Sustainable Road Safety Research Articles

The application of the Fuzzy Analytical Hierarchy Process (FAHP) as a multi-criteria analysis tool for road risk assessment: Algeria as a case study

In response to the escalating road safety challenges and the persistent increase in traffic accidents, it is imperative to adopt an integrated approach to address this multifaceted issue effectively. The main objective of this research is to classify or identify high-risk areas by studying the impact of the most significant factors contributing to road accidents. The methodology is based on a hierarchical model of three levels, including the essential factors that increase road risk. Subsequently, a fuzzy hierarchy process (FAHP) is conducted using a fuzzy scale to evaluate and analyse the most influential factors to determine the risk level for each road segment. This approach has been applied to the motorway in Algeria, specifically in the Mascara region, where the road was divided into 83 sections of 100 metres. The study's results revealed that factors related to infrastructure and those associated with drivers had the most significant impact, while environmental factors had less influence on road safety. The studied area exhibited risk levels ranging from moderate to low. The current state analysis of the roads (open to traffic) allows for the evaluation of factors that heighten road risks, this comprehensive evaluation is instrumental in formulating sustainable road safety strategies to mitigate future traffic accidents.

Capacity building for road safety in LMICs: the need for a sustainable local knowledge and research infrastructure

Road crashes continue to be a major cause of death and serious injury for low- and middle-income countries (LMICs). At the global level, 90% of traffic fatalities occur in these countries with a dramatic daily amount of 3 260 road deaths, many of whom are children. The first UN Decade of Action for Road Safety 2011–2020 was designed to develop a massive movement towards a decrease of these numbers. This resulted in many initiatives to introduce the safe system approach in LMICs, i.e. to implement road safety management, make roads, road users, and vehicles safer, and improve post-crash health care. International organisations together with NGOs and universities prepared road safety guides and manuals, gave courses and webinars, introduced auditing and inspection systems, with the overall intention to build capacity in LMICs. Together these actions contributed to a variety of road safety developments in LMICs but the overall results were still modest. At the third Global Ministerial Conference on Road Safety in Stockholm, 2020, and in the Global Status report by the World Health Organization, 2023, the results of all efforts were presented and evaluated. Many countries made progress through road safety management and better legislation addressing risk factors such as speeding, drinking and driving, failing to use seatbelts, and poor infrastructure design. However, the reduction in road deaths strongly lagged behind the original goals. Continued implementation of programs and development of new approaches are needed to make a breakthrough, and to reach the goals of the 2nd Decade of Action, i.e. a 50% reduction in fatalities by 2030, and the same percentage reduction in injuries. The present position paper argues that despite the enormous amount of road safety information, which has been and is ‘sent’ to LMICs, and despite the quality and robustness of international organisations behind these programs, there is a shortfall in the scale of the knowledge and research infrastructure currently existing in LMICs, which is needed to ‘receive and transfer’ this knowledge. In order to develop evidence-based policy, LMICs need research programs that are able to transfer safe system principles to the local context and culture. Several literature overviews illustrate the lack of such research in LMICs, i.e. the limited number of programs at local universities and research institutes. Although recently initiatives have been taken in some countries, the implementation of such programs is urgently needed. Based on this observation we call on international organisations to establish a special program for the development of a sustainable road safety knowledge and research infrastructure in LMICs. Such structural local capacity is a prerequisite to translate international road safety knowledge into local guidelines and to develop an evidence-based road safety policy. Most importantly, this local infrastructure will give countries a national knowledge bank, thus providing them with an urgently needed sustainable road safety memory.

Blockchain-enabled transparent traffic enforcement for sustainable road safety in cities

With the progress of the times, cars have become an important means of transportation in our lives. However, with new cars of all kinds, road safety issues still cannot be effectively improved. While countries have responded by enforcing traffic laws and using electronic technology to enhance enforcement, challenges still need to be addressed, including blurred images and misjudgments by police agencies, and even exploiting loopholes in traffic enforcement frameworks to evade consequences through bribery or connections. exacerbating an accident and leaving victims and families in the lurch of the aftermath. To solve this problem, we proposed a data traceability law enforcement system based on blockchain and InterPlanetary File System (IPFS). The system ensures rapid traceability and protects law enforcement data from external attacks. The goal of leveraging blockchain’s decentralized nature and smart contracts is to instill accountability and fairness in road safety measures, mitigate the effects of corruption, and pave the way for a safer and more just transportation environment. Our experimental results show that under our stress test of 50 transactions per second, the throughput can be as high as 300 and the maximum delay can reach 2.01s, which is enough to experimentally prove that our system is feasible. Our approach is designed to solve the data corruption problem caused by the centralized server being paralyzed. It applies to all technology enforcement, with high flexibility and scalability for all participants to join or set privileges. we also provide an automated traffic law enforcement system in a smart city. To make the data storage more secure and fair, and not easily damaged by malicious people or tampered with by intentional attackers. This brings a breakthrough to the country’s program security.

Inclusive assessment of road traffic accident associated with design-construction disparities and contemplating its relative impact for sustainable road safety

Purpose Road accident is a major threat to sustainable road safety, causing immense suffering and posing an increasingly serious global challenge, especially in developing countries. It is the leading cause of death, injuries and property damage. While vehicle driver-related factors play a significant role in accidents, poorly designed and constructed roads are also a growing factor. As result, this study aims to assess traffic accident problems associated with design-construction complications on Arba Minch-Jinka Road, Ethiopia. Design/methodology/approach From 2013 to 2021, a large amount of traffic accident data was gathered, and through actual roadway surveys at potential locations along the road, the data was associated with design-construction parameters. The analysis was done by adopting descriptive statistics incorporating comparative hypotheses, in which the individual and combined effects of design-construction issues were identified. Results revealed, on average, 76% of total coincided accidents along the study road were associated with design-construction issues. Exclusively, causing factors, i.e. roadway, driver, vehicle, pedestrian problems and environmental, contributed 7.65%, 77.78%, 6.17%, 6.05% and 2.35% traffic accidents, respectively. Findings Detailed and time-consuming data collection, investigations, analysis and assessments were used in the research to discover a strong association between road design-construction problems and traffic accidents. As a result, 42 black spot sections were identified, and 7.65% is exclusively caused from design-construction problems. Curved road sections led the surge by 42% from selected design-construction variable, whereas the remaining 58% was shared among four parameters. According to relative analysis, design-construction issues caused a 58.17%, 12.14%, 32.36% and 29.93% increase in accidents in combination with driver, vehicle, pedestrian and environmental factors, respectively. This is in an average of 33.15% escalated problem in a combination that raises questions about the sustainability of road safety. Originality/value It is essential to use scientific methodologies to evaluate traffic accidents and associated design-build discrepancies in developing nations like Ethiopia if we are to achieve sustainable road safety. The fundamental importance and value of this study is that it promotes accountability to the road design and construction, which are not frequently thought of as influencing factors in traffic accidents. This paper is original, and all references have been correctly mentioned, to the best of the author’s knowledge.

Enhancing Road Crack Localization for Sustainable Road Safety Using HCTNet

Road crack detection is crucial for maintaining and inspecting civil infrastructure, as cracks can pose a potential risk for sustainable road safety. Traditional methods for pavement crack detection are labour-intensive and time-consuming. In recent years, computer vision approaches have shown encouraging results in automating crack localization. However, the classical convolutional neural network (CNN)-based approach lacks global attention to the spatial features. To improve the crack localization in the road, we designed a vision transformer (ViT) and convolutional neural networks (CNNs)-based encoder and decoder. In addition, a gated-attention module in the decoder is designed to focus on the upsampling process. Furthermore, we proposed a hybrid loss function using binary cross-entropy and Dice loss to evaluate the model’s effectiveness. Our method achieved a recall, F1-score, and IoU of 98.54%, 98.07%, and 98.72% and 98.27%, 98.69%, and 98.76% on the Crack500 and Crack datasets, respectively. Meanwhile, on the proposed dataset, these figures were 96.89%, 97.20%, and 97.36%.

Perceptions underlying road safety behaviours of drivers in urban Ghana – a health-belief and planned behaviour perspective

PurposeThe study aims to examine social-psychological beliefs and personality traits and their linkage with driver predispositions and road safety behaviour grounded on notions derived from an integration of the health belief model (HBM) and the theory of planned behaviour (TPB) in social marketing.Design/methodology/approachThe study used a cross-sectional survey to gather data from 587 licenced drivers in 3 major urban settlements in Ghana. The theoretical model was tested by using covariance-based structural equation modelling.FindingsThe study finds that the effects of perceived benefits, perceived behavioural control, social norms and cues to action on road safety behaviour are direct; the effects of perceived susceptibility, severity and barriers on road safety behaviour are fully mediated by driver attitude towards safe driving. Some of these effects were moderated by conscientiousness and neuroticism.Practical implicationsThe findings offer empirical grounds for the development of evidence-based social marketing interventions that leverage efficacy-centred messages, social influence through community-based approaches, informational cues with consistent education and are tailored to the personality traits of drivers with the aim of inducing wilful on-road safety behaviour towards achieving sustainable road safety culture.Originality/valueThis study extends the integrative applicability of the HBM and TPB in understanding road safety behaviour and establishes attitude as a vital facilitator, and personality traits as moderators of the belief-preventive behaviour linkage within a developing country context. It contributes towards the use of theory-based outcomes to enhance the efficacy of social marketing road safety campaigns.

Towards Sustainable Safe Driving: A Multimodal Fusion Method for Risk Level Recognition in Distracted Driving Status

Precise driving status recognition is a prerequisite for human–vehicle collaborative driving systems towards sustainable road safety. In this study, a simulated driving platform was built to capture multimodal information simultaneously, including vision-modal data representing driver behaviour and sensor-modal data representing vehicle motion. Multisource data are used to quantify the risk of distracted driving status from four levels, safe driving, slight risk, moderate risk, and severe risk, rather than detecting action categories. A multimodal fusion method called vision-sensor fusion transformer (V-SFT) was proposed to incorporate the vision-modal of driver behaviour and sensor-modal data of vehicle motion. Feature concatenation was employed to aggregate representations of different modalities. Then, successive internal interactions were performed to consider the spatiotemporal dependency. Finally, the representations were clipped and mapped into four risk level label spaces. The proposed approach was evaluated under different modality inputs on the collected datasets and compared with some baseline methods. The results showed that V-SFT achieved the best performance with an recognition accuracy of 92.0%. It also indicates that fusing multimodal information effectively improves driving status understanding, and V-SFT extensibility is conducive to integrating more modal data.

A Review of Surrogate Safety Measures Uses in Historical Crash Investigations

Historical road crash data are the main indicator for measuring road safety outcomes. Over the past few decades, significant efforts have been made in obtaining and exploiting Surrogate Safety Measures (SSMs). SSMs have the potential to provide excellent sustainable road safety indicators and proxy measurements which can complement traditional historical crash analyses or even substitute them. By using SSMs, crash data collection demands can be bypassed and areas can be investigated before crashes occur. Due to such advantages, the objective of the present research is to provide a review of the scientific literature regarding studies exploiting SSMs for historical crash record investigations. Specifically, 34 studies were examined, providing insights on the different types of SSMs collected under real road environment conditions, the way they are collected, their connection with specific road crash types, and the type of the developed statistical models are examined and discussed. Particular focus is also placed on the temporal dimension of the collection period of both SSMs and road crashes. Finally, the overall trends deriving from the reviewed studies are summarized and future research directions are provided.

A sustainable road safety approach for pedestrians in new cities of Egypt

Over the last decade, Egypt’s growing population and dynamic economy have resulted in a need for greater infrastructure development; consequently, the risk of pedestrians crossing at grade has increased tremendously. For reducing fatalities caused by the conflict between pedestrians crossing at grade and vehicles, pedestrian bridges have been established. Noting that these bridges which are dedicated to human safety are highly expensive, therefore without the fulfilment of conditions of safety, convenience and ease of accessibility they might be a wasted investment. In this respect, site visits and a SWOT analysis were conducted on three pedestrian bridges in New Cairo for monitoring and evaluating the impact of these interventions. The assessment of strengths, weaknesses, opportunities and threats of these projects formed a base for upgrading and the development of new projects. Although, there are some attempts for using escalators for encouraging usability of pedestrian bridges, the research propose a national project using small solar PV systems for the operation of outdoor escalators in a more sustainable manner, which would in turn support the 2030 Agenda for Sustainable Development. This requires joining efforts of all relevant stakeholders in coordinated and rigorous action towards achieving road safety targets.

Towards Sustainable Road Safety in Saudi Arabia: Exploring Traffic Accident Causes Associated with Driving Behavior Using a Bayesian Belief Network

Understanding the causes and effects of road accidents is critical for developing road and action plans in a country. The causation hypothesis elucidates how accidents occur and may be applied to accident analysis to more precisely anticipate, prevent, and manage road safety programs. Driving behavior is a critical factor to consider when determining the causes of traffic accidents. Inappropriate driving behaviors are a set of acts taken on the roadway that can result in aberrant conditions that may result in road accidents. In this study, using Al-Ahsa city in Saudi Arabia’s Eastern Province as a case study, a Bayesian belief network (BBN) model was established by incorporating an expectation–maximization algorithm. The model examines the relationships between indicator variables with a special focus on driving behavior to measure the uncertainty associated with accident outcomes. The BBN was devised to analyze intentional and unintentional driving behaviors that cause different types of accidents and accident severities. The results showed when considering speeding alone, there is a 26% likelihood that collision will occur; this is a 63% increase over the initial estimate. When brake failure was considered in addition to speeding, the likelihood of a collision jumps from 26% to 33%, more than doubling the chance of a collision when compared to the initial value. These findings demonstrated that the BBN model was capable of efficiently investigating the complex linkages between driver behavior and the accident causes that are inherent in road accidents.

The Evaluation of Experimental Variables for Sustainable Virtual Road Safety Audits

This paper evaluates experimental variables for virtual road safety audits (VRSAs) through practical experiments to promote sustainable road safety. VRSAs perform road safety audits using driving simulators (DSs), and all objects in the road environment cannot be experimental variables because of realistic constraints. Therefore, the study evaluates the likelihood of recommendation of VRSA experimental variables by comparing DSs experiments and field reviews to secure sustainable road safety conditions. The net promoter score results evaluated “Tunnel”, “Bridge”, “Underpass”, “Footbridge”, “Traffic island”, “Sign”, “Lane”, “Road marking”, “Traffic light”, “Median barrier”, “Road furniture”, and “Traffic condition” as recommended variables. On the contrary, the “Road pavement”, “Drainage”, “Lighting”, “Vehicle”, “Pedestrian”, “Bicycle”, “Accident”, and “Hazard event” variables were not recommended. The study can be used for decision making in VRSA scenario development as an initial effort to evaluate its experimental variables.

Sustainable Public Safety and the Case of Two Epidemics: COVID-19 and Traffic Crashes. Can We Extrapolate from One to the Other?

COVID-19 and motor vehicle crashes (MVC) are both considered epidemics by the U.S. Centers for Disease Control (CDC) and the World Health Organization (WHO), yet their progression, treatment and success in treatment have been very different. In this paper, we propose that the well-established sustainable safety approach to road safety can be applied to the management of COVID-19. We compare COVID-19 and MVC in terms of several defining characteristics, including evolvement and history, definitions and measures of evaluation, main attributes and characteristics, countermeasures, management and coping strategies, and key success factors. Despite stark differences, there are also some similarities between the two epidemics, and these enable insights into how the principles of sustainable road safety can be utilized to cope with and guide the treatment of COVID-19. Major guidelines that can be adopted include an aggressive policy set at the highest national level. The policy should be data- and science-based and would be most effective when relying on a systems approach (such as Sweden’s Vision Zero, the Netherlands’ Sustainable Safety, and the recommended EU Safe System). The policy should be enforceable and supplemented with positive public information and education campaigns (rather than scare tactics). Progression of mortality and morbidity should be tracked continuously to enable adjustments. Ethical issues (such as invasion of privacy) should be addressed to maximize public acceptance. Interestingly, the well-established domain of MVC can also benefit from the knowledge, experience, and strategies used in addressing COVID-19 by raising the urgency of detection and recognition of new risk factors (e.g., cell phone distractions), developing and implementing appropriate policy and countermeasures, and emphasizing the saliency of the impact of MVC on our daily lives.

Speed perception by drivers as dependent on urban street design; a case-study

The strategy of sustainable road safety aims to match the road design characteristics to the target travel speeds, on every road type. This study examined the speed perception by drivers on collector urban roads in Israel, as reflected in their actual travel speeds and in the speeds reported by drivers. First, field surveys were conducted to collect detailed data on the road design characteristics, travel speeds, vehicle traffic and pedestrian activities on 80 urban street sections, in fifteen cities. Second, a drivers' survey was undertaken in proximity to the areas of the field surveys, to collect drivers' opinions about appropriate speeds on various street sections. The survey included 200 drivers, where each participant estimated four pictures with representative layouts of the study streets. Multivariate regression models were developed to examine the relationship between street characteristics, traffic exposure and travel speeds, as well as to explore the relationship between the driver characteristics, street design and speeds as reported by drivers. The results showed that road layout type was the most influential on selecting speeds. Multi-lane dual-carriageway roads are characterized by the highest actual and reported speeds, lower speeds are attributed to single-lane dual-carriageway and single-carriageway roads, and the lowest ones - to one-way streets. Among other characteristics moderating actual travel speeds were: higher pedestrian activity on the street, higher visual narrowing, more pedestrian attractions, presence of non-signalized junctions. The selection of speeds by drivers was affected by the street layout, the road visual narrowing, the socio-economic level of the town and driver's personal characteristics. The drivers believed that for moderate street layouts, the appropriate speeds should be around 40 km/h, i.e. below the existing speed limit. The road design characteristics that were found to affect the speed selection by the drivers may be applicable for attaining targeted travel speeds on collector streets.

Saving lives through vehicle safety

Saving lives through vehicle safety

An approach driven critical review on the use of accident prediction models for sustainable transport system

Over the past decade, the use of statistical analysis for the prediction of road accidents in sustainable road infrastructure and road safety has become popular. However, due to lack of adequate knowledge, for practical applications, a gap has been found between state-of-art and state-of-practice. The primary objective of this paper is to introduce a new innovative statistical technique called Accident Prediction Model (APM) along with its types, and possible challenges with their solutions while dealing with these models. In nutshell, why and how APM can contribute to improving road safety has been discussed in depth. The study recommends the use of APM for precise, accurate and effective prediction of road accidents for sustainable road infrastructure.

Traffic Accident Spatial Simulation Modeling for Planning of Road Emergency Services

The appropriate locations of road emergency stations (RESs) can help to decrease the impact of traffic accidents that cause around 50 million injuries per year worldwide. In this research, the appropriateness of existing RESs in the Khuzestan province, Iran, was assessed using an integrated fuzzy analytical hierarchy process (FAHP) and geographic information system (GIS) approach. The data used in this research were collected from different sources, including the department of roads, the department of health, the statistics organization, forensics, police centers, the surveying and geological department, remotely-sensed and global positioning system (GPS) data of accident high crash zones. On the basis of previous studies and the requirements of the Ministry of Health and Medical Education, as well as the department of roads of Iran for the location of RESs, nine criteria and 19 sub-criteria were adopted, including population, safety, environmental indicators, compatible area in RES, incompatible area in RES, type of road, accident high crash zones, traffic level and performance radius. The FAHP yielded the criteria weights and the ideal locations for establishing RESs using GIS analysis and aggregation functions. The resulting map matched the known road accident and high crash zones very well. The results indicated that the current RES stations are not distributed appropriately along the major roads of the Khuzestan province, and a re-arrangement is suggested. The finding of the present study can help decision-makers and authorities to achieve sustainable road safety in the case study area.

Surrogate Measures for Traffic Safety Evaluation in Developing Countries: An Application Toward Sustainable Safety

Abstract Road traffic crashes have significant negative social, economic, and infrastructure consequences, particularly in developing countries. The methods for evaluating the causal factors to identify appropriate interventions and to mitigate the problem are causes of great concern in those countries. One of the major reasons is that the evaluation methods are still based on traditional approaches, which mainly rely on the reported crash records. The underreporting coupled with the incomplete and inconsistent recording of crashes is a major issue in such settings. Poor timelines, ethical issues, biasness, and human error are also critical issues. Using a case study from Bangladesh, an assessment of the data quality of reported crash databases is presented in this article. The approach offers a means to develop and apply a robust method that can yield targeted safety measures without the need for using crash data. The application of traffic conflict techniques, which has gained research interest as a proactive surrogate approach, could be a better alternative. However, the testing and application of this approach are still confined to the lane-based homogeneous traffic environment, which mainly prevails in developed countries. Considering the traffic characteristics and limited facilities in developing countries, this article outlines an adapted framework for safety evaluation using a traffic conflict technique. The adapted technique has been applied in a major highway section of Bangladesh and validated by comparing the characteristics of the estimated conflicts and real crash data. Finally, future research directions for achieving sustainable road safety objectives in developing countries are outlined.

Driven by Distraction: Sustainable Road Safety and the Impact of Autonomous Driving on Vulnerable Users ( breakout presentation )

This presentation first it will deal with how pedestrians will have to be taken into account by Autonomous Vehicles (AV) and second with how this new technology will impact sustainable mobility and cities in general. Twentieth century cities were shaped by motorization while humanity is still moving towards different forms of urban settlements. Half of those dying on the world's roads are “vulnerable road users” outside of potential AV. From the easier challenge of finding algorithms for AV in open intra-urban roads, the debate should shift to how to tackle safety in urban roads and assure more sustainable and equitable Transportation as a Service (TaaS) models. Pedestrians pose very complex challenges to AV. Being a pedestrian is a universal condition - no ability test is necessary. Hopefully there will be always people walking the streets who are unpredictable and physiologically unable to assess danger - a well designed system should prioritise the safety of the most vulnerable. Therefore, we will argue that pedestrian safety should be yardstick to measure the quality of any ethical system and the centerpiece of the debate. However, there is a lot to be done using available and affordable technology: Transit Oriented Communities have about one-fifth of the per capita traffic casualty rate as automobile-oriented communities. Moreover, fatalities and injuries are only a small part of the car externalities - congestion, pollution, space waste will not disappear with AV. Automation might in fact reduce considerably the cost of driving, thus increasing the aforementioned externalities. Only a smart use of technology, serving clear sustainable mobility objectives, will be able to avoid worse consequences. We will argue that we are all better off with carless drivers instead of driverless cars.

Positive evaluation and learning: Looking for ‘success’ in Netherlands road safety policy

Traditionally, many academics and practitioners seek the added value of evaluation primarily to highlight errors and shortcomings. As a consequence, evaluative inquiry risks becoming associated with failure and, therefore, best to be avoided. It seems that, in this respect, evaluators may be their own worst enemies: how much of the perpetual questions and disappointments that often still seem to plague our craft – perceived lack of relevance and, hence, attention and utilization – can be blamed on our natural focus on problems and failure? What could be gained from a positive evaluation approach, in which the evaluator actively seeks to improve policy programmes by focusing on success? How can it contribute to effective learning? What benefits and challenges would emerge? Taking the ‘Sustainable Road Safety’ programme of The Netherlands as an example, this article investigates potential answers to these questions. Starting from a definition of positive evaluation and learning theory, I will describe the opportunities of positive evaluation for more effective policy-oriented learning processes. From this example, the positive – but cautious – conclusion is that, in order to contribute to effective learning while seeking to optimize policy programmes, an evaluator could do well to opt for ‘looking for success’ first.

Robust data management- Sine Qua Non for sustainable road safety in Nigeria

This paper makes a case for robust data management in Nigeria as well as presents road safety approaches that required data collection, analysis, management, sharing and dissemination for sustainable road safety in Nigeria. It therefore points out the relevance of data management for worthwhile safety programme. This paper advocates for a veritable database with reliable, accurate and up-to-date information on road traffic crashes, mortality rate, high risk areas, driver’s license, vehicle population, road audit survey, traffic count, offenders, offences, personnel and other important details which can be stored, retrieved, updated, maintained, processed and shared for comprehensive analyses as well as make evidence-based policies on road safety issues in a sustainable way.