Pedestrian Vehicle Research Articles

Optimisation study on multibody vehicle-front model for pedestrian safety

ABSTRACTEnsuring the safety of pedestrians in a crash with automobiles remains a vehicle design challenge. Multibody simulations were developed in MADYMO to simulate a crash of a parametrised vehicle front model (14 parameters) against three different Netherlands Organization for Applied Scientific Research (TNO) pedestrian models (50th %le M, 5th %le F, 6 Y.O. Child). Threat to a targeted pedestrian population was measured using a weighted injury cost (WIC) measure. A pedestrian friendly vehicle profile was obtained using genetic algorithm-based global optimisation to minimise WIC with geometric constraints on vehicle profile. With known limitations, at least one pedestrian-friendly vehicle shape not resembling any existing vehicle profile was found.

Personalized route planning system based on Wardrop Equilibrium model for pedestrian–vehicle mixed evacuation in campus

Emergency evacuation is an important task while dealing with a sudden accident. Aiming at emergency evacuation in campus, this paper proposed a personalized route planning model for pedestrian–vehicle mixed evacuation. Considering the congestion of pedestrian–vehicle mixed evacuation and the actual factors of students, this model found the optimal user equilibrium close to the system equilibrium. By the help of the Wardrop Equilibrium model, the server calculated the optimized evacuation route planning and guided evacuees by mobile intelligent terminals. Finally this paper applied this model to the evacuation of Wuhan University of Technology. By simulating the process of emergency evacuation, the results showed the feasibility of the algorithm, which proved this model a scientific basis for guiding the real evacuation process.

Traumatic brain injury in pedestrian–vehicle collisions: Convexity and suitability of some functionals used as injury metrics

Background and objectiveAbrupt accelerations or decelerations can cause large strain in brain tissues and, consequently, different forms of Traumatic Brain Injury (TBI). In order to predict the effect of the accelerations on the soft tissues of the brain, many different injury metrics have been proposed (typically, an injury metric is a real valued functional of the accelerations). The objective of this article is to make a formal and empirical comparison, in order to identify general criteria for reasonable injury metrics, and propose a general guideline to avoid ill-proposed injury metrics. MethodsA medium-sized sample of vehicle–pedestrian collisions, from Post Mortem Human Subject (PMHS) tests, is analyzed. A statistical study has been conducted in order to determine the discriminant power of the usual metrics. We use Principal Component Analysis to reduce dimensionality and to check consistency among the different metrics. In addition, this article compares the mathematical properties of some of these functionals, trying to identify the desirable properties that any of those functionals needs to fulfill in order to be useful for optimization. ResultsWe have found a pair-wise consistency of all the currently used metrics (any two injury metrics are always positively related). In addition, we observed that two independent principal factors explain about 72.5% of the observed variance among all collision tests. This is remarkable because it indicates that despite high number of different injury metrics, a reduced number of variables can explain the results of all these metrics. With regard to the formal properties, we found that essentially all injury mechanisms can be accounted by means of scalable, differentiable and convex functionals (we propose to call minimization suitable injury metric any metric having these three formal properties). In addition three useful functionals, usable as injury metrics, are identified on the basis of the empirical comparisons. ConclusionsThe commonly used metrics are highly consistent, but also highly redundant. Formal minimal conditions of a reasonable injury metric has been identified. Future proposals of injury metrics can benefit from the results of this study.

Optimal Design of Light Commercial Vehicle Headlamp for Pedestrian Protection

In this study, the headlamp of a light commercial vehicle was optimized in the way of pedestrian safety. This work aims to prevent harms to pedestrians in the urban crashes. Finite element analysis models of current headlamp and impactors representing pedestrian body forms were created. Static, modal and dynamic/explicit analyses were carried out by using existing and optimized headlamp models. Both models were in the simulations under the same boundary conditions. The results of two conditions were compared with each other. The results showed that connection regions of the headlamp have a major effect on pedestrian safety in pedestrian–vehicle collisions.

Personal injury recovery cost of pedestrian–vehicle collisions in New South Wales, Australia

ABSTRACTBackground: There is a need for routine estimates of injury recovery costs from pedestrian collisions using hospital separation records for economic evaluations.Objective: To estimate the cost of injury recovery following pedestrian–vehicle collisions using the personal injury recover cost (PIRC) equation using key demographic and injury characteristics.Method: An estimation of the costs of on-road pedestrian–vehicle collisions involving individuals who were injured and hospitalized in New South Wales (NSW), Australia, from 2002 to 2011 using the PIRC equation. The PIRC estimates individual injury recovery costs and does not include costs associated with property damage, vehicle repair, or rescue services. Individual recovery costs associated with severe traumatic brain injury (TBI) were estimated. The injured individual's mean, median, and total injury recovery costs are described for key demographic, injury, and crash characteristics.Results: There were 9,781 pedestrians who were injured, costing an estimated total of $2.4 billion in personal injury recovery costs, an annual cost of $243 million. Males had a total injury recovery cost 1.7 times higher than females. The median injury recovery cost decreased with increasing age. TBI ($248,491) and spinal cord and vertebral column injuries ($264,103) had the highest median injury recovery costs for the body region of the most severe injury. TBI accounted for 22.6% of the total injury recovery costs for the most severe injury sustained. Just over one third of pedestrians sustained 4 or more injuries, with a median cost of $243,992, which was 1.6 times higher than the cost for a pedestrian who sustained a single injury ($153,682).Conclusions: Personal injury recovery costs following pedestrian–vehicle collisions where a pedestrian is injured are substantial in NSW. The PIRC equation enables the economic cost burden of road traffic injury to be calculated using hospital separation data. The PIRC enables comprehensive personal injury recovery costs to be estimated and would aid in economic evaluations of preventive strategies in road safety.

Effects of vehicle–pedestrian interaction and speed limit on traffic performance of intersections

Abstract The intersection model consisting of vehicle model, pedestrian model, pedestrian–vehicle interaction model and intersection rules has been presented in this paper. The well-established vehicle and pedestrian movement models in the literature are combined and applied to the intersection system with additional rules. Extensive numerical simulations with different scenarios are carried out. The effects of road speed limit, vehicle arrival rate, pedestrian regularity rate and vehicle rational rate on the intersection performance are quantitatively investigated. Three measures of the traffic performance are studied including transportation efficiency, energy economy and traffic safety. We have found that the energy economy can be achieved with the high transportation efficiency, and that the traffic safety is in conflict with the efficiency. Furthermore, we have found that the pedestrian interference makes the intersection performance worse, resulting in lower transportation efficiency, more energy consumptions and higher safety risk.

A refined and dynamic cellular automaton model for pedestrian–vehicle mixed traffic flow

Mixed traffic flow sharing the “same lane” and having no discipline on road is a common phenomenon in the developing countries. For example, motorized vehicles (m-vehicles) and nonmotorized vehicles (nm-vehicles) may share the m-vehicle lane or nm-vehicle lane and pedestrians may share the nm-vehicle lane. Simulating pedestrian-vehicle mixed traffic flow consisting of three kinds of traffic objects: m-vehicles, nm-vehicles and pedestrians, can be a challenge because there are some erratic drivers or pedestrians who fail to follow the lane disciplines. In the paper, we investigate various moving and interactive behavior associated with mixed traffic flow, such as lateral drift including illegal lane-changing and transverse crossing different lanes, overtaking and forward movement, and propose some new moving and interactive rules for pedestrian–vehicle mixed traffic flow based on a refined and dynamic cellular automaton (CA) model. Simulation results indicate that the proposed model can be used to investigate the traffic flow characteristic in a mixed traffic flow system and corresponding complicated traffic problems, such as, the moving characteristics of different traffic objects, interaction phenomenon between different traffic objects, traffic jam, traffic conflict, etc., which are consistent with the actual mixed traffic system. Therefore, the proposed model provides a solid foundation for the management, planning and evacuation of the mixed traffic flow.

Data-mining techniques for traffic accident modeling and prediction in the United Arab Emirates

ABSTRACTRoad traffic accidents are among the leading causes of death and injury worldwide. In Abu Dhabi, in 2014, 971 traffic accidents were recorded, which contributed to 121 fatalities and 135 severe injuries. Several factors contribute to injury severity, including driver-related factors, road-related factors, and accident-related factors. In this article, data-mining techniques were employed to establish models (classifiers) to predict the injury severity of any new accident with reasonable accuracy, based on 5,973 traffic accident records in Abu Dhabi over a 6-year period from 2008 to 2013. Additionally, the research aimed to establish a set of rules that can be used by the United Arab Emirates (UAE) Traffic Agencies to identify the main factors that contribute to accident severity. Using Waikato Environment for Knowledge Analysis (WEKA) data mining software, four well-known classification algorithms were employed to model the severity of injury. These algorithms included: Decision Tree (DT) (J48), Rule Induction (PART), Naïve Bayes (NB), and Multilayer Perceptron (MLP). The effectiveness of each method in predicting accident severity was evaluated in three different ways. First, the entire data set was used as a training set for the algorithm. Second, accuracy was evaluated using cross-validation with 10-fold. Third, to overcome the problems that resulted from the imbalanced distribution of accident severity in our data set, the data set was resampled to bias the accident severity distribution toward a uniform distribution, and then cross-validation with 10-fold was used again to evaluate the performance. Furthermore, to establish the main contributing factors for road accidents severity, rules generated by the DT J48 algorithm were further explored. The results showed that the overall accuracy of the DT J48 classifier, the PART classifier, and the MLP classifier in predicting the severity of injury resulting from traffic accidents, using 10-fold cross-validation, were similar. The NB classifier exhibited less accuracy. Additionally, the prediction accuracy of the classifiers was enhanced after resampling the training set. The results indicated that the most important factors associated with fatal severity were age, gender, nationality, year of accident, casualty status, and collision type. 18- to 30-year-olds were the most vulnerable age group to traffic accidents. There was a clear trend in accident reduction over the period of the study. Drivers were involved more frequently in traffic accidents than passengers and pedestrians. Male drivers were involved more frequently in traffic accidents than female drivers. UAE, Asian, and Arab nationalities had the highest traffic accident frequency; Gulf and other nationalities had lower traffic accident frequency. The highest number of traffic accidents occurred at right angles. Pedestrian–vehicle type collisions had the next highest number of traffic accidents, followed by rear-end collisions and sideswipe collisions.

Management of intersections with multi-modal high-resolution data

A high-resolution (HR) data system for an intersection collects the location (lane), speed, and turn movement of every vehicle as it enters an intersection, together with the signal phase. Some systems also provide video monitoring; others measure pedestrian and bicycle movements; and some have vehicle to infrastructure (V2I) communication capability. The data are available in real time and archived. Real time data are used to implement signal control. Archived data are used to evaluate intersection, corridor, and network performance. The system operates 24×7. Uses of a HR data system for assessing intersection performance and improving mobility and safety are discussed. Mobility applications include evaluation of intersection performance, and the design of better signal control. Safety applications include estimates of dilemma zones, red-light violations, and pedestrian–vehicle conflicts.

Children at risk: A comparison of child pedestrian traffic collisions in Santiago, Chile, and Seoul, South Korea

ABSTRACTObjective: We examine and compare pedestrian–vehicle collisions and injury outcomes involving school-age children between 5 and 18 years of age in the capital cities of Santiago, Chile, and Seoul, South Korea.Methods: We conduct descriptive analysis of the child pedestrian–vehicle collision (P-VC) data (904 collisions for Santiago and 3,505 for Seoul) reported by the police between 2010 and 2011. We also statistically analyze factors associated with child P-VCs, by both incident severity and age group, using 3 regression models: negative binomial, probit, and spatial lag models.Results: Descriptive statistics suggest that child pedestrians in Seoul have a higher risk of being involved in traffic crashes than their counterparts in Santiago. However, in Seoul a greater proportion of children are unharmed as a result of these incidents, whereas more child pedestrians are killed in Santiago. Younger children in Seoul suffer more injuries from P-VCs than in Santiago. The majority of P-VCs in both cities tend to occur in the afternoon and evening, at intersections in Santiago and at midblock locations in Seoul. Our model results suggest that the resident population of children is positively associated with P-VCs in both cities, and school concentrations apparently increase P-VC risk among older children in Santiago. Bus stops are associated with higher P-VCs in Seoul, and subway stations relate to higher P-VCs among older children in Santiago. Zone-level land use mix was negatively related to child P-VCs in Seoul but not in Santiago. Arterial roads are associated with fewer P-VCs, especially for younger children in both cities. A share of collector roads is associated with increased P-VCs in Seoul but fewer P-VCs in Santiago. Hilliness is related to fewer P-VCs in both cities. Differences in these model results for Santiago and Seoul warrant additional analysis, as do the differences in results across model type (negative binomial versus spatial lag models).Conclusions: To reduce child P-VCs, this study suggests the need to assess subway station and bus stop area conditions in Santiago and Seoul, respectively; areas with high density of schools in Santiago; areas with greater concentrations of children in both cities; and collector roads in Seoul.

Driver types and their behaviors within a high level of pedestrian activity environment

Driver behavior analysis has recently been the focus of research to enhance traffic simulation modeling. Previous research has developed algorithms to model different driver types in both urban networks and freeways, and defined driver behavioral parameters based on pre-categorized driver groups. However, driver behaviors within the more confined, low speed, high pedestrian flow environment (such as CBD of a major city, urban downtown, campus) may be quite different and research concentrating on such locations is limited. The objective of this study is to assess and evaluate the relation between driver type and driver behavior within a relatively restrictive environment with high levels of pedestrian–vehicle interactions and develop suitable schemes to categorize driver types. To meet this objective, the University of Florida campus environment was used as the starting point of analyzing such driver types and behaviors, and a diverse pool of drivers was selected based on age, gender, driving experiences, etc. to participate in surveys and an instrumented vehicle study. The instrumented vehicle was used to collect vehicle trajectory and driver behavior data from the study subjects on the campus at the University of Florida. Two performance measures (namely, driver-desired speed and yield behavior) were applied to categorize driver types. These two categorizations provided consistent results and indicated that either one can be effectively applied in future studies for driver type classifications. Additional comparisons of driver background and personal characteristics obtained from questionnaires further confirmed the driver classification results.

Pedestrian Crossing Treatment Warrants for Midblock Crosswalks Under Mixed Traffic Conditions

Pedestrian crossings are important for accessing the adjacent land use facilities in daily life. Improperly designed crossing facilities cause discomfort to pedestrians and may even jeopardize their safety as well as being a hindrance to the smooth flow of vehicle traffic. These problems exist especially in developing countries such as India, where mixed traffic conditions prevail and road discipline is essentially absent. Thus, the design of efficient crossing facilities considering the flow of both pedestrians and vehicles is of utmost importance in these countries. In this regard, the objective of the current study was to propose warrants for pedestrian crossing facilities in midblock sections under mixed traffic conditions. To achieve this objective, pedestrian–vehicle ( PV2) conflict analysis was carried out at eight different unprotected midblock crosswalks in Mumbai, India. Videographic surveys were conducted and vehicle and pedestrian volumes were extracted, along with pedestrian-crossing characteristics such as crossing difficulty, safety and traffic, and vehicle characteristics. The initial computed PV2-values were adjusted by different factors, and k-means cluster analysis was carried out to determine the threshold PV2-values for selection of a suitable crosswalk facility. The study also highlighted the importance of taking into consideration site characteristics for evaluation of a midblock crosswalk facility. The results of this study are expected to have a wide range of applications in the design of new crosswalk facilities or in the improvement of existing pedestrian crosswalk facilities under mixed traffic conditions.

Evaluation of Pedestrian–Vehicle Conflict Severity at Unprotected Midblock Crosswalks in India

Promoting and creating proper facilities for nonmotorized (pedestrian and bicycle) trips is very important in an urban transportation system to enhance pedestrian safety. Pedestrian–vehicle conflicts on urban roads are increasing, particularly at road crossings, because of the tremendous rate of growth in vehicle traffic in developing countries. Accident statistics clearly indicate the need to improve pedestrian safety and to analyze the pedestrian–vehicle interactions and collisions more deeply. This study analyzed the severity of pedestrian–vehicle conflicts at unprotected midblock crosswalk locations under mixed traffic conditions. The pedestrian–vehicle conflicts were considered on the basis of a pedestrian safety margin, which can be defined as the time difference between the time gap of an approaching vehicle and the pedestrian crossing time. For this purpose, field surveys were conducted at eight unprotected midblock crosswalk locations. Data such as pedestrian demographics and behavioral, traffic, vehicle, and roadway characteristics were considered to analyze the severity of the pedestrian–vehicle conflicts. The study identified the significant contributing factors in such conflicts by using an ordered probit model. The model’s results show that rolling behavior, pedestrian speed change condition, land use type, and vehicle speed have a significant effect on the severity of pedestrian–vehicle conflicts. The findings of this study contribute to developing traffic countermeasures to reduce the severity of pedestrian–vehicle conflict levels in order to improve pedestrian safety at unprotected midblock crosswalk locations under mixed traffic conditions. More studies at various unprotected midblock crosswalk locations would be useful to develop guidelines for redesigning the existing midblock crosswalk facilities by introducing suitable traffic control measures.

Modeling the Frequency of Cyclists’ Red-Light Running Behavior Using Bayesian PG Model and PLN Model

Red-light running behaviors of bicycles at signalized intersection lead to a large number of traffic conflicts and high collision potentials. The primary objective of this study is to model the cyclists’ red-light running frequency within the framework of Bayesian statistics. Data was collected at twenty-five approaches at seventeen signalized intersections. The Poisson-gamma (PG) and Poisson-lognormal (PLN) model were developed and compared. The models were validated using Bayesianpvalues based on posterior predictive checking indicators. It was found that the two models have a good fit of the observed cyclists’ red-light running frequency. Furthermore, the PLN model outperformed the PG model. The model estimated results showed that the amount of cyclists’ red-light running is significantly influenced by bicycle flow, conflict traffic flow, pedestrian signal type, vehicle speed, and e-bike rate. The validation result demonstrated the reliability of the PLN model. The research results can help transportation professionals to predict the expected amount of the cyclists’ red-light running and develop effective guidelines or policies to reduce red-light running frequency of bicycles at signalized intersections.

Are electric self-balancing scooters safe in vehicle crash accidents?

With the pressing demand of environmentally friendly personal transportation vehicles, mobility scooters become more and more popular for the short-distance transportation. Similar to pedestrians and bicyclists, scooter riders are vulnerable road users and are expected to receive severe injuries during traffic accidents. In this research, a MADYMO model of vehicle–scooter crash scenarios is numerically set up. The model of the vehicle with the scenario is validated in pedestrian–vehicle accident investigation with previous literatures in terms of throwing distance and HIC15 value. HIC15 values gained at systematic parametric studies. Injury information from various vehicle crashing speeds (i.e. from 10m/s to 24m/s), angles (i.e. from 0 to 360°), scooter's speeds (i.e. from 0m/s to 4m/s), contact positions (i.e. left, middle and right bumper positions) are extracted, analyzed and then compared with those from widely studied pedestrian–vehicle and bicycle–vehicle accidents. Results show that the ESS provides better impact protection for the riders. Riding ESS would not increase the risk higher than walking at the same impact conditions in terms of head injury. The responsible reasons should be the smaller friction coefficient between the wheel-road than the heel-road interactions, different body gestures leading to different contact positions, forces and timing. Results may shed lights upon the future research of mobility scooter safety analysis and also the safety design guidance for the scooters.

Optimisation study on multibody vehicle-front model for pedestrian safety

ABSTRACTEnsuring the safety of pedestrians in a crash with automobiles remains a vehicle design challenge. Multibody simulations were developed in MADYMO to simulate a crash of a parametrised vehicle front model (14 parameters) against three different Netherlands Organization for Applied Scientific Research (TNO) pedestrian models (50th %le M, 5th %le F, 6 Y.O. Child). Threat to a targeted pedestrian population was measured using a weighted injury cost (WIC) measure. A pedestrian friendly vehicle profile was obtained using genetic algorithm-based global optimisation to minimise WIC with geometric constraints on vehicle profile. With known limitations, at least one pedestrian-friendly vehicle shape not resembling any existing vehicle profile was found.

An efficient parallel sampling technique for Multivariate Poisson-Lognormal model: Analysis with two crash count datasets

This study investigates the Multivariate Poisson-lognormal (MVPLN) model that jointly models crash frequency and severity accounting for correlations. The ordinary univariate count models analyze crashes of different severity level separately ignoring the correlations among severity levels. The MVPLN model is capable to incorporate the general correlation structure and also takes account of the overdispersion in the data that leads to a superior data fitting. However, the traditional estimation approach for MVPLN model is computationally expensive, which often limits the use of MVPLN model in practice. In this work, a parallel sampling scheme is introduced to improve the original Markov Chain Monte Carlo (MCMC) estimation approach of the MVPLN model, which significantly reduces the model estimation time. Two MVPLN models are developed using the pedestrian–vehicle crash data collected in New York City from 2002 to 2006, and the highway-injury data from Washington State (5-year data from 1990 to 1994) The Deviance Information Criteria (DIC) is used to evaluate the model fitting. The estimation results show that the MVPLN models provide a superior fit over univariate Poisson-lognormal (PLN), univariate Poisson, and Negative Binomial models. Further, the correlations among the latent effects of different severity levels are found significant in both datasets,that justifies the importance of jointly modeling crash frequency and severity accounting for correlations.

A study on crossing speed profiles of pedestrians at signalized crosswalks

Pedestrian–vehicle conflicts are one of the most important safety concerns especially at intersections. Of total traffic fatalities, 30% and 36% are pedestrians in Qatar and in Japan, respectively (National Police Agency in Japan, 2015). Although pedestrians at signalized intersections are given priority during the green phase, turning vehicles in conflict often do not give the right of way to pedestrians but tend to compete for it. Furthermore, long crosswalks, short green times, and other reasons may cause pedestrians to rush or suddenly change their speed without paying attention to the surrounding conditions (Iryo-Asano et al. 2014). The sudden changes in pedestrian behavior while crossing cannot be predicted by the driver, which can cause severe conflicts. Therefore, the possible behavioral changes of pedestrians should be studied so that surrogate safety measures such as post-encroachment time can be quantitatively estimated to provide a reliable assessment of pedestrian–vehicle conflicts and their severities. Continuous pedestrian speed profiles were analyzed at signalized crosswalks considering the impact of crosswalk geometry and signal timing. Five signalized crosswalks at three intersections in Nagoya City were videotaped and individual pedestrian maneuvers were extracted by image processing. A stepwise speed function is proposed to identify significant sudden changes in individual pedestrian speed profiles. The locations and timings of these sudden speed change events were analyzed, and the influencing factors were statistically evaluated. Empirical analysis showed that sudden acceleration events were observed at the entrance points to the pedestrian–vehicle conflict area, which highlights the significance of these events to pedestrian–vehicle conflict analysis. More than a quarter of all acceleration events occurred just after the onset of the pedestrian flashing green signal indication. Furthermore, it is concluded that long crosswalks have higher percentage of speed change occurrence and as a result higher risk of crashes. In this regard, the application of two-stage pedestrian crossing is a potential solution to reduce crosswalk length and the possibility of having unpredicted pedestrian behavioral changes. In general, the results implied that pedestrian entering speed to crosswalk, necessary speed to finish crossing before the onset of the pedestrian red signal indication, and crosswalk length have a significant impact on pedestrian speed change choices.

Testing Methodology of Vehicle Pedestrian Notification Systems

Transport Canada’s ecoTECHNOLOGY for Vehicles Program tests and evaluates the safety and environmental performance of advanced vehicle technologies. One area of investigation, in collaboration with Transport Canada's Motor Vehicle Safety Standards and Regulations Group, is audible alert systems for electric vehicles. BEVs and HEVs can be significantly quieter than conventional vehicles at low speeds. The inclusion of sound alert systems that emit a detectable minimum sound is currently being studied as one option to enhance pedestrian safety. This paper will provide an overview of TC’s testing to measure/assess the noise emissions from BEVs, HEVs and conventional vehicles, and various manufacturers’ noise emissions systems for HEVs / BEVs.

A hospital based surveillance system to assess the burden of trauma in KwaZulu-Natal Province South Africa.

In response to the ongoing excessive burden of trauma in South Africa the Data Management and Epidemiology Units of the Department of Health in conjunction with a group of trauma specialists developed a number of trauma data variables for inclusion on the routine District Health Information System (DHIS). The aim of this study is to describe the process followed and review the 2012-2014 data. The variables collected included: total patient numbers assessed in the emergency room with a diagnosis of trauma; the mechanisms of trauma (blunt assault, motor vehicle accident, pedestrian vehicle accident, stab, gunshot wound, other); any trauma patient admitted to a health facility ward/ICU for longer than 12h; and whether the patient required transfer to a higher centre of care. All trauma deaths in hospital were recorded. The severity of trauma was measured using the Emergency Medical Services (EMS) classification of blue code (dead), red code (stretcher case with deranged physiology), yellow code (stretcher case with normal physiology) and green code (able to walk with normal physiology. The DHIS trauma data from April 2012 to March 2014 was reviewed. There were 197,219 emergency room visits for trauma in KZN in the 2013/2014 financial year. This constitutes 27.0% of all emergency room visits. The ratio of intentional to non-intentional injury is 45:55. There were 18,716 admissions to public sector hospitals for trauma in KZN in the 2013/2014 financial year. This constitutes 2.4% of all admissions in the province. There were 1045 inpatient deaths due to trauma in the same period, constituting 2.5% of all inpatient deaths. The overall rate of trauma in KZN was 17 per 1000 population. The adapted DHIS has successfully collected essential data that quantify the hospital burden of trauma in KZN province. This has provided the most complete overview of the burden of trauma in the Province. These trauma indicators should remain a permanent part of the DHIS to allow planners to track the trauma epidemic and to institute informed management strategies.