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This study conducts a comparative assessment of subjective experience of real-world and simulated world driving for investigating factors leading to simulator sickness. Thirty professional car drivers drove a fixed-base driving simulator in real and simulated worlds under No Time Pressure (NTP) and Time Pressure (TP) driving conditions. Drivers rated their perceptions based on real-world driving and simulator driving experiences after each driving session with respect to three factors: simulator sickness, mental workload, and sense of presence. The structural equation model results revealed that drivers experienced high mental workload due to TP driving conditions (factor loading = 0.90) and repeated exposure to simulated world (factor loading = 0.20) which induced simulator sickness (factor loading = 0.41) and resulted in low sense of presence (factor loading = -0.18). Thus, it can be concluded that lack of experience with virtual reality induced high simulator sickness, increased mental workload, and low sense of presence.

In India, over 25,000 pedestrian fatalities occur due to road crashes every year. While several studies have identified possible causative factors that contribute to these fatalities, little is known about how pedestrians perceive their surrounding environment. This study attempts to bridge this gap by analysing the pedestrian perception of the built environment and traffic-related aspects considering urban roads (arterial and sub-arterial). Fourteen parameters were selected to assess pedestrian perception, and four factors were derived through factor analysis. The obtained factor scores were then subjected to two-step cluster analysis to determine whether pedestrian perception is different for people from different socio-economic demographics with varying travel behaviour. Based on the results obtained from the descriptive analysis, the respondents were most satisfied with the 'quality of streetlights at sidewalks' and 'visibility/sight distances', while they were most dissatisfied with 'pedestrian volume at sidewalks' and 'lighting facilities at crossings'. From the cluster analysis, it can be summarized that female pedestrians walk less frequently than males and perceive a higher probability of collision or near-collision incidents against male pedestrians. The study findings can aid the policymakers in the assessment of the pedestrian perception of the existing road infrastructure and suggest improvements to ensure pedestrian safety.

Mobile phone distraction is a significant contributor to pedestrian injuries. However, mobile phone engagement among pedestrians has been scarcely explored in a developing country like India. The present study utilized the beliefs-based theory of planned behaviour to examine the association between pedestrian beliefs towards distracted walking (behavioural, normative, and control) and their mobile phone use frequencies. Based on a survey of 560 pedestrians (64.6% males), it was found that the major use of mobile phones was for listening to music (30.7%), followed by receiving a call (25%), making a call (18.9%), texting (9.8%), navigation (8.5%) and internet browsing (7.1%). A series of multivariate ANOVAs and logistic regression models were developed to investigate the relationships between the beliefs and frequencies of mobile phone use in hands-free and hand-held conditions. Significant multivariate differences were found for behavioural and normative beliefs in hands-free conditions and all three types of beliefs in hand-held conditions. The frequency of mobile phone use was significantly predicted by normative beliefs (

Alcohol-impairment of drivers has significant influence on road traffic safety; however, no experimental research has been conducted on the lateral driving control of Indian drivers. Therefore, the present study investigates the effects of different Blood Alcohol Concentration (BAC) levels (0%, 0.03%, 0.05% and 0.08%) and driver attributes on the lane positioning and steering control of Indian drivers.A driving simulator experiment was designed where 82 adult licensed drivers (62 males, 20 females) completed driving on the simulated urban arterial road environment under the influence of varying BACs. Lateral driving performance measures associated with lane positioning (lane position variability) and steering control of drivers (steering angle variability and steering reversal rates (SRR)) were analyzed.The findings reported that lane position variability was significantly influenced only at 0.08% BAC (5.8% increment); no significant influence was observed at 0.03% and 0.05% BACs. Compared to 0% BAC, steering angle variability increased by 0.105 degrees or 15.7%, 0.142 degrees or 21.4%, and 0.176 degrees or 25.7% at 0.03%, 0.05% and 0.08% BACs respectively. No significant differences were observed between the sober-state driving and alcohol-impaired driving at 1In conclusion, the outcomes of this study provide novel insights into the alcohol-impaired lateral vehicle control of Indian drivers which can assist in policy interventions aiming to reduce crashes with alcohol as a major crash causation factor.

We, the Editor and Publisher of Traffic Injury Prevention, have retracted the following article:Ankit Kumar Yadav. Psychological predictors behind the intention to drink and drive among female drivers: Application of extended theory of planned behavior. Traffic Injury Prevention. 2020. https://doi.org/10.1080/15389588.2019.1703961.The author has requested the retraction of his article due to an error in one of the collected psychological measures. During data extraction, the responses for 'attitude' and 'intention' measures were switched and may have influenced the findings from the developed regression model and its results. As a result, the Editor and Publisher have agreed to retract the article in full.We have investigated and have been informed in our decision-making by our policy on publishing ethics and integrity and the COPE guidelines on retractions.The retracted article will remain online to maintain the scholarly record, but it will be digitally watermarked on each page as "Retracted".

OBJECTIVE Driving While Intoxicated (DWI) is a significant threat to traffic safety worldwide, but little is known about the motivational factors behind the willingness to drink and drive especially in low- and middle-income countries (LMICs) such as India. The present study applied an extended version of prototype willingness model (PWM) to investigate the factors predicting the willingness to drink and drive. METHODS One hundred and forty-three participants (77% males) responded to an online survey in India. The survey included the standard PWM constructs such as attitudes, subjective norms, prototype similarity and prototype favourability. Additionally, the measures of traffic fatalism and risk-perceptions were also incorporated to examine their effects on the willingness to drink and drive. RESULTS The hierarchical regression model showed that the PWM constructs explained 84% of the variance in willingness to drink and drive. When the additional measures (traffic fatalism and risk perception) were included along with the PWM variables, it resulted in an increase of additional 2% of the variance in explaining the willingness, thereby leading to a total of 86%. In both the steps, the variable "attitudes" was found to be the strongest predictor of willingness to drink and drive. CONCLUSIONS This study is first of its kind to evaluate the effectiveness of PWM model in Indian scenario for understanding the willingness to engage in the act of drunk driving. The study findings may prove useful to the stakeholders of educational and awareness programs, where the focus is required to be aimed at attitudes, subjective norms, prototype similarity and fatalistic beliefs of the drivers.

Objective: The present study examines the accelerating and braking behaviors of drivers at different blood alcohol concentrations (BACs) in heterogeneous driving conditions using driving simulator experiments. Methods: Eighty-two licensed drivers performed simulated driving in a rural road environment designed in the driving simulator at 4 BAC levels: 0.00, 0.03, 0.05, and 0.08%. Driving performance was analyzed using vehicle control variables such as mean acceleration and mean brake pedal force. Generalized linear mixed models were developed to quantify the effect of different alcohol levels and explanatory variables such as driver’s age, gender, and other factors on the driving performance indicators. Results: Alcohol use was reported as a significant factor affecting the accelerating and braking performance of drivers. The acceleration model results indicated that drivers’ mean acceleration increased by 0.013, 0.026, and 0.027 m/s2 for BAC levels of 0.03, 0.05, and 0.08%, respectively. Results of the brake pedal force model showed that drivers’ mean brake pedal force increased by 1.09, 1.32, and 1.44 N for BAC levels of 0.03, 0.05, and 0.08%, respectively. Age was a significant factor in both the models where a 1-year increase in driver age resulted in a 0.2% reduction in mean acceleration and a 19% reduction in mean brake pedal force. Driving experience could compensate for the negative effects of alcohol to some extent while driving. Conclusions: The findings of the present study revealed that drivers tend to be more aggressive and impulsive under the influence of alcohol, which deteriorates their driving performance. Impairment in accelerating and braking behaviors of drivers under the influence of alcohol leads to increased crash probabilities. The conclusions may provide reference in making countermeasures against drinking and driving and contribute to traffic safety.

Speed compliance of drivers plays a significant role in influencing crash risks, and remains a major road safety issue. Majority of the speed compliance behavioral studies have been conducted in the western world; relatively little knowledge is available about the speed compliance of the drivers of developing nations. The present study aims to investigate the speed compliance behavior of Indian drivers in changing driving environment, and to identify the significant predictors influencing their speed compliance.The driving scenario (consisting of rural and urban driving environments) representing heterogenous Indian driving conditions was designed on a driving simulator where eighty-two licensed drivers completed the driving task. Driver attributes (demographics and driving characteristics) were recorded with the help of a self-reported questionnaire. Speed compliance of drivers was estimated as an indication of the difference of driving speed from the posted speed limit of a particular driving environment, averaged over the duration of driving. The low speed difference indicated better speed compliance of drivers and vice-versa. A Generalized Linear Model (GLM) was developed using speed difference as the dependent variable along with driving environments and driver attributes as predictor variables.Speed compliance of drivers was found to be better in urban driving environment compared to rural driving environment, indicating that drivers were less able to adapt to the corresponding speed limits in rural environment. Drivers' age was positively associated with the speed compliance. For male drivers, speed compliance was found to be lower than the female drivers. Compared to the drivers who studied till their secondary education, speed compliances of post-graduate and graduate drivers were found to be better. Moreover, driving experience was observed as a negative predictor of speed compliance. Drivers who had prior crash history were found to have better speed compliance compared to the other drivers. Other predictors such as vehicle type and preferred time of driving did not show any significant influence on the speed compliance of drivers.This is the first exploratory study which investigated the speed compliance behavior of Indian drivers. Findings of the present study may assist the road safety strategies and policy interventions in reducing the speed-related crashes.

Objective: Driving errors contribute to traffic crashes and thus the causal factors associated with driving errors are of great interest to the road safety researchers. The present study attempts to identify and quantify the effects of various risk factors that are likely to influence driving error with the application of structural equation modeling (SEM). These risk factors include blood alcohol concentration (BAC) levels (0%, 0.03%, 0.05%, and 0.08%), different driving environments (rural, urban), and driver attributes (such as age, gender, education). Method: Eighty-two licensed drivers participated in a driving simulator experiment. They completed driving under the influence of 4 BAC levels in the driving environments within the framework of a full-factorial within-subjects design. Driving error was modeled as an unobserved latent variable based on several driving simulator indicators. An SEM approach was utilized to examine the influence of BAC level, driving environment, and driver attributes on the latent variable pertaining to driving error. Results: The findings suggest the suitability of an SEM approach in the investigation of driving error. The results revealed that all 3 positive BACs (0.03%, 0.05%, and 0.08%) had a significant positive influence on driving error compared to 0% BAC, and the tendency toward driving error increased with increasing BAC (factor loadings for 0.03%, 0.05%, and 0.08% BAC were 0.22, 0.31, and 0.37, respectively). Moreover, driving in an urban environment led to more driving errors compared to a rural environment, including sober drivers. Among the driver attributes, gender and awareness about drink and drive laws were the only factors influencing driving error. Conclusion: This study highlights a novel approach to investigate driving error by modeling it as a latent variable instead of modeling individual performance measures. The successful execution of SEM in alcohol impairment research may serve as a significant step in the human factors field moving from piecemeal analysis to a combined analysis where interrelationships among numerous risk factors and driving error can be established. The study outcomes may serve as a reference while developing strategies to enhance road traffic safety where special emphasis can be given to the critical risk factors influencing driving error identified in the study.

Driving error is an intrinsic component of unsafe driving behaviour. Even though alcohol results in substantial crash fatalities on Indian roads, there is hardly any evidence-based research on alcohol impairment in the driving errors of Indian drivers. The present study examined the effects of differentiated Blood Alcohol Concentration (BAC) levels (0%, 0.03%, 0.05%, and 0.08%) on the driving errors of Indian drivers. 82 volunteers participated in the driving simulator study and drove in rural and urban environments in a randomized and counterbalanced order. Generalized negative binomial regression models were developed for longitudinal and lateral driving error measures. Compared to the sober state, the increments in speed limit violations were 53%, 138% and 143% in rural driving environment, and 68%, 89%, 95% in urban driving environment at 0.03%, 0.05% and 0.08% BACs. While 0.03% and 0.05% BACs did not significantly influence the lane excursions in rural environment, 0.08% BAC resulted in 107% increment; corresponding increments were 71%, 84%, and 148% in urban environment. In rural environment, 0.03%, 0.05% and 0.08% BACs resulted in 28%, 39% and 58% increments in low RPM frequencies (RPM 5000). In urban environment, the increments were 35%, 56% and 71% for low RPMs at 0.03%, 0.05% and 0.08% BACs; whereas, for high RPMs, the increments at 0.05% and 0.08% BACs were 45% and 67% respectively (no significant influence of 0.03% BAC). The study identified the significant risk factors influencing driving errors, thereby sketching the risky driving profiles.

Braking performance of drivers is a crucial factor in evaluating the collision patterns and implementing road safety measures. Further, alcohol is known to impair driving control. The present study aims to examine the influence of a comprehensive range of Blood Alcohol Concentration (BAC) levels (0%, 0.03 %, 0.05 % and 0.08 %) on brake transition times of drivers. As young drivers show significantly higher crash risks compared to the experienced drivers, fifty-four young Indian drivers in the age group of 21-25 years (forty males and fourteen females) participated in the driving simulator experiments. The study adopted the framework of a within-subjects design, where each driver encountered rural and urban driving scenarios in a counterbalanced order, during experimental driving at each of the four BAC levels. Their brake transition times were estimated with respect to sudden pedestrian crossing events. Weibull Accelerated Failure Time (AFT) models with shared frailty were developed for quantifying the effects of BAC levels along with driver attributes on brake transition time. Preliminary analysis showed significant main effects of BAC (p0.001) and driving environment (p = 0.002) on brake transition time; however, their interaction effect was not significant (p = 0.485). The models revealed that 0.03 %, 0.05 % and 0.08 % BACs significantly reduced the brake transition times by 16 %, 28 % and 52 % in rural driving environment, and by 23 %, 37 % and 53 % in urban driving environment, compared to 0% BAC. The study outcomes may find application in assisting collision warning systems which take into account the braking behaviour of drivers.

Speeding behaviour is known to influence crash risk among alcohol-impaired drivers, but this relationship is scarcely explored. The present study investigated the effects of different Blood Alcohol Concentrations (BAC) levels on driving performance with respect to mean speed of drivers and their ability to avoid crashes during sudden events while driving. Eighty-two drivers participated in the simulation driving experiment at four BAC levels (0%, 0.03 %, 0.05 % and 0.08 % BAC) in rural and urban driving scenarios. Two sudden events (pedestrian crossing and road crossing by parked vehicles (a car and a truck) in the perpendicular direction of traffic) were designed to evaluate the crash probabilities in both the driving scenarios. Generalized linear mixed models were developed to analyse the effects of BAC levels and driver attributes (e.g., age, gender) on mean speeds and crash probabilities. Results for mean speed showed that, compared to sober state, drivers drove 3.5 kmph, 5.76 kmph and 8.78 kmph faster at 0.03 %, 0.05 % and 0.08 % BAC respectively in the rural environment and this increment was 3.6 kmph, 3.69 kmph and 4.13 kmph in the urban environment. The model results for crash probabilities revealed that 0.03 %, 0.05 % and 0.08 % BAC levels increased the crash probabilities by 1.9 times, 2 times and 3 times in case of the rural environment and 2 times, 2.3 times and 3.5 times respectively in the urban driving environment.