Exploring improvisations in road safety in a low-income setting.

Road collision types repeat themselves, especially in low- and middle-income countries (LMICs), where countermeasures are often improvised and implemented with little planning. At the Shahbag intersection in Dhaka, Bangladesh, speed bumps were quickly constructed at the exit of the intersection as an improvised road safety measure following the occurrence of a fatal collision, which eventually contributed to another collision between a truck and a car. The events influencing the improvisation decision, and that action's consequences, have been analysed using the Impromap methodology, a variation of the Accimap approach that focusses specifically on improvisation. The applicability of the Impromap as a systems-based approach to the road safety domain is assessed using the predictions described in Rasmussen's risk management framework, and corresponding countermeasures are proposed. The analysis shows that improvisation in the road safety domain is undesirable irrespective of the economic setting as it is likely to eventually contribute to secondary collisions.Practitioner summary: In this paper, the events influencing the improvisation decision following a road crash, and that action's consequences, have been analysed using the Impromap methodology. The applicability of Impromap as a systems-based approach in road safety domain is assessed using the Rasmussen's risk management framework-based predictions, and corresponding countermeasures are proposed.

Towards safer streets: A framework for unveiling pedestrians' perceived road safety using street view imagery.

Road safety has become a global concern but its impact in low- and middle-income countries is widespread mainly due to lack of appropriate crash database system and under-reporting. In this context, the primary objective of this paper is to provide a scalable framework for unveiling pedestrians' perceived road safety that can also be applied in regions where accessible crash data are limited or near-crashes are left unreported. In the first step of our methodology, a deep learning architecture-based semantic segmentation model (HRNet+OCR) is trained using labeled Google Street View (GSV) images from specific study areas in Dhaka, Bangladesh, which facilitates the identification of both man-made components (such as roads, sidewalks, buildings, and vehicles) and natural elements (including trees and sky). The developed model showed excellent performance in identifying different features in an image by achieving high precision (0.95), recall (0.97), F1-score (0.96), and intersection over union (IoU) (91.86). Secondly, a group of trained raters scored the perceived road safety on an ordinal scale from 0 to 10 (extremely unsafe to extremely safe to walk in terms of road crashes) by assessing the GSV images. Then, several regression models have been used on features extracted from GSV images, and socio-demographic factors (i.e., population density, and relative wealth index) to estimate the perceived road safety, and random forest regression model was found to perform the best. Further, Shapley Additive Explanations (SHAP), a model-agnostic technique has been used for examining feature importance by computing the contribution of each feature to the random forest regression model output. The results show that sidewalk, road, population density, wall, and relative wealth index have higher impact on determining the perceived road safety rating. Additionally, the results of t-tests between the average perceived road safety scores for crash-prone and non crash-prone areas revealed the existence of significant differences. This study also provides perceived road safety rating map on a neighborhood scale, which can be a useful visualization tool for policy-makers and practitioners to identify the road safety deficiencies at specific locations, and formulate appropriate and strategic countermeasures to improve pedestrians' road safety.

Taking a mixed-methods approach to collision investigation: AcciMap, STAMP-CAST and PCM.

Recently, ergonomics and safety researchers have turned their attention towards applying combinations of sociotechnical methods rather than using single methods in isolation. In the current research, a mixed-method approach combining two systems-based methods, Accimaps and the Systems Theoretic Accident Model and Process - Causal Analysis using Systems Theory (STAMP-CAST), and one cognitive approach, the Perceptual Cycle Model (PCM), were employed in analysing a rail-level crossing incident in Bangladesh. Each method was applied individually to investigate the collision, and interventions were proposed corresponding to incident events at different risk management framework levels. The three methods provided different perspectives of the whole picture, together identifying an array of contributory factors. The complementary nature of these methods aided in proposing a comprehensive set of safety recommendations, thereby demonstrating the benefit of a mixed-method approach for collision investigation in low-income settings.

An investigation of urban pedestrian behaviour in Bangladesh using the Perceptual Cycle Model.

In Bangladesh, pedestrians remain the most neglected road user group in terms of research and safety measures, even though they are involved in nearly 50% of all fatal collisions. In the Dhaka metropolitan area, this statistic rises to around 65%. To reduce the recurrence of such collisions, it is necessary to understand the underlying thought processes of pedestrians, and how pedestrians interact with different road users, particularly when crossing the road. This study contributes to knowledge through the analysis of verbal data from 46 pedestrians, framed in terms of the Perceptual Cycle Model, where cognitive processes are described in terms of three categories: schema (mental templates), action (doing things), and world (environmental information). Concurrent verbal reports were provided by participants while they negotiated a busy area of mixed traffic in the centre of Dhaka city. The analysis revealed some of the factors that affected decision-making (for road crossing behaviour) at the different road sections. Many external factors (e.g., street sellers, rubbish blocking the path, lack of shade and poor pavement condition) prevented the pavement from being used and contributed to riskier road crossing behaviour. Some safety implications and related recommendations are presented.

Resolving the differences between system development and system operation using STAMP: a road safety case study in a low-income setting.

Road safety strategies adopted worldwide have made significant progress in reducing road trauma, but have stagnated more recently. The situation in low- and middle-income countries is even worse with no significant decrease in fatality rates. Safety researchers have argued that adopting sociotechnical systems approach is necessary to make significant advancements and improvements. The aim of this study was to develop a control structure model of the Bangladesh road safety system by identifying the actors and organisations involved across the system. Expert stakeholders were identified and interviewed, and relevant information was gathered in order to generate the Systems Theoretic Accident Model and Process control structure model. Throughout the analysis of this model, differences in the control and feedback mechanisms of the system were identified, and road safety intervention recommendations were made. Future research should also predict potential risks within the system and propose proactive and preventative countermeasures. Practitioner summary: In this article, a Systems Theoretic Accident Model and Process control structure model of the Bangladesh road safety system is developed, and the involved actors are identified. Based on interviews and workshops with expert stakeholders, differences in the controls and feedback mechanisms in the system were identified, and road safety intervention recommendations were made. Abbreviations: BUET: Bangladesh University of Engineering and Technology.

Representing two road traffic collisions in one Accimap: highlighting the importance of emergency response and enforcement in a low-income country.

Seemingly erratic pedestrian crossing has become a major source of vehicle-pedestrian collisions on highways in Bangladesh, and across other low- and middle-income countries (LMICs). In this article, we approach the challenge from a sociotechnical systems perspective by using the Accimap method to analyse a pair of time-separated yet interconnected road traffic collisions. The first event involved a truck colliding with a road divider; in the second, fatal incident, a bus hit a university student. The traditional-style investigation conducted immediately after the collision apportioned blame to end users, that is, drivers and pedestrian; however, application of sociotechnical systems thinking revealed the contribution from lack of emergency response and enforcement among many other important factors. Results and recommendations are discussed in terms of reducing the chance and severity of such collisions across LMICs, and in terms of the need to look beyond the end-user, a focus that remains dominant in such settings. Practitioner summary: This paper applies sociotechnical systems thinking to pedestrian safety in Bangladesh by analysing two inter-connected road traffic collisions using a single Accimap. The findings emphasise the importance of implementing road safety interventions that target all system levels, and draw attention to the importance of post-collision response in low-income settings. Abbreviation: BUET: Bangladesh University of Engineering and Technology.