Pressure gauge accuracy and tire maintenance awareness among vehicle owners in Birnin Kebbi, Nigeria

Aside from human factors, tire blowouts and other tire imperfections are major contributors to the persistently high road accident rate. While tire imperfections are categorized as part of the mechanical factors affecting road accident, the tire maintenance personnel and the vehicle owners' human behavior plays a significant role in ensuring that accidents due to tire imperfections are minimized. Therefore, this study aims to determine the accuracy of the pressure gauges used by tire maintenance personnel, popularly called vulcanizers in Nigeria, and to determine the level of awareness of vehicle owners about the basic information that affects the safe use of tires on the road.  The study consists of two stages. The first stage investigates the accuracy of the pressure gauges used by twenty vulcanizers in four different districts in Birnin Kebbi, the northwestern part of Nigeria. The second stage was an online survey regarding the tire maintenance behavior of 87 participants, who were formally educated from Diploma to Ph.D. level. The study's findings showed that about 25% of the vulcanizers do not use pressure gauges to measure air pressure during tire inflation, and less than 17% of the readings taken were accurate. Yet about 60% of the respondents believe that vulcanizers' pressure gauges are reliable and less than 30% of the respondents know that the expiring date of tires is four years in Nigeria. Therefore, there is an urgent need for proper awareness about tire usage and maintenance among the general population. It would also be appropriate to include such basic road safety information in the school curriculum at all levels

In-Field Observations of Heavy Mining Vehicle Wheels and Analyses of Proposed Solutions to Enhance Safety

This research strives to enhance the safety of multi-piece wheel assemblies as injuries and fatalities are associated with their failure, yet information on this topic is limited. Experiments were performed to determine mechanical performance and planar deformation characteristics of several tires to aid in numerical model development. For a 29.5-29 tire, observations included determining vertical versus lateral deflection relationships (0.310 mm/mm), and vertical (2.59 kN/mm) and lateral (6.29 kN/mm) stiffness. A database capable of tracking wheel maintenance trends based on historical data was developed, allowing maintenance schedules to be estimated. A safety shield system was proposed. Effectiveness of the design was examined through numerical simulation of the ISO 7141 impact test, a tire blowout, and a rotational side impact. Depending on the test condition, observations comparing shield-equipped versus standard wheels show reductions in von Mises stress between 15% and 55% and reductions in effective plastic strains between 20.3% and 92%

Towards Transportation Digital Twin Systems for Traffic Safety and Mobility Applications: A Review

Digital twin (DT) systems aim to create virtual replicas of physical objects that are updated in real time with their physical counterparts and evolve alongside the physical assets throughout its lifecycle. Transportation systems are poised to significantly benefit from this new paradigm. In particular, DT technology can augment the capabilities of intelligent transportation systems. However, the development and deployment of networkwide transportation DT systems need to take into consideration the scale and dynamic nature of future connected and automated transportation systems. Motivated by the need of understanding the requirements and challenges involved in developing and implementing such systems, this paper proposes a hierarchical concept for a Transportation DT (TDT) system starting from individual transportation assets and building up to the entire networkwide TDT. A reference architecture is proposed for TDT systems that could be used as a guide in developing TDT systems at any scale within the presented hierarchical concept. In addition, several use cases are presented based upon the reference architecture which illustrate the utility of a TDT system from transportation safety, mobility and environmental applications perspective. This is followed by a review of current studies in the domain of TDT systems. Finally, the critical challenges and promising future research directions in TDT are discussed to overcome existing barriers to realize a safe and operationally efficient connected and automated transportation systems.Comment: 15 pages, 2 figures; corrected issue in author(s) fiel

A contemporary trend analysis of Kentucky State Police vehicular pursuit-related collisions and injuries.

This study investigates the trends in vehicular pursuits conducted by the Kentucky State Police (KSP) over time (i.e., years 2009 - 2017). Additionally, predictors for collisions and injuries were examined. The issues surrounding vehicular pursuits center on officer safety and agency liability concerns with the most significant of these being collisions and injuries. This study contains several primary areas. Chapter two includes a review of the literature surrounding the area of vehicular pursuits. Specifically, it reviews definitions pertinent to this study, legal aspects concerning pursuits, major empirical studies conducted on pursuits and specific risks associated with pursuit practices. This section was utilized to develop the themes for analysis. Chapter three covered the methodology for this study. In this chapter, the measures for analysis were presented and the analysis plan was thoroughly explained. The analysis plan involved three steps: Step 1: Descriptive Statistics; Step 2: Trend Analysis and Step 3: Logistic Regressions. The trend analysis employs a Bayesian process utilized by the Center for Disease Control and Prevention (CDC). This process is used to examine risk behaviors over time and was ideal for conducting the type of analysis required for this study. Chapters 4 presents the results of this study. The results indicate an upward trend in pursuit-related collisions and injuries between 2009 and 2017. The results determined that pursuits involving three or more units had the potential to increase the likelihood of collisions while the use of tire deflation devices was found to decrease the risk of collisions. No predictors were found significant for injuries. Chapter 5 contains the discussion, policy recommendations, study limitations, recommendations for future studies and conclusions. The policy recommendations should be generalizable across law enforcement agencies of similar disposition to the KSP. Recommendations are presented in the areas of intervention techniques, pursuit policy development, compliance with pursuit policy, and the development of pursuit training programs. Lastly, this study concludes with limitations and conclusions which focus on suggestions for improvement and provisions for making any future studies conducted on KSP pursuit data more robust

Advanced Sensing and Control for Connected and Automated Vehicles

Connected and automated vehicles (CAVs) are a transformative technology that is expected to change and improve the safety and efficiency of mobility. As the main functional components of CAVs, advanced sensing technologies and control algorithms, which gather environmental information, process data, and control vehicle motion, are of great importance. The development of novel sensing technologies for CAVs has become a hotspot in recent years. Thanks to improved sensing technologies, CAVs are able to interpret sensory information to further detect obstacles, localize their positions, navigate themselves, and interact with other surrounding vehicles in the dynamic environment. Furthermore, leveraging computer vision and other sensing methods, in-cabin humans’ body activities, facial emotions, and even mental states can also be recognized. Therefore, the aim of this Special Issue has been to gather contributions that illustrate the interest in the sensing and control of CAVs

A Driving Risk Surrogate and Its Application in Car-Following Scenario at Expressway

Traffic safety is important in reducing death and building a harmonious society. In addition to studies of accident incidences, the perception of driving risk is significant in guiding the implementation of appropriate driving countermeasures. Risk assessment can be conducted in real-time for traffic safety due to the rapid development of communication technology and computing capabilities. This paper aims at the problems of difficult calibration and inconsistent thresholds in the existing risk assessment methods. It proposes a risk assessment model based on the potential field to quantify the driving risk of vehicles. Firstly, virtual energy is proposed as an attribute considering vehicle sizes and velocity. Secondly, the driving risk surrogate(DRS) is proposed based on potential field theory to describe the risk degree of vehicles. Risk factors are quantified by establishing submodels, including an interactive vehicle risk surrogate, a restrictions risk surrogate, and a speed risk surrogate. To unify the risk threshold, acceleration for implementation guidance is derived from the risk field strength. Finally, a naturalistic driving dataset in Nanjing, China, is selected, and 3063 pairs of following naturalistic trajectories are screened out. Based on that, the proposed model and other models use for comparisons are calibrated through the improved particle optimization algorithm. Simulations prove that the proposed model performs better than other algorithms in risk perception and response, car-following trajectory, and velocity estimation. In addition, the proposed model exhibits better car-following ability than existing car-following models