Landscape heritage objects' effect on driving: a combined driving simulator and questionnaire study

Assessing the determinants of crash propensity using structural equation modeling: Role of distractions caused by fellow drivers

INTRODUCTION

Aggressive behavior of drivers is a source of crashes and high injury severity. Aggressive drivers are part of the driving environment, however, excessive aggressive driving by fellow drivers may take the attention of the recipient drivers away from the road resulting in distracted driving. Such external distractions caused by the aggressive and discourteous behavior of other road users have received limited attention. These distractions caused by fellow drivers (DFDs) may agitate recipient drivers and ultimately increase crash propensity. Aggressive driving behaviors are quite common in South Asia and, thus, it is necessary to determine their contribution to distractions and crash propensity.

METHOD

Our study aimed to evaluate the effects of DFDs using primary data collected through a survey conducted in Lahore, Pakistan. A total of 801 complete responses were obtained. Various hypotheses were defined to explore the associations between the latent factors such as DFDs, anxiety/stress (AS), anxiety-based performance deficits (APD), hostile behavior (HB), acceptability of vehicle-related distractions (AVRD), and crash propensity (CP). Structural Equation Modeling (SEM) was employed as a multivariate statistical technique to test these hypotheses.

RESULTS

The results supported the hypothesis that DFDs lead to AS among recipient drivers. DFDs and AS were further found to have positive associations with APDs. Whereas, there was a significant negative association between DFD, AS, and AVRD. As hypothesized, DFD and AS had positive associations with CP, indicating that distractions caused by aggressive behaviors leads to stress and consequently enhances crash propensity.

PRACTICAL APPLICATIONS

The results of this study provide a statistically sound foundation for further exploration of the distractions caused by the aggressive behaviors of fellow drivers. Further, the results of this study can be utilized by the relevant authorities to alter aggressive driving behaviors and reduce DFDs.

Personality, perceptions and behavior: A study of speeding amongst drivers in Victoria, Australia

INTRODUCTION

Road crashes present a serious public health issue. Many people are seriously or fatally injured every year in avoidable crashes. While these crashes can have multiple contributing factors, including road design and condition, vehicle design and condition, the environment and human error, the performance of illegal driving behavior, including speeding, may also play a role. The current study aimed to examine the mediating influence that four potential deterrents (perceptions towards enforcement, crash risk, social norms and disapproval, and negative personal/emotional affect) have between the Big Five personality traits (conscientiousness; extraversion; agreeableness; neuroticism; openness) and expectations to speed.

METHODS

A total of 5,108 drivers in Victoria, Australia completed an online survey in 2019. A mediated regression analysis was used to examine pathways in a conceptual model developed for the study.

RESULTS

The results showed that perceptions towards the four potential deterrents examined did mediate the relationship (either completely or partially) between personality and expectations to speed.

CONCLUSIONS

The results of this study suggest that if interventions to deter illegal driving behavior are to be successful, one factor that could be taken into account is the personality traits of drivers who may be at greatest risk of the performance of illegal driving behaviors.

Saccades and driving

Driving is not only a physical task, but is also a mental task. Visual inputs are indispensable in scanning the road, communicating with other road users and monitoring in-vehicle devices. The probability to detect an object while driving (conspicuity) is very important for assessment of driving effectiveness, and correct choice of information relevant to the safety of driving determines the efficiency of a driver. Accordingly, eye fixation and eye movements are essential for attention and choice in decision making. Saccades are the most used and effective means of maintaining a correct fixation while driving. In order to identify the features of the most predisposed subjects at high driving performances and those of the high-level sportsmen, we used a special tool called Visual Exploration Training System. We evaluated by saccade and attentional tests various groups of ordinary drivers, past professional racing drivers, professional truck drivers and professional athletes. Males have faster reaction time compared to females and an age below 30 seems to guarantee better precision of performance and accuracy in achieving all visual targets. The effect on physical activity and sports is confirmed. The performances of the Ferrari Driver Academy (FDA) selected students who were significantly better than those of a group of aspiring students and amateur racing drivers probably thanks to individual predisposition, training and so-called ‘neural efficiency’.

Quantifying visual road environment to establish a speeding prediction model: An examination using naturalistic driving data

Speeding is one of the major contributors to traffic crashes. To solve this problem, speeding prediction is recognized as a critical step in a pre-warning system. While previous studies have shown that speeding is affected by road environmental design, research in predicting speeding behavior through road environment features has not yet been conducted. Furthermore, there is a large discrepancy between actual and perceived road environmental information given that a driver's visual perception plays a crucial role as the dominant source of information in determining driver's behavior. Thus, this paper aims to establish a speeding prediction model based on quantifying the visual road environment to improve the design of pre-waring systems, which can predict whether drivers are going to speed and provide them with visual or/and audio warnings about their current driving speed and the speed limit prior to the occurrence of speeding behavior. Twenty input variables derived from three categories including visual road environment parameters, vehicle kinematic features, and driver characteristics were considered in the proposed speeding prediction model. Especially, the road environmental design factors consisting of the visual road geometry and visual roadside environment as perceived by the driver's eyes were quantified using a visual road environment model. Field experiments were conducted to collect naturalistic driving data concerning speeding behavior on the typical two-lane mountainous rural highways in five provinces of China. Random Forests, an ensemble learning method for regression and classification, were applied to build the speeding prediction model and variable importance was calculated. Additionally, logistic regression was used as a supplement to further investigate factors impacting on speeding behavior. A speeding criterion was defined with two levels in this study: a lower level (exceeding the posted speed limit) and a higher level (10% above the posted speed limit). Under both levels of the speeding criterion, the speeding prediction model performed well with high accuracy (over 85%). This model could use the value of the variables obtained from the current position to predict drivers' speeding behavior at the future position located a sighting distance away. This interval was sufficient for a pre-warning system to give a speeding warning that a driver with normal perception-reaction time (around 2.5 s) could respond to. Findings in this study can be used to effectively predict speeding in advance and help to reduce speeding-related traffic accidents.

Validation of the influencing factors associated with traffic violations and crashes on freeways of developing countries: A case study of Iran

Among the rural roads, freeways have the maximum allowable speed limit. This subject increases the tendency of drivers to use these kinds of roads, and despite its positive effects, it has caused numerous problems. One of them is the increase in the rate of traffic violations and crashes. The amount of crashes per kilometer in Iran's freeways is almost twice the other rural roads. Hence, finding a solution to this problem is of particular importance. This research intends to validate some of the influencing factors which cause traffic violations and crashes in freeways and determine their amount of influence through statistical models. For this purpose, the authors considered violations and crashes for 36 road segments as dependent variables and other factors as independent ones. Since dependent variables were count, discrete, and non-zero, the proposed models were Poisson and Zero-truncated Poisson. The processing of the models indicated that the amounts of Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) indices for the Zero-truncated Poisson model are less than those of the Poisson model and the result of the Pseudo-R² test for this model is within the acceptable range. Moreover, the result of Chi-square test which shows the proximity of expected and observed amounts was better for Zero-truncated Poisson model. Thus, this model has a considerable advantage against Poisson model. Final models indicated that the average speed has a positive correlation with the number of violations and crashes and as it increases, they increase too. Besides, peripheral landscapes, number of interchanges, number of passing lanes, and exemption from paying toll have an opposite relationship with violations and crashes.

Visual Landscape Quality as Viewed from Motorways in Spain

Motorways are large infrastructures that alter the environmental resources in a territory, while constituting an important element through which the individual comes into contact with the landscape. Motorways are integrated in the landscape through their layout design and construction, the aesthetic details of minor structures (design and building materials) and the treatment of embankments and landscape planting. In this paper, we test the following hypotheses: motorway elements are related to the perception of landscape quality—from the point of view of the road users—and the aesthetic characteristics of minor infrastructures and planting affect the quality of the landscape perceived from the roads. These research questions were tested by comparing the visual quality of the landscapes captured in 128 photographs taken from sections of motorways in Spain. We compared the results obtained from (a) a photo-based method, and (b) the public’s landscape preferences determined using a survey of 737 people. The results show a correlation between the landscape quality values obtained using the model and the landscape preferences expressed by the public. We also found that the presence of the motorway elements and their aesthetic characteristics are significant in the users’ perception. These results can be applied in the decision-making process for potential investments to integrate new and existing motorways in the landscape.

Development of a statistical model for predicting seat pressure felt level in simulated condition based on direct and anthropometric measurement

[Purpose] The purpose of this study was to investigate the effects of seat pressure distribution measurements based on a specific posture to predict the pressure felt level when seated. [Subjects and Methods] To examine the relationship between body pressure data and the driver's perception, eleven subjects were selected to participate in a simulated driving experiment using a pressure mat as a direct measurement method to measure the seat pan's pressure distribution. The buttock-popliteal length was measured using an anthropometer, and the pressure felt ratings evaluated after the body pressure measurements were recorded. Accordingly, this was then followed by performing statistical analysis using seat pressure measurements, and the buttock-popliteal length as independent variables along with subjective ratings selected of the pressure felt by the drivers' as dependent variables. [Results] The findings of this study suggest that the direct measurements and anthropometric body data are positively correlated with the predictive model thereby confirming the validity of the model with an R² value of 0.952. [Conclusion] The proposed model is expected to provide a useful reference value for new vehicle drivers by providing the pressure felt level based on direct and body measurements in a specific posture.

The Experience of Risk-Adjusted Capitation Payment for Family Physicians in Iran: A Qualitative Study

Background

When a country’s health system is faced with fundamental flaws that require the redesign of financing and service delivery, primary healthcare payment systems are often reformed.

Objectives

This study was conducted with the purpose of exploring the experiences of risk-adjusted capitation payment of urban family physicians in Iran when it comes to providing primary health care (PHC).

Materials and Methods

This is a qualitative study using the framework method. Data were collected via digitally audio-recorded semi-structured interviews with 24 family physicians and 5 executive directors in two provinces of Iran running the urban family physician pilot program. The participants were selected using purposive and snowball sampling. The codes were extracted using inductive and deductive methods.

Results

Regarding the effects of risk-adjusted capitation on the primary healthcare setting, five themes with 11 subthemes emerged, including service delivery, institutional structure, financing, people’s behavior, and the challenges ahead. Our findings indicated that the health system is enjoying some major changes in the primary healthcare setting through the implementation of risk-adjusted capitation payment.

Conclusions

With regard to the current challenges in Iran’s health system, using risk-adjusted capitation as a primary healthcare payment system can lead to useful changes in the health system’s features. However, future research should focus on the development of the risk-adjusted capitation model.