one of the many factors that participate in increasing the risk of road-traffic crashes. Drivers must constantly adapt their behavior to the environment and control their vehicles, and must also anticipate the behavior of others, which may pose a threat to their own safety. Interactions between road users can therefore be stressful and elicit strong negative emotions. Psychological resources and vulnerabilities may be important in understanding how drivers perceive and respond to these driving interactions. The aim of this study was to investigate the role of empathy, self-compassion, personal distress, and alexithymia in both dangerous and prosocial driving behaviors. Method: Our sample (N = 550) of French drivers was recruited via snowball sampling. The drivers filled in paper-and-pencil questionnaires including the Driver Behavior Questionnaire (DBQ), the French adaptation of the Toronto Empathy Questionnaire (Short-FTEQ), the Interpersonal Reactivity Index (IRI), the Self-Compassion Scale – Short Form (SCS-SF), and the Toronto Alexithymia Scale (TAS-20). Results: After controlling for gender and age, regression analyses revealed that road traffic violations were positively predicted by alexithymia and negatively predicted by cognitive empathy; errors were positively predicted by alexithymia and personal distress, and prosocial driving was positively predicted by emotional and cognitive empathy. A two-step cluster analysis identified three groups of drivers: unsafe and psychologically vulnerable (n = 176), self-focused and less prosocial (n = 151), and safe and resourceful (n = 223). Conclusions: Empathy seems to promote safe driving behaviors. Moreover, cognitive empathy appears to safeguard drivers against deliberate violations, whereas psychological vulnerabilities seem to increase the probability of engaging in dangerous behaviors. Practical Applications: These results could open new research avenues for the prevention of dangerous driving behaviors and the promotion of road safety.

Sustainability and the Contribution of Electric Scooter Sharing Business Models to Urban Mobility

There has been a rapid uptake of electric scooter (e-scooter) sharing services in cities in recent years. However, the academic literature is still scarce on how e-scooter operators contribute to sustainable urban mobility through their business models. In this qualitative case study, we analyse the sustainability of these rapidly evolving sharing services through a frame of sustainable business model archetypes, and study value transfer, its obstacles, and its controversies within the Finnish urban transport system. While e-scooter services mainly target delivering functionality over ownership, according to the operators, combinations of approaches are applied that contribute positively to sustainability. These include, for example, increasing the lifecycle of scooters, recycling of scooters and their parts, using renewable energy, commi ing to climate compensation, and promoting road safety and the responsible use of scooters. The findings indicate that in Finland, e-scooter services are seen to have potential in serving the first and last miles of public transport journeys. Due to a lack of binding regulation, co- and self-regulation is emphasized and is supported by active information and data sharing with public authorities. While sustainability is embedded in many ways into the business models of e-scooter operators, there are still potential sources of unsustainability aff ecting the urban transport system. For example, current business models favour convenience over physical activity, which can reduce the amount of active travel and use of city bikes.

Analysis on mortality trends of road traffic injury in Tianjin, 2000-2019

Objective: To investigate the mortality trends of road traffic injury in Tianjin from 2000 to 2019, understand the mortality of road traffic injury in different populations and provide evidence for the prevention and control of road traffic injury. Methods: Mortality data of road traffic injury in Tianjin during 2000-2019 were collected from the Population Based Mortality Surveillance System in Tianjin. Population data of permanent residents were collected from Tianjin Municipal Public Security Bureau. The crude mortality rate, the Chinese age-standardized rates, and premature mortality probability and gender and area specific constituent ratio were calculated. The trends in different populations were analyzed by using Joinpoint regression analysis. The average annual percent change (AAPC) and annual percent change (APC) were calculated. Results: From 2000 to 2019, a total of 26 919 deaths due to road traffic injury occurred in Tianjin. The death constituent ratio decreased from 21.28% to 18.38% in urban males and the death constituent ratio in urban women declined from 7.01% to 6.28%. The death constituent ratio declined from 59.16% to 55.59% in rural males, whereas the death constituent ratio in rural women increased from 12.55% to 19.75%. From 2000 to 2019, the crude mortality rate of road traffic injury declined from 14.08/100 000 to 7.89/100 000, and the age-standardized mortality declined from 13.28/100 000 to 5.51/100 000. The probability of premature mortality was 0.70% in 2000 and 0.38% in 2019. The mortality rate and premature mortality probability of road traffic injury increased first, then decreased slightly and then decreased rapidly. The mortality of road traffic injury increased with age. From 2000 to 2019, the mortality of road traffic injury in males was higher than in females, but showed a rapid decline. The age-standardized mortality rate was 20.97/100 000-8.01/100 000 in males, and 5.10/100 000-2.85/100 000 in females. Compared with the urban area, the mortality rate in rural area was higher, but declined more rapidly in recent years. The age-standardized mortality rate decreased from 6.99/100 000 to 2.46/100 000 in urban area, and from 19.85/100 000 to 8.75/100 000 in rural area. As the population with the highest mortality of road traffic injury, the morality rate in males in rural area had decreased rapidly since 2016, the APC of age-standardized mortality rate from 2016 to 2019 was -18.55%. Conclusions: The effect of the road safety promotion in Tianjin was significant. The mortality of road traffic injury showed a downward trend, especially in recent years. It is necessary to strengthen the prevention and control of rode traffic injury in males, rural residents and elderly people.

Strontium Aluminate Compound as Road Line Materials Application

Road line marking are used as a mean of controlling traffic and road user safety. It is very significant on any roads and intersections as they promote road safety. They highlight a harmonious flow of traffic along guided paths of travel. The objectives of this study are to investigate the properties of road line materials and examine the illuminance properties of glow in the dark powder applied in road marking materials. The use of photoluminescent glow-in-the-dark material was tested in the lab for its suitability (luminosity and the glow duration). The methods involved are selection of suitable type of glow in the dark materials, selection of optimum mixing ratio of the glow in the dark powder with thermoplastic powder, and finally analyzed for the properties of the type of the material chosen. The fine granular strontium aluminate compound, SrAl2O4 was selected as the most suitable type of glow in the dark material. Based on the laboratory analysis, the optimum ratio of the glow in the dark material to be used with thermoplastic powder is 55% of total mix volume. The average visible light emission period is in acceptable range of 20 m. This is a suitable distance to implement the road line because of the high visibility on the road during dark or night.

Reduce speeding in times of COVID-19 in Buenos Aires, Argentina

Abstract Buenos Aires has a mortality rate due to road crashes of 3.6 per 100,000 habitants. 6/10 fatal incidents are due to speeding. Unfortunately, the City has an outdated electronic control system and a small, corps of traffic agents oversees the execution of mobile speed controls. Under the part of Partnership for Healthy Cities, the city implemented a speed reduction policy to strengthen the existing speed management by measuring speeds. The observation points were established from the sampling of 567 avenues segments according to their level of danger and # of traffic lights. 74 observation points were selected. The final sample (1,572,879 observations) obtained a representative balance of the vehicular circulation arteries according to the territory's geographical zones. 92.1% of the vehicles that circulate on the avenues respect the speed limits while 7.9% exceed the speed limit. In passenger transport and trucks, the average number of exceeding the speed limits more than doubled. During COVID-19 lockdowns, the vehicles that exceeded the maximum speed reached 9.1%. As movement and mobility changed in Buenos Aires due to COVID-19, they used this opportunity to reduce the speed limits and add cycling lanes. At the start of 2020, there were 300,000 daily trips by bicycle and during lockdown, trips rose between 24% and 114%. It is expected that by next year they will be 500,000 per day. 17 km of bicycle lanes were built in two of the largest avenues in the city and the speed limit was reduced to 50 km/h on these avenues. In addition, it was detected that both avenues were the ones on which the most trips were carried out outside the formal network of bicycle lanes, which is 250 kilometers long. On journeys that are made outside this circuit, the risk of a road accident increases by 86%. The planning process must carry out, even when in an emergency. Training and socialization of interventions for all road actors are necessary to promote road awareness. Key messages Cities are catalysts for actions to promote public health interventions on the front line to emergencies and they have the responsibility of continuing to manage the NCDI and injuries. Healthy, safe, and sustainable mobility are parameters to be met in interventions that promote road safety.

A model to explain road traffic data collection and registry in Iran: a grounded theory

:Background:Sufficient data should be gathered and analyzed to increase awareness and attention of the community and policymakers in the field of road traffic injury (RTI) prevention. While various organizations and stakeholders are involved in road traffic crashes, there is no clear lead agency for data collection system in RTIs. Exploring stakeholders' perspective is one of the key sources for understanding this system. The purpose of this study is to identify the process of RTI data collection system based on stakeholders’ experience.Methods:This qualitative study was conducted employing grounded theory approach since September 2017 to December 2018 in Iran. Participants in this study were the authorities of the Emergency organizations, police, Ministry of Health and Medical Education, faculty members, as well as executive staff and road users who were involved in collecting and recording data (n=15). Data collection was carried out through face-to-face interviews using purposeful and theoretical sampling. Data analysis was performed based on Strauss and Corbin 2008.Results:The core category was identified as “separated registration” explaining the process of collecting and recording road traffic injury data. Other variables obtained using the Strauss and Corbin Paradigm model were categorized as context, casual, intervening, strategies, and outcomes factors. The findings were classified into five groups including lack of trust in road safety promotion, process factors, management and organizational factors, failure of quality assurance, and administrative and organizational culture.Conclusions:The most important theory is “separated registration” and non-systematic registry system of road traffic injury data which is shown in a conceptual model. The findings of this study will help policymakers for better understanding the collecting and recording of RTI information.

Forecasting Travel Speed in the Rainfall Days to Develop Suitable Variable Speed Limits Control Strategy for Less Driving Risk

In order to reduce driving risk in the rainfall days, developing the variable speed limits (VSL) is effective. However, it is hard to develop suitable VSL aligning with travel speed of mainstream that it affected by the traffic flow, rainfall intensity, individual travel speed, peak hours, working days, random events, and so on. In this paper, the average travel speed and traffic flow of each road section are calculated from the toll collection data of Xi’an Ring Road from May to July in 2018 in Shaanxi Province, China. The weather data are collected and extrapolated to the corresponding road sections. Travel speed, traffic flow, and rainfall intensity are integrated to predict the fluctuation trend of travel speed through the proposed deep belief-radial basis function network. The experimental results show that a significant decrease happens in the travel speed in the rainfall day during peak hours. Furthermore, the deep learning algorithm that considers more factors such as the rainfall intensity and traffic flow could improve the prediction accuracy. Then, a VSL method and an expressway risk coefficient evaluation method based on estimation of average travel speed are proposed. The experimental results show that the variable 85th percentile speed limit method proposed in this paper can reduce the risk of expressway driving. This can promote road safety in the development of intelligent transportation system (ITS) in future.

Child Occupant Safety: Towards Implementation of Child Restraint System Law in Malaysia


 
 
 The World Health Organization (WHO) has consistently recommended that all countries regardless of their income add the requirement for Child Restraint System (CRS) to their traffic regulations in order to promote road safety. Malaysia is adopting the CRS regulation in 2020. This paper aims to discuss the readiness and mapping of the roadmap towards the implementation of the law. In a temporal view of road crashes, CRS was part of 'during-crash' passive safety components i.e. to provide protection during the crash impact phase. This analysis includes the CRS benefits and issues, related road safety strategic programmes, the current legal framework, and local research findings based on observational studies. CRS usage and acceptance are on the rise, although still at a nascent stage. This situation can be considered as 'below satisfactory compliance level', hence a more inclusive solution is needed, including the introduction of technology, to influence or compel parents to ensure their children are always secured by CRS while on the road.
 
 

Пропаганда безопасности дорожного движения ГИБДД МВД России среди несовершеннолетних

In the introduction, the problem of road safety is updated, and especially, accidents and injuries of minors due to violations of traffic rules. In this connection, the need to optimize the promotion of road safety by the traffic police of the Ministry of internal Affairs of Russia among minors is becoming more acute. The purpose of this article is to substantiate the positive experience of the divisions of the traffic police Department of the Ministry of internal Affairs of Russia in Vologda in promoting road safety among minors of primary school age through a pedagogical study. The main part of the article offers a solution to the problem under consideration by forming an attitude to road safety among minors of primary school age. Based on the identified violations of traffic rules committed by minors of this age category, pedagogical principles are identified and tools for promoting road safety are selected. The organization of the activities of the traffic police inspector of the Ministry of internal Affairs of Russia on the basis of these principles and the corresponding pedagogical tools contributes to the formation of minors ' attitudes to road safety. The results of the study showed a positive impact of the selected pedagogical tools on the promotion of road safety among minors of primary school age corresponding to modern pedagogical principles. The article concludes with a General conclusion and practical recommendations based on the results of the study.

Alcohol consumption and illicit drug use among young music festival attendees in Australia

Vanessa is a youth-led service promoting road safety at music festivals. We conducted a cross-sectional survey at 23 festivals in Victoria, Australia to investigate alcohol and illicit drug use among attendees aged ≥16 years who visited Vanessa. Participants completed the Alcohol Use Disorders Identification Test - Consumption (AUDIT-C) and reported recent illicit drug use and intentions to use drugs at festivals. Multinomial and logistic regression identified correlates of risky drinking and drug use. 2305 participants were recruited (60% female, median age 22). Most (98%) consumed alcohol in the past year and 26% had high-risk AUDIT-C scores. Almost half (48%) reported recent drug use and 24% intended to use drugs at festivals. Females had lower odds than males of recent drug use [adjusted odds ratio (AOR)=0.49, 95% confidence interval (CI)=0.38, 0.62], intending to use drugs at festivals (AOR = 0.60, CI = 0.45, 0.80) and lower risk of high-risk drinking (adjusted relative risk ratio (ARRR)=0.35, CI = 0.27, 0.47). Attending electronic music festivals was associated with high-risk drinking (ARRR = 2.07, CI = 1.14, 3.72), recent drug use (AOR = 2.23, CI = 1.42, 3.51) and intending to use drugs at festivals (AOR = 1.90, CI = 1.15, 3.14). Vanessa was a useful setting to reach young people reporting risky alcohol consumption and illicit drug use. Genre of music festivals may be useful for tailoring harm reduction strategies.

SAMNET: Self-adaptative multi-kernel clustering algorithm for urban VANETs

Nowadays, vehicle ad hoc networks (VANET) are becoming one of the trends that motivate many service providers in urban areas. In this work, we take into account the random and continuous evolution of traffic in the VANET environment. We adopt a system to model the mode of evolution based on commutation. The proposed system is defined as a finite collection of linear submodels. Thus, for each subsystem, it is necessary to identify the discrete state and to establish a specific sub-model to model the overall system. However, according to recent studies, the adoption of an efficient VANET clustering algorithm can promote road safety, provide a means of entertainment for passengers, and promote message routing. In this article, a clustering algorithm based on a Self-Adaptative Multi-Kernel clustering for urban VANET (SAMNET) is also provided. SAMNET is based on a set of measurement data, representing the unpredictable density of vehicle nodes, acceleration or deceleration, and the limited radio range of the communication scheme used. The proposed algorithm takes advantage of the concept of identifying these data generated by linear sub-models which communicate through an unpredictable dynamic switching. It is a self-adapting clustering algorithm that consists of modeling each sub-model based on a linear regression function. SAMNET is broken down into three stages: (i) initialization of clusters, (ii) adaptation of clusters, (iii) fusion of clusters. To assess the comparative effectiveness of SAMNET, many experiments are carried out. The results obtained show that the proposed methodology provides almost optimal results and works well with regard to the average lifetime of the clusters and the data delivery rate.

Classification of road traffic injury collision characteristics using text mining analysis: Implications for road injury prevention.

Road traffic injuries are a leading cause of morbidity and mortality globally. Understanding circumstances leading to road traffic injury is crucial to improve road safety, and implement countermeasures to reduce the incidence and severity of road trauma. We aimed to characterise crash characteristics of road traffic collisions in Victoria, Australia, and to examine the relationship between crash characteristics and fault attribution. Data were extracted from the Victorian State Trauma Registry for motor vehicle drivers, motorcyclists, pedal cyclists and pedestrians with a no-fault compensation claim, aged > = 16 years and injured 2010-2016. People with intentional injury, serious head injury, no compensation claim/missing injury event description or who died < = 12-months post-injury were excluded, resulting in a sample of 2,486. Text mining of the injury event using QDA Miner and Wordstat was used to classify crash circumstances for each road user group. Crashes in which no other was at fault included circumstances involving lost control or avoiding a hazard, mechanical failure or medical conditions. Collisions in which another was predominantly at fault occurred at intersections with another vehicle entering from an adjacent direction, and head-on collisions. Crashes with higher prevalence of unknown fault included multi-vehicle collisions, pedal cyclists injured in rear-end collisions, and pedestrians hit while crossing the road or navigating slow traffic areas. We discuss several methods to promote road safety and to reduce the incidence and severity of road traffic injuries. Our recommendations take into consideration the incidence and impact of road trauma for different types of road users, and include engineering and infrastructure controls through to interventions targeting or accommodating human behaviour.

A model to explain road traffic data collection and registry in Iran: a grounded theory.

Sufficient data should be gathered and analyzed to increase awareness and attention of the community and policymakers in the field of road traffic injury (RTI) prevention. While various organizations and stakeholders are involved in road traffic crashes, there is no clear lead agency for data collection system in RTIs. Exploring stakeholders' perspective is one of the key sources for understanding this system. The purpose of this study is to identify the process of RTI data collection system based on stakeholders' experience. This qualitative study was conducted employing grounded theory approach since September 2017 to December 2018 in Iran. Participants in this study were the authorities of the Emergency organizations, police, Ministry of Health and Medical Education, faculty members, as well as executive staff and road users who were involved in collecting and recording data (n=15). Data collection was carried out through face-to-face interviews using purposeful and theoretical sampling. Data analysis was performed based on Strauss and Corbin 2008. The core category was identified as "separated registration" explaining the process of collecting and recording road traffic injury data. Other variables obtained using the Strauss and Corbin Paradigm model were categorized as context, casual, intervening, strategies, and outcomes factors. The findings were classified into five groups including lack of trust in road safety promotion, process factors, management and organizational factors, failure of quality assurance, and administrative and organizational culture. The most important theory is "separated registration" and non-systematic registry system of road traffic injury data which is shown in a conceptual model. The findings of this study will help policymakers for better understanding the collecting and recording of RTI information.

Predictors and geographic analysis of road traffic accidents in Leon, Nicaragua.

To identify environmental factors present in areas with high density of road traffic accidents (RTA) in Leon, Nicaragua. The analysis included all accidents recorded by the Police Department in León City, from January to June 2017. All crashes were georeferenced, and data were collected from the environment elements within a perimeter of 20 meters from the site in which accidents occurred with a pre-tested data collection instrument. We specified a Poisson regression model to estimate incidence rate ratios (IRR) and 95% confidence intervals (CI) to determine environmental factors associated with the event incidence. For the identification areas with high, medium, and low occurrences of crashes, kernel density around points in which RTA occurred were estimated. Out of 667 recorded crashes, 90% involved men aged 15-40, and motorcycle accidents represented 60% of injuries or deaths. Environmental factors that were positively associated with RTA included good road conditions (adjusted IRR = 1.36, 95%CI 1.13 - 1.63) and the existence of bicycle lanes (adjusted IRR = 1.64, 95%CI 1.29 - 2.10). Environmental characteristics associated with higher speeds and heavier accidents can increase their incidence. We found that high-foot-traffic commercial or touristic centers are three areas with high density of crashes. Local authorities can use these findings to promote road safety measures in high-incidence areas in León City.

Agent-Based Modeling of Social Campaign Message Adoption: Problem of Parameter’s Value Determination

The paper addresses the issue of determining the parameter values of the agent-based model of social campaign message adoption relying on Bass’s classical innovation diffusion model. The problem concerns the parameters that reflect the influence of advertising and social communication on the adoption of the idea conveyed in the social campaign. Due to the fact that the factors influencing the behavior of message recipients are conditioned by their personality, circumstances or reaction to the environment, the conventional methods for estimating these parameters may not deliver a model reproducing reality with the required accuracy. Therefore, this paper proposes a procedure for determining the values of agent-based model parameters that relies on an experimental data acquisition procedure using a combination of cognitive neuroscience techniques and a survey method. The presented research examines a social campaign promoting road safety. The obtained results prove the suitability of the suggested solution for estimating the parameters of the agent-based model of social campaign message adoption. The proposed approach contributes to the methodology of data collection and parameter estimation in building agent-based models, although it is not without some limitations.

Older Adults' Motivations for Participating in a "Tune-Up" of Their Driving Skills: A Multi-Stakeholder Analysis.

Driver training has the potential to keep older adults safe behind-the-wheel for longer, yet there is limited evidence describing factors that influence their willingness to participate in training. Focus groups with community-dwelling older drivers (n = 23; 70–90 years) and semi-structured interviews with driving instructors (n = 6) and occupational therapists (n = 5) were conducted to identify these factors. Qualitative descriptive analyses highlighted how self-awareness of behind-the-wheel abilities in later life can influence an older adult’s motivation to participate in driver training, as well as their willingness to discuss their behaviors. Collision-involvement and near-misses prompted participants to reflect on their driving abilities and their openness to feedback. Participants’ preferences for learning contexts that use a strengths-based approach and validate the driving experience of older drivers, while providing feedback on behind-the-wheel performance, were raised. Older driver training initiatives that consider the needs of the aging population in their design can promote road safety and community mobility.