Conflict analysis for prediction of fatal crash locations in mixed traffic streams

Advances and applications of computer vision techniques in vehicle trajectory generation and surrogate traffic safety indicators

The application of Computer Vision (CV) techniques massively stimulates microscopic traffic safety analysis from the perspective of traffic conflicts and near misses, which is usually measured using Surrogate Safety Measures (SSM). However, as video processing and traffic safety modeling are two separate research domains and few research have focused on systematically bridging the gap between them, it is necessary to provide transportation researchers and practitioners with corresponding guidance. With this aim in mind, this paper focuses on reviewing the applications of CV techniques in traffic safety modeling using SSM and suggesting the best way forward. The CV algorithms that are used for vehicle detection and tracking from early approaches to the state-of-the-art models are summarized at a high level. Then, the video pre-processing and post-processing techniques for vehicle trajectory extraction are introduced. A detailed review of SSMs for vehicle trajectory data along with their application on traffic safety analysis is presented. Finally, practical issues in traffic video processing and SSM-based safety analysis are discussed, and the available or potential solutions are provided. This review is expected to assist transportation researchers and engineers with the selection of suitable CV techniques for video processing, and the usage of SSMs for various traffic safety research objectives.

Determining an Improved Traffic Conflict Indicator for Highway Safety Estimation Based on Vehicle Trajectory Data

Currently, several traffic conflict indicators are used as surrogate safety measures. Each indicator has its own advantages, limitations, and suitability. There are only a few studies focusing on fixed object conflicts of highway safety estimation using traffic conflict technique. This study investigated which conflict indicator was more suitable for traffic safety estimation based on conflict-accident Pearson correlation analysis. First, a high-altitude unmanned aerial vehicle was used to collect multiple continuous high-precision videos of the Jinan-Qingdao highway. The vehicle trajectory data outputted from recognition of the videos were used to acquire conflict data following the procedure for each conflict indicator. Then, an improved indicator Ti was proposed based on the advantages and limitations of the conventional indicators. This indicator contained definitions and calculation for three types of traffic conflicts (rear-end, lane change and with fixed object). Then the conflict-accident correlation analysis of TTC (Time to Collision)/PET (Post Encroachment Time)/DRAC (Deceleration Rate to Avoid Crash)/Ti indicators were carried out. The results show that the average value of the correlation coefficient for each indicator with different thresholds are 0.670 for TTC, 0.669 for PET, and 0.710 for DRAC, and 0.771 for Ti, which Ti indicator is obviously higher than the other three conventional indicators. The findings of this study suggest TTC often fails to identify lane change conflicts, PET indicator easily misjudges some rear-end conflict when the speed of the following vehicle is slower than the leading vehicle, and PET is less informative than other indicators. At the same time, these conventional indicators do not consider the vehicle-fixed objects conflicts. The improved Ti can overcome these shortcomings; thus, Ti has the highest correlation. More data are needed to verify and support the study.

Modelling of road traffic fatalities in India

Passenger modes in India include walking, cycling, buses, trains, intermediate public transport modes (IPT) such as three-wheeled auto rickshaws or tuk-tuks, motorised two-wheelers (2W) as well as cars. However, epidemiological studies of traffic crashes in India have been limited in their approach to account for the exposure of these road users. In 2011, for the first time, census in India reported travel distance and mode of travel for workers. A Poisson-lognormal mixture regression model is developed at the state level to explore the relationship of road deaths of all the road users with commute travel distance by different on-road modes. The model controlled for diesel consumption (proxy for freight traffic), length of national highways, proportion of population in urban areas, and built-up population density. The results show that walking, cycling and, interestingly, IPT are associated with lower risk of road deaths, while 2W, car and bus are associated with higher risk. Promotion of IPT has twofold benefits of increasing safety as well as providing a sustainable mode of transport. The mode shift scenarios show that, for similar mode shift across the states, the resulting trends in road deaths are highly dependent on the baseline mode shares. The most worrying trend is the steep growth of death burden resulting from mode shift of walking and cycling to 2W. While the paper illustrates a limited set of mode shift scenarios involving two modes at a time, the model can be applied to assess safety impacts resulting from a more complex set of scenarios.

A bibliometric analysis of the published road traffic injuries research in India, post-1990

BACKGROUND

Globally, road traffic injuries are the leading cause of death among those aged 15-29 years. However, road traffic injury research has not received adequate attention from the scientific community in low- and middle-income countries, including India. The present study aims to provide a bibliometric overview of research assessing road traffic injuries in India.

METHODS

We used Scopus to extract relevant research in road traffic injuries published from 1991 to 2017. This study presented the key bibliometric indicators such as trends of annual publications and citations, top 10 authors, journals, institutions and highly cited articles, citation analysis of articles, co-occurrence of keywords, etc. Analysis was performed using Scopus, Microsoft Excel, and VOS-viewer.

RESULTS

A total of 242 articles were retrieved with an h-index of 18, excluding self-citations. A steadfast growth of publications was documented in last decade, especially after the year 2010. The h-index of the top 10 authors, institutions, journals and highly cited articles did not surpass single digits. A network visualisation map showed that 'traffic accident', 'male', 'adolescent' and 'child' were the most commonly encountered key terms. The prominent authors were Gururaj G, Dandona R, and Hyder AA, whereas the top journals were the Indian Journal of Forensic Medicine and Toxicology, Medico Legal Update, and the International Journal of Applied Engineering Research and top institutions were the All India Institute of Medical Sciences, New Delhi, the Indian Institute of Technology, Delhi, and the Administrative Staff College of India.

CONCLUSION

In India, road traffic injuries research is inadequate in quantity and quality, warranting greater attention from researchers and policy planners to address the burden of road traffic injuries.

Traffic evacuation time under nonhomogeneous conditions

During many manmade and natural crises such as terrorist threats, floods, hazardous chemical and gas leaks, emergency personnel need to estimate the time in which people can evacuate from the affected urban area. Knowing an estimated evacuation time for a given crisis, emergency personnel can plan and prepare accordingly with the understanding that the actual evacuation time will take longer. Given the urban area to be evacuated, street widths exiting the area's perimeter, the area's population density, average vehicle occupancy, transport mode share and crawl speed, an estimation of traffic evacuation time can be derived. Peak-hour traffic data collected at three, midblock, Mumbai sites of varying geometric features and traffic composition were used in calibrating a model that estimates peak-hour traffic flow rates. Model validation revealed a correlation coefficient of +0.98 between observed and predicted peak-hour flow rates. A methodology is developed that estimates traffic evacuation time using the model.

Individual driver risk assessment using naturalistic driving data

Driving risk varies substantially among drivers. Identifying and predicting high-risk drivers will greatly benefit the development of proactive driver education programs and safety countermeasures. The objective of this study is twofold: (1) to identify factors associated with individual driver risk and (2) predict high-risk drivers using demographic, personality, and driving characteristic data. The 100-Car Naturalistic Driving Study was used for methodology development and application. A negative binomial regression model was adopted to identify significant risk factors. The results indicated that the driver's age, personality, and critical incident rate had significant impacts on crash and near-crash risk. For the second objective, drivers were classified into three risk groups based on crash and near-crash rate using a K-mean cluster method. The cluster analysis identified approximately 6% of drivers as high-risk drivers, with average crash and near-crash (CNC) rate of 3.95 per 1000miles traveled, 12% of drivers as moderate-risk drivers (average CNC rate=1.75), and 84% of drivers as low-risk drivers (average CNC rate=0.39). Two logistic models were developed to predict the high- and moderate-risk drivers. Both models showed high predictive powers with area under the curve values of 0.938 and 0.930 for the receiver operating characteristic curves. This study concluded that crash and near-crash risk for individual drivers is associated with critical incident rate, demographic, and personality characteristics. Furthermore, the critical incident rate is an effective predictor for high-risk drivers.

Methodological proposal for implementing an intervention to prevent pedestrian injuries, a multidisciplinary approach: the case of Cuernavaca, Morelos, Mexico

OBJECTIVE

To describe the process for implementing an intervention to prevent pedestrian injuries in Cuernavaca, Mexico, using a multidisciplinary and evidence-based approach.

METHODOLOGY

This study included two phases with several stages. The first was an overall assessment of pedestrian mortality in Cuernavaca that included a comparison of pedestrian mortality between Cuernavaca and the rest of Morelos State (1998-2007), an analysis and geocoding of pedestrian injuries (2008-2009), and a description of techniques for selecting and analysing clustered events using road audits. The second phase focused on selecting an intervention through a review of the literature seeking the 'best evidence' adaptable to the local context and a methodological evaluation for implementation including techniques for cluster randomisation and for the evaluation of possible effects of the intervention.

RESULTS

Between 2008 and 2009, in Cuernavaca there were 620 pedestrian injury events: 59.4% were men, the mean age was 36.3 years, 70% occurred during daylight hours, 55% had mild severity and there were no differences by sex (p>0.05). We generated evidence, that when combined with the results from a systematic search of the literature, provided sufficient information for the implementation of a pedestrian injury prevention intervention.

CONCLUSIONS

A combination of strategies and disciplines makes it possible to comprehensively address this public health problem, allowing interventions to strengthen aspects of pedestrian safety while accounting for characteristics of the local context; the promotion of local measures, of low cost and high impact, with modifications to the road infrastructure, are more effective in addressing pedestrian vulnerabilities.

Relationship between road traffic accidents and conflicts recorded by drive recorders

OBJECTIVE

Road traffic conflicts can be used to estimate the probability of accident occurrence, assess road safety, or evaluate road safety programs if the relationship between road traffic accidents and conflicts is known. To this end, we propose a model for the relationship between road traffic accidents and conflicts recorded by drive recorders (DRs).

METHODS

DRs were installed in 50 cars in Beijing to collect records of traffic conflicts. Data containing 1366 conflicts were collected in 193 days. The hourly distributions of conflicts and accidents were used to model the relationship between accidents and conflicts. To eliminate time series and base number effects, we defined and used 2 parameters: average annual number of accidents per 10,000 vehicles per hour and average number of conflicts per 10,000 vehicles per hour. A model was developed to describe the relationship between the two parameters.

RESULTS

If A(i) = average annual number of accidents per 10,000 vehicles per hour at hour i, and E(i) = average number of conflicts per 10,000 vehicles per hour at hour i, the relationship can be expressed as [Formula in text] (α>0, β>0). The average number of traffic accidents increases as the number of conflicts rises, but the rate of increase decelerates as the number of conflicts increases further.

CONCLUSIONS

The proposed model can describe the relationship between road traffic accidents and conflicts in a simple manner. According to our analysis, the model fits the present data.

Traffic injury deaths in West Azarbaijan province of Iran: a cross-sectional interview-based study on victims' characteristics and pre-hospital care

This study highlights the socio-demographics and death circumstances of victims of fatal road traffic injuries (RTIs) in one Iranian province. A representative sample of cases was selected from a national register and interviews were conducted with the victims' family members. The study shows that there is a strong association between victim attributes (e.g. sex, age, occupation, education or marital status) and category of road-user. Although men are over-represented in all categories, women die above all as car passengers or pedestrians. Deaths of vulnerable road-users are more frequent among the younger and older age groups. Two-thirds of all deaths occurred before arrival at the hospital and 11% of the victims received ambulance transport. The patterns of fatal RTIs observed in the province differ somewhat from the rest of Iran and other low- and middle-income countries. Not only pre- but also post-crash counter-measures could help save lives in the region.

The effect of conformity tendency on pedestrians' road-crossing intentions in China: an application of the theory of planned behavior

This paper presents a survey investigating the effects of age, gender and conformity tendency on Chinese pedestrians' intention to cross the road in potentially dangerous situations. A sample of 426 respondents completed a demographic questionnaire, a scale measuring their tendency towards social conformity, and a questionnaire based on the theory of planned behavior (TPB). This questionnaire measured people's intentions to cross the road in two different road crossing situations, their attitude towards the behavior, subjective norms, perceived behavioral control, anticipated affect, moral norms, and perceived risk. The two scenarios depicted (i) a situation where the crossing was consistent with other pedestrians' behavior (Conformity scenario) and (ii) a situation where the road crossing was inconsistent with other pedestrians (Non-Conformity scenario). Pedestrians reported greater likelihood in crossing the road when other pedestrians were crossing the road. People who showed greater tendencies towards social conformity also had stronger road crossing intentions than low conformity people for both scenarios. The predictive model explained 36% and 48% of the variance in the Non-Conformity and Conformity scenarios, respectively. Attitude, subjective norm, perceived behavioral control, and perceived risk emerged as the common predictors for both situations. The results have a number of theoretical and practical implications. In particular, interventions should focus on perceptions of risk that inform road users that crossing with other pedestrians against the signal is also unsafe and prohibited, and may lead to negative outcomes.

A risk-based method for modeling traffic fatalities

We describe a risk-based analytical framework for estimating traffic fatalities that combines the probability of a crash and the probability of fatality in the event of a crash. As an illustrative application, we use the methodology to explore the role of vehicle mix and vehicle prevalence on long-run fatality trends for a range of transportation growth scenarios that may be relevant to developing societies. We assume crash rates between different road users are proportional to their roadway use and estimate case fatality ratios (CFRs) for the different vehicle-vehicle and vehicle-pedestrian combinations. We find that in the absence of road safety interventions, the historical trend of initially rising and then falling fatalities observed in industrialized nations occurred only if motorization was through car ownership. In all other cases studied (scenarios dominated by scooter use, bus use, and mixed use), traffic fatalities rose monotonically. Fatalities per vehicle had a falling trend similar to that observed in historical data from industrialized nations. Regional adaptations of the model validated with local data can be used to evaluate the impacts of transportation planning and safety interventions, such as helmets, seat belts, and enforcement of traffic laws, on traffic fatalities.

Road traffic injuries in India: a review of the literature

AIMS

India is the largest country in the South Asian region with all the problems faced by rapidly developing nations, especially increasing motorization. In spite of such developments, there are limited data in the literature addressing the problem of road traffic injuries. This article is an attempt to estimate the magnitude of the problem through published literature.

METHODS

This article is a systematic review of the literature on road traffic injuries in India, conducted using three electronic databases and hand-searching of the selected articles. Final analyses were conducted with 22 studies.

RESULTS

Road traffic injuries are a significant burden on the health care system in India. The most commonly affected group is young males. Pedestrians constitute a large majority of the victims and there is high early mortality in most cases.

CONCLUSIONS

There is lack of population-based data on road traffic injuries in India and there is large heterogeneity in the published data. This is an important research agenda for the country. Immediate steps are required to curb this problem to limit the loss of life and resources.

Road safety in less-motorized environments: future concerns

In the last three decades, the incidence of traffic crash fatalities and injuries has been reduced significantly in the high-income countries but not in the low- and middle-income countries. The traffic patterns in the former are not only different but are also less complex than those in the latter. Traffic in low-income countries comprises a much higher share of vulnerable road users and so vehicles, roads and the environment have to be designed for their safety. Solutions for such problems are not readily available and very innovative work needs to be done around the world to arrive at new policies and designs. In addition to crashworthiness of vehicles, transportation planning, exposure control, intelligent separation of non-motorized traffic on major roads, and traffic calming are likely to play a much more important role.