An analysis of motorcyclists' injury severities in work-zone crashes with unobserved heterogeneity

Work-zone related crashes in Florida are increasing steadily in recent years. With such growing concern, work-zone is recognized in Florida Strategic Highway Safety Plan. The severity and complexity of motorcycle crashes in work-zones is critically important and worth investigating. However, the resulting effect of work-zone on motorcyclists' injuries in work-zone crashes is not fully understood. The purpose of study is to identify the contributing factors of motorcyclists' injury severity sustained in the work-zone crashes in Florida. Recognizing the relatively higher risk of motorcyclists in work-zones with respective to non-work-zones, this study further uncovers the contributing factors for single- and multi-vehicle motorcycle crashes in Florida work-zones. This study investigated motorcyclists' injury severity applying random parameter multinomial logit with possible heterogeneity in means and variances of the random parameters for single-motorcycle and multi-vehicle motorcycle crashes. This study utilizes the Crash Analysis Reporting (CAR) system in Florida over a period of five years from 2012 to 2016 (inclusive). The model result indicates a complex relationship between dark condition, old-aged motorcyclist (50–65), requirement and absence of endorsement, partial ejection, straight roadway segment, shoulder width (up to 1.22 m (4 ft), and 2.74–3.66 m (9–12 ft), urban interstate, activity area, and lane closure and work on shoulder-median work-zone types. The effect of work-zone on single-motorcycle crashes tends to have much more in resulting injury severities relative to multi-vehicle motorcycle crashes. It is more important to investigate the injury severity by single- and multi-vehicle crashes involving motorcycles in work-zones. These risk factors identified in the study are expected to provide more insights for the countermeasures specific to engineering (roadway design) and policy (motorcycle training), which can be considered to improve motorcycle safety in Florida.     

Behavioral aspects of safety culture: Identification of critical safety-related behaviors of motorcyclists in Indonesia's urban areas via the application of behavioral-based safety programs

Many violations and accidents involving motorcyclists occur in the urban areas of Indonesia. It can be said that the failure to develop a good traffic safety culture causes poor motorcyclist behavior, as shaped by existing programs and mechanisms. This study aimed to identify motorcyclists' critical behaviors by conducting investigations using the reciprocal safety culture model as a framework. We tried to identify and clarify the safe behaviors expected by local governments from the existing driving safety program. By applying the antecedent-behavior-consequence model of the behavioral-based safety program, we obtained sixty-three behaviors associated with the six criteria of safe driving. We surveyed motorcyclists (N = 97) to review the sixty-three motorcyclist behaviors in the urban area. The relationship between the behavioral and psychological aspects of the reciprocal safety culture model was investigated to obtain the motorcyclists' critical behaviors. Multiple linear regression model, optimized by the stepwise regression, described the influence motorcyclist behavior on the perception of driving safety. We identified eight critical safety-related behaviors engaged in by motorcyclists. Observation revealed some cultural issues embedded in motorcyclists' eight critical safety-related behaviors that need to be intervened by the local government. The reciprocal safety culture model could be applied in the behavioral-based safety program to approach traffic safety culture issues. In order to develop a good traffic safety culture in the urban area, the local government needs to review the existing driving safety program by understanding drivers' behaviors as they relate to such a program.     

Effectiveness evaluation on cross-sector collaborative education programs for traffic safety toward sustainable motorcycle culture in Vietnam

Motorcycle injuries have caused serious implications for public health and national economies in many ASEAN countries. Drivers' lack of road safety awareness and low level of voluntary compliance hinder the promotion of traffic safety. Against this background, the Vietnamese government cooperated with motorcycle manufacturers in a wide range of educational activities. This study evaluates the effectiveness of cross-sector collaborative education programs implemented in Vietnam through a series of statistical analyses. Utilizing a sample of 600 respondents, we focus on the educational effects on riders' attitudes, behaviors, accident prevention, and riders' psychological changes after participating in safety activities. The results show that the effectiveness of rider training differed depending on riders' experience. Motorcyclists' improvement in risk awareness mainly results from the enhancement of safety awareness. The structural model revealed that safety activities have positive effects on motorcyclists' riding confidence, safety awareness, joy and comfort while riding, independence and freedom in daily life, and perspective-taking abilities. Altruistic motivation is suggested as the key factor to encourage motorcyclists' safe riding, highlighting the importance of building up traffic moral and expanding traffic safety culture across the country. With an attempt to find out the insufficient and missing content from the present training programs, this study seeks to inform policy decisions on accident prevention as well as promote motorcyclists' well-being based on the sustainable motorcycle culture in ASEAN countries.     

Motorcycle fatalities in Malaysia

Malaysia has the highest road fatality risk (per 100,000 population) among the ASEAN countries and more than 50% of the road accident fatalities involve motorcyclists. This study has collected and analysed data from the police, government authorities, and national and international research institutes. Only fatality data are used due to the severe underreporting of severe injuries (up to 600%) and slight injuries (up to 1400%). The analysis reveals that the highest numbers of motorcycle fatalities occur in rural locations (61%), on primary roads (62%) and on straight road sections (66%). The majority are riders (89%), 16 to 20 years old (22.5%), and 90% of the motorcycles are privately owned. Of those involved in fatal accidents, 75% of the motorcyclists wear helmets, and 35% do not have proper licences. The highest number of fatalities by type of collision is ‘angular or side’ (27.5%). Although fatal motorcyclist crashes mostly involve ‘passenger cars’ (28%), motorcyclists are responsible for 50% of the collisions either by crashing singly (25%) or with other motorcyclists (25%). While male motorcyclists predominate (94% of fatalities), female motorcyclists aged 31 to 70, possessing ‘no licence’, not wearing helmets and travelling during the day, account for a higher percentage than male motorcyclists. Malaysia must acquire more motorcycle exposure data and establish an injury recording system and database based on hospital-records. To reduce motorcycle fatalities, it first has to understand why young male motorcyclists are prone to fatal crashes in the evenings and on weekends on rural primary roads, especially on straight road sections.     

Developing a safer road user behaviour index

Road user behaviour is an essential factor of increasing the rate of traffic accidents worldwide. Road safety experts and scientists consider aspects of road users' behaviour to be the main risk factors for road fatalities. These factors include drinking alcohol, speeding, not wearing seat belts, not wearing helmets when riding two-wheeled vehicles, not using child restraints, consuming illegal drugs, and being distracted by mobile phone use. This paper aims to investigate the role of these factors in assessing the road user behaviour through aggregating them and build a composite indicator that can be used in countries benchmarking and cross countries comparison, then identifying most successful practises. To achieve this aim, data related to the selected indicators, life-saving rate, and real crash data were collected. The indicators were weighted using simple and theoretical methods. The weighted indicators were aggregated using simple additive method. The developed index was applied to 12 European countries to test the validation of the index through investigation the correlation between index’ ranking of countries with the ranking according to the rate of fatalities. It is concluded that the developed composite indicator can be used to assess the role of using the protection system and speeding in the severity of the road crashes. However, the role of the remaining factors in the likelihood of crashes occurrence needs more investigation. It can be concluded also that the road users' behaviour is not the only factor of reducing the road fatalities in some countries. This enhances the multidimensional system approach of defining the road safety. Based on this, it is recommended to consider other factors in conducting research, developing indices of road safety, and in recommending solutions. The results show also that the UK, Sweden, Ireland and Ireland have the most successful strategies to improve the road user behaviour among the selected countries; therefore, it is recommended to take lessons from these practices.     

Behavioral factors of motorcyclists in right-turn movements at unsignalized intersections: An insight from Yogyakarta,Indonesia

Conflicting actions of motorcyclists making right-turn movements (RTM) pose a considerable risk of accidents, which is of great concern when attempting to augment the level of safety at unsignalized intersections. This study was conducted to identify the habits of motorcyclists in RTMs, including normal RTM, weaving/merging RTM, and opposite indirect RTM when crossing unsignalized intersections. The behavioral factors were affected by gender, passenger status, motorcycle type, STOP factor, speed, travel time, and lane width of major and minor roads, which were tested using multinomial and nested logit models on 2358 motorcyclists. The results indicated that all of the observed variables significantly influenced motorcyclists' behaviors at unsignalized intersections, excepting the variable of travel time. The factors of speed and lane width on minor roads significantly correlated to motorcyclist behaviors during weaving and merging RTM only. The logit model reveals that female motorcyclists tend to make normal RTMs. The study also proposes ideal and practical recommendations, such as stop and speed regulations, channelization, number of lanes and lane widths, and maneuver markers, in order to address dangerous behaviors, in particular weaving and merging and opposite indirect-type RTMs.     

Factors affecting lane change crashes

This study aims to investigate the contributing factors affecting the occurrence of crashes while lane-changing maneuvers of drivers. Two different data sets were used from the same drivers' population. The first data set was collected from the traffic police crash reports and the second data set was collected through a questionnaire survey that was conducted among 429 drivers. Two different logistic regression models were developed by employing the two sets of the collected data. The results of the crash occurrence model showed that the drivers' factors (gender, nationality and years of experience in driving), location and surrounding condition factors (non-junction locations, light and road surface conditions) and roads feature (road type, number of lanes and speed limit value) are the significant variables that affected the occurrence of lane-change crashes. About 57.2% of the survey responders committed that different sources of distractions were the main reason for their sudden or unsafe lane change including 21.2% was due to mobile usage. The drivers' behavior model results showed that drivers who did sudden lane change are more likely to be involved in traffic crashes with 2.53 times than others. The drivers who look towards the side mirrors and who look out the windows before lane-change intention have less probability to be involved in crashes by 4.61 and 3.85 times than others, respectively. Another interesting finding is that drivers who reported that they received enough training about safe lane change maneuvering during issuing the driving licenses are less likely to be involved in crashes by 2.06 times than other drivers.     

Exploring factors contributing to injury severity at work zones considering adverse weather conditions

Despite recent efforts to improve work zone safety, the frequency and severity of crashes at work zones are still considerably high. The effect of work zones on traffic safety can be exacerbated by adverse weather conditions. As an example, a sudden reduction in visibility may intensify the severity of work zone crashes. There is a lack of studies that strive to gain a good understanding of the effect of weather on the severity of work zone crashes. In this study, an Ordered Probit Model was developed to identify factors affecting the severity of work zone crashes in different spatial, temporal, and environmental conditions in Washington state using five-year of work zone-related crashes (2009–2013). The interesting findings of this study showed that weather and lighting conditions are among the most important factors influencing the severity of crashes at work zones. Lack of daylight was found to be a determining factor in increasing the severity of work zone crashes, specifically, during dusk and dawn. It was also found that although drivers have less severe work zone-related crashes in adverse weather conditions, the interactions between adverse weather conditions and other contributing factors might increase the severity of work zone crashes. The results of this study will help traffic engineers to design effective safety countermeasures considering different contributing factors including the weather and lighting conditions in the work zone planning and installation stages to prevent safety deficiencies.     

Car drivers' road safety performance: A benchmark across 32 countries

The road safety performance of a country and the success of policy measures can be measured and monitored in different ways. In addition to the traditional road safety indicators based on the number of fatalities or injured people in road traffic crashes, complementary road safety performance indicators can be used in relation to vehicles, infrastructure, or road users' behaviour. The last-mentioned can be based on data from roadside surveys or from questionnaire surveys. However, results of such surveys are seldom comparable across countries due to differences in aims, scope, or methodology.This paper is based on the second edition of the E-Survey of Road Users' Attitudes (ESRA), an online survey carried out in 2018, and includes data from more than 35,000 road users across 32 countries. The objective is to present the main results of the ESRA survey regarding the four most important risky driving behaviours in traffic: driving under the influence (alcohol/drugs), speeding, mobile phone use while driving, and fatigued driving. The paper explores several aspects related to these behaviours as car driver, such as the self-declared behaviours, acceptability and risk perception, support for policy measures, and opinions on traffic rules and penalties.Results show that despite the high perception of risk and low acceptability of all the risky driving behaviours analysed, there is still a high percentage of car drivers who engage in risky behaviours in traffic in all the regions analysed. Speeding and the use of a mobile phone while driving were the most frequent self-declared behaviours. On the other hand, driving under the influence of alcohol or drugs was the least declared behaviour. Most respondents support policy measures to restrict risky behaviour in traffic and believe that traffic rules are not being checked regularly enough, and should be stricter.The ESRA survey proved to be a valuable source of information to understand the causes underlying road traffic crashes. It offers a unique database and provides policy makers and researchers with valuable insights into public perception of road safety.     

What affects pedestrian crossing difficulty at urban intersections in a developing country?

In developing countries, road traffic crashes involving pedestrians have become a foremost concern. At present, road safety assessment plans and selection of interventions are primarily restricted to traditional approaches that depend on the investigations of historical crash data. However, in developing countries such as India, the availability, consistency, and accuracy of crash data are major concerns. In contrast, proactive approaches such as studying road users' risk perception have emerged as a substitute method of examining potential risk factors. An individual's risk perception offers vital information on probable crash risk, which may be beneficial in detecting high-risk locations and major causes of crashes. Since the pedestrian fatality risk is not uniform across the urban road network level, it may be expected that pedestrians' perceived risk measured in terms of “crossing difficulty” would also vary across the sites. In this perspective, the present paper establishes a mathematical association between the pedestrians' perceived “crossing difficulty” and actual crashes. The model outcome confirms that pedestrians' perceived crossing difficulty is a good surrogate of fatal pedestrian crashes at the intersection level in Kolkata City, India. Subsequently, to examine the impact of traffic exposures, road infrastructure, land use, spatial factors, and pedestrian-level attributes on pedestrians' “crossing difficulty”; a set of Ordered Logit models are developed. The model outcomes show that high vehicle and pedestrian volume, vehicular speed, absence of designated bus stop, the presence of inaccessible pedestrian crosswalk, on-street parking, lack of signalized control (for both vehicle and pedestrian), inadequate sight distance, land use pattern, slum population, pedestrian-vehicular post encroachment time, waiting time before crossing, road width, and absence of police enforcement at an intersection significantly and positively increase pedestrian's crossing difficulty at urban intersections. To end, the model findings are advantageously utilized to develop a set of countermeasures across 3E's of road safety.     

An optimization model to determine an appropriate budget for improving work zone safety

In order to keep up with demand, government agencies must maintain and rehabilitate roadways so the supply to the public is met. However, while maintaining and rehabilitating roadways, work zones are a major threat to both the safety of the drivers, as well as the workers. In the U.S., 799 people were killed in work zone crashes in 2017 which comprises 2.1% of total fatalities in motor vehicle crashes. It is therefore crucial to maximize the safety within the work zone while maintaining under a limited budget. The purpose of this study is to improve work zone safety within a limited budget most efficiently. This study will develop an optimization model to determine appropriate budget for improving work zone safety. The appropriate budget can be defined as the budget below which the rate of safety improvement per dollar spending is higher than the spending above the budget. The primary factors in the model included a wide range of safety countermeasures and the implementation costs. The model identified a best mix of safety countermeasures minimizing expected number of crashes based on the crash modification factors of the safety countermeasures within an appropriate budget. The appropriate budget was determined by conducting a sensitivity analysis. The developed methodology utilized a linear integer programming to identify the best mix of safety countermeasures. The methodology was implemented on a work zone project as a case study. The developed methodology will help engineers in making funding decisions to improve safety on work zones.     

基于GIS分析的深圳市道路交通事故空间分布特征研究

掌握城市道路交通事故空间分布特征是城市道路交通安全管理的重要基础。基于深圳市2014~2016年的道路交通事故数据,首先应用地理编码方法对原始事故记录进行空间定位,形成事故的空间分布。其次针对考虑/不考虑路网密度的2种情况,应用密度分析方法对道路交通事故多发的区域和事故严重程度较高的区域进行鉴别,比较2种情况下区域分布的差异并分析造成这种差异的可能原因。最后利用异常点分析和热点分析2种空间聚类分析模型对事故严重程度较高的区域进行进一步鉴别,并对密度分析和聚类分析2种方法得到的结果进行了比较。密度分析结果表明：就事故频度而言,深圳市中心城区单位面积上的交通事故频度较高,而郊区单位长度道路上的交通事故分布更为密集;就事故严重程度而言,郊区的交通事故平均严重程度高于市中心区域。造成上述差异的原因可能与郊区道路限速较高等因素有关。聚类分析结果与密度分析结果相近,在郊区形成了高严重程度的事故聚类,而在中心城区形成了低严重程度的事故聚类,说明郊区的交通事故严重程度总体高于市中心区域。从2种方法的比较来看,密度分析简单易行,有助于交通管理部门对城市交通事故空间分布特征直观快速的了解;聚类分析可精确到事故点,为精细化的交通安全管理工作提供支撑。研究结果表明基于密度分析和聚类分析的研究方法对于确定道路交通事故空间分布特征有良好的作用。     

An international comparative study on driving attitudes and behaviors based on questionnaire surveys

Road traffic crashes (RTCs) are influenced by a driver's awareness and attitude toward road safety, as well as the socio-economic status, infrastructure development level, traffic status, social system, and traffic safety culture of the area to which the driver belongs. In this study, based on the results of a questionnaire survey conducted in seven countries, the characteristics of each country concerning tolerance for traffic violations, dangerous driving, and acceptance for road safety measures were studied. It was suggested that a high tolerance for traffic violations and dangerous driving might affect traffic violations and RTCs in each country. Additionally, to reduce the tolerance for traffic violations and dangerous driving, the promotion of road safety education, especially among young and male drivers, and stricter regulations and enforcement were suggested.     

Exclusive motorcycle lanes: A systematic review

Road accidents are the main leading cause of death, and more than half of people killed in road accidents are motorcyclists, pedestrians, and bicyclists. In developing countries, the share of motorcycles is very high in the traffic stream, which results in an increased number of accidents. Nonetheless, a high share of motorcycles and risky riding behavior of motorcyclists raise notable threats to other road users as well as themselves. Segregating motorcycles from the main traffic stream by providing an Exclusive MotorCycle Lane (EMCL) is reported as one of the strategies to improve motorcyclist's safety and overall road safety. Although EMCLs are successfully running in some Asian countries like Malaysia, Taiwan, and Indonesia, and have reported reducing motorcycle accidents, existing literature related to such lanes is limited and lacks combined contemplation of various design factors. Therefore, a systematic review of studies related to EMCL was carried out in the present paper using the PRISMA approach. The review was majorly divided into the following three categories viz., geometric design elements of EMCL, motorcyclist's flow characteristics on EMCL, and traffic control measures for EMCL to highlight the research lacunas in this field. The present study aims to cast light on the need for specific geometric design standards for EMCL and to assess the safety impact of segregating motorcyclists from other mixed traffic. The review highlights that the design standards for EMCL should be based on the motorcycle's characteristics, as it varies from other vehicle categories in terms of riding behavior and the physical properties of the motorcycle.     

Non-fatal spine injuries resulting from motorcycle crashes

This study aims to determine spinal injury patterns and identify crash factors commonly associated with serious spinal injury as a result of motorcycle crashes. Data was retrospectively collected from motorcyclists sustaining spinal injuries from road crashes treated at Kuala Lumpur Hospital, Malaysia, over the 5-year period from 2005 to 2009. Each patient's injuries were analyzed by reviewing his or her medical records for radiographic imaging and computed tomography scans.A total of 151 patients were included in this study, of which, males accounted for over 87%. The first lower lumbar (L1) was the most commonly injured vertebral level, followed by the adjacent thoracic vertebra (T12). Fracture to the vertebral body without dislocation was found to be the most frequently observed spinal injury pattern. Injury severities for a majority of patients (65%) were measured at Maximum Abbreviated Injury Scale (MAIS) of 2. Serious spinal injury was associated with thorax or upper-extremity injury.Prevalence of lumbar spinal injury in the study reflects a predominantly low-speed crash among the motorcyclist in the region. Motorcyclists are at greater odd to sustain severe spinal injury when directly striking an object compare to striking the ground during the crash event.     

基于随机参数Logit模型的校车事故伤害严重程度分析

为深入分析安全因素对校车事故伤害严重程度的影响，探寻事故数据中未观察到的异质性，基于随机参数Logit模型从驾驶员、车辆、道路特征及环境4个方面构建校车事故伤害严重程度模型。结果表明:①涉事车辆数为2辆且对应参数服从正态分布时，不发生死亡受伤事故的概率为83.84%；②驾驶员年龄35~44岁、涉事车辆数为1辆时，死亡受伤事故概率均降低0.58%；③道路限速值为40~50 km/h时发生死亡受伤事故概率增加0.35%，道路限速值大于60 km/h时发生死亡受伤事故概率增加0.96%；④安全气囊状态打开，死亡受伤事故概率增加2.35%；⑤交通控制方式为车道标线时可能伤害事故概率增加1.85%，控制方式为中央分隔带时未受伤事故概率降低1.44%，死亡受伤事故发生概率却增加0.48%；⑥不安全时倒车转弯时发生可能伤害事故概率降低0.42%，分心驾驶、未按规定车道行驶、跟车太近和其他（饮酒）时未受伤事故概率分别增加1.36%，0.56%，0.39%和0.97%，可能受伤事故和死亡受伤事故发生概率却有所降低。      

Measure of productivity loss due to road traffic accidents in Thailand

As one of the top countries with the highest casualties per capita in road traffic accidents, Thailand needs to raise public awareness about the economic loss from road traffic crashes. This paper calculates the value of productivity loss due to road traffic accidents in Thailand in 2017. Extensive data collection and analyses enable to compute income losses over time in case of fatalities, permanent disabilities as well as major and minor injuries. The results reveal that, at the end of 2017, the total amount of productivity loss caused by road traffic accidents alone was approximately 121 billion Baht (45 billions for fatalities, 7 for disabilities, 67.5 for serious injuries and 1.5 for slight injuries), or close to 0.8% of the country's GDP, which is very significant. At-risk age groups are determined in each case and we see that the 16–25 age group is bearing the highest burden in all types of accidents. Future policies can then be targeted to types of casualties and to a specific public.     

Using machine leaning techniques for evaluation of motorcycle injury severity

There is a growing interest in the application of the machine learning techniques in predicting the motorcycle crash severity. This is partly due to a progress in autonomous vehicles technology, and machine learning technique, which as a main component of autonomous vehicle could be implemented for traffic safety enhancement. Wyoming's motorcycle crash fatalities constitute a concern since the count of riders being killed in motorcycle crashes in 2014 was 11% of the total road fatalities in the state. The first step of crash reduction could be achieved through identification of contributory factors to crashes. This could be accomplished by using a right model with high accuracy in predicting crashes. Thus, this study adopted random forest, support vector machine, multivariate adaptive regression splines and binary logistic regression techniques to predict the injury severity outcomes of motorcycle crashes. Even though researchers applied all the aforementioned techniques to model motorcycle injury severities, a comparative analysis to assess the predictive power of such modeling frameworks is limited. Hence, this study contributes to the road safety literature by comparing the performance of the discussed techniques. In this study, Wyoming's motorcycle crash injury severities are modeled as functions of the characteristics that give rise to crashes. Before conducting any analyses, feature reduction was used to identify a best number of predictors to be included in the model. Also to have an unbiased estimation of the performance of different machine learning techniques, 5-fold cross-validation was used for model performance evaluation. Two measure, Area under the curve (AUC), and confusion matrix were used to compare different models' performance. The machine learning results indicate that random forest model outperformed the other models with the least misclassification and higher AUC. It was also revealed that a dichotomous response variable, with fatality and incapacitation injury in one category, along with all other categories in another group would result in a lower misclassification rate than a polychotomous response variable. This might result from the nature of motorcycle crashes, lacking a protection compared with passenger cars, preventing machine learning technique to get trained properly. Moreover, the most important variables identified by the random forest model are those related to the operating speed, resentful other party, traffic volume, truck traffic volume, riding under the influence, horizontal curvature, wide roadway with more than two lanes and rider's age.     

Investigation of helmet use behavior of motorcyclists and effectiveness of enforcement campaign using CART approach

Use of the helmet is beneficial in reducing the severity of injuries and avoiding fatalities for motorcyclists, therefore, legislation exists in almost all countries. In practice, the situation is different regarding the helmet use, especially in the developing countries. This paper investigates the helmet use behavior of motorcyclists in Karachi, Pakistan. It determines the significant factors affecting the helmet use in Karachi (Pakistan) and recommending effective campaign measures to promote helmet use. It is vital in relation to the exponential growth of motorcycle users and poor enforcement of traffic rules. Repeated cross-sectional data collected before (n = 226) and after (n = 277) the helmet use enforcement campaign is analyzed using univariate and non-parametric classification and regression tree (CART) techniques. A significant number of motorcyclists do not hold a driving license and CART analysis highlighted the significance of this variable along with exposure to the road environment (measured as daily usage of motorcycle) to explain helmet use. Campaign effects are found temporary, therefore, serious efforts are required to design coherent and structured awareness and enforcement programs.     

Modelling traffic safety at uncontrolled median openings: A case study in India

Assessment of traffic safety is an essential study in transportation engineering. In a developing country like India, around 150,000 people die in road crashes every year. Furthermore, at uncontrolled median openings, the severity of road crashes is higher due to the presence of impatient U-turning road users who don't obey the rule of priority. Traditionally, road crash data have been used since long to analyze traffic safety. However, in developing countries, the main drawback of this conventional method is limited availability of accident data as very few accidents get reported. Moreover, the accuracy of these reported data is questionable. Therefore, now-a-days, various surrogate traffic safety measures like Post Encroachment Time (PET), and Time to Collision (TTC) are being used to examine the safety of road users. Among them, PET is regarded as the most consistent, and most widely used safety indicator. Therefore, in the present study, PET across different traffic volume levels has been determined. Videography data has been collected from selected median openings located on six-lane divided urban roads. PET values for different traffic volumes, and different category of vehicles have been analysed in detail. Further, the distribution of PET values across the full width of road has also been studied. Concept of critical speed is introduced which is compared with conflicting speed to assess unsafe conflicts and determine a critical PET. Finally, regression models have also been proposed with good levels of accuracy to determine the PET values for various category of vehicles travelling at different conflicting speeds.