The Sustainable Road Traffic and Road Safety Vol 35 No 6 (2023)
Dr. Stevanovic is an Associate Professor of the Department of Civil and Environmental Engineering at the University of Pittsburgh. He teaches courses in traffic engineering, transportation planning, and operations research and conducts research in a variety of subjects including traffic signal control systems, intelligent transportation systems, multimodal and sustainable operations, transportation simulation modeling, etc. He has advised more than 30 graduate students (MSc and PhD) and five post-doctoral associates. He has published more than 150 journal and conference papers and presented at more than 80 international, national, and state seminars and professional meetings. He has been principal investigator on 31 research projects for a total of ~ $3.9 million in funding, and has authored more than 30 technical reports for various transportation agencies, including TRB/NAS, NSF, UDOT, UTA, FLDOT, NJDOT, and others. Dr. Stevanovic is a member of TRB AHB25 Committee for Traffic Signal Systems and he is also member of ITE, TRB, ASCE, etc. Dr. Stevanovic serves as a paper reviewer for 30 scientific journals and conference proceedings. Although Dr. Stevanovic’s main research interests emphasize arterial operations and traffic signal control, he is best known for his contributions in Adaptive Traffic Control Systems (ATCS). He is a sole author of the NCHRP 403 Synthesis Study – Adaptive Traffic Control Systems: Domestic and Foreign State of Practice and has been invited many times to give talks and teach about ATCSs, both nationally and internationally. His research has been highlighted in a range of media articles - from local newspapers to the TIME magazine.
Luka Novačko, PhD is part of PROMET Traffic and Transportation editorial board for over five years, where he obtained functions of section editor for road transport.
As an Associate Professor at the Faculty of Transport and Traffic Sciences, University of Zagreb he obtains the function of Head of Department for Road Transport and he is also Head of Laboratory for Planning in Road Transport. His research interests include modelling and planning in road and urban traffic, traffic simulations and intersection design.
He was also involved in numerous scientific and expert projects in the field of road and urban traffic and transport.
Željko Šarić Ph.D. is Associate Professor at University of Zagreb, Faculty of Transport and Traffic Sciences. His research work includes analysis of traffic accidents and road traffic safety methods. As the Head of the Laboratory for Traffic - Technical Expertise at the Faculty of Traffic Sciences, he regularly organizes various tests of collision processes in crash tests. He is an authorized specialist for collection and analysis data from Event Data Recorder in vehicles and a Court Expert for traffic accidents. He led several dozens of projects in the field of road traffic safety and conducted several traffic accident expertise for courts in the Republic of Croatia. In co-authorship with foreign authors, he has published several scientific papers in prestigious international journals and he is the author of the official methodology for the identification of road black spots in the Republic of Croatia. He is an authorized auditor for road safety and a member of the international association of court experts European Association for Accident Research and Analysis
Dear readers, dear authors,
The significance of sustainable road traffic and safety cannot be overstated in the contemporary world. This importance stems from the intricate link between transportation, environmental sustainability and human safety. Roads are the arteries of modern societies, facilitating movement and connecting lives, but they also pose significant risks and environmental challenges.
Road traffic accidents are a leading cause of death and injury worldwide. According to the World Health Organization, approximately 1.19 million people die each year as a result of road traffic accidents. This staggering number underscores the critical need for safer road practices and infrastructure. The impact of these accidents extends beyond immediate physical harm, affecting families, communities and the broader economy. Road injuries and deaths often lead to significant financial burdens, loss of workforce and long-term psychological trauma. The burden of road traffic injuries and deaths disproportionately affects vulnerable road users – pedestrians, cyclists and motorcyclists – and people in low- and middle-income countries. These countries have around 60% of the world’s vehicles but account for over 90% of road traffic deaths, highlighting a significant inequality in road safety (source: WHO). The loss of young and working-age individuals in road accidents has a profound demographic impact. It deprives societies of productive workforce members and contributes to a loss of skills and potential.
Sustainable road traffic is also central to addressing environmental concerns. The transportation sector is a major contributor to greenhouse gas emissions, which are driving climate change. Motor vehicles emit carbon dioxide and other pollutants that degrade air quality, harm public health and contribute to global warming. Implementing sustainable practices in road traffic management, such as promoting the use of electric vehicles, improving public transportation systems, and encouraging biking and walking, can significantly reduce these environmental footprints. Efficient and sustainable road traffic systems are vital for economic prosperity. Traffic congestion, a common issue in many urban areas, results in significant economic costs due to lost time, reduced productivity and increased fuel consumption. Sustainable traffic management strategies that reduce congestion can therefore contribute to economic efficiency and productivity. Additionally, investments in road safety and sustainable infrastructure are often recouped through reductions in the costs associated with accidents and environmental degradation.
Public transportation and cycling are cornerstones of sustainable urban traffic management. Efficient public transit systems significantly reduce the reliance on private vehicles, thus lowering traffic volume, decreasing emissions and conserving energy. They provide accessible and affordable mobility options, enhancing the inclusivity of city transportation networks. Cycling, supported by dedicated bike lanes and shared bike programs, serves as a zero-emission transport solution, further contributing to urban sustainability. Both modes promote environmental health by reducing the carbon footprint and improving air quality. Together, they represent key strategies for creating greener, more liveable and less congested urban environments, aligning with broader goals of sustainable city development.
Emerging technologies such as autonomous vehicles (AVs), smart traffic lights and artificial intelligence (AI) have begun to revolutionise road safety and sustainable road transport. These innovations hold the promise of drastically reducing traffic accidents, enhancing the efficiency of transport systems and reducing environmental impacts.
In conclusion, the importance of sustainable road traffic and safety is multifaceted, encompassing human, environmental, economic, social and health dimensions. It is a critical area that demands attention from policymakers, urban planners, engineers and the public. By focusing on sustainable practices and safety, we can work towards a future where roads continue to connect and enrich our lives without the current levels of associated risks and environmental costs.
We would like to express our gratitude to the authors, the reviewers and the Editor-in-Chief of Promet – Traffic&Transportation, Prof. Ivona Bajor, for giving us the opportunity to compile this reflection on current research in road safety and sustainable road transport.
Yours sincerely, editors of the thematic issue,
Assoc. Prof. Aleksandar Stevanovic, Ph.D.
University of Pittsburgh
Swanson School of Engineering
Assoc. Prof. Luka Novačko, Ph.D.
University of Zagreb
Faculty of Transport and Traffic Sciences
Assoc. Prof. Željko Šarić, Ph.D.
University of Zagreb
Faculty of Transport and Traffic Sciences
More and more connected and autonomous vehicle (CAV) open test roads reconstructed on the basis of traditional roads have appeared in China. However, the management policies vary, which makes the traffic environment complicated. This paper takes CAV test road safety management as the research aim and investigates the open test condition through the evaluation of the traffic safety facilities. Indicators were rigorously screened, then the game theory model was used to determine the combination weight of the indicators, and the set pair analysis was applied to solve the uncertain problems. A case study for the CAV test road network of a city in central China was implemented and the results show, regarding the traffic safety facilities’ condition, among the 20 sections of the city’s CAV test road network, 15% of which are at an excellent level, 75% of which are at a good level and 10% of which are at a moderate level; road signs, guardrail facilities, isolation facilities and road features are the main limiting factors affecting the level of traffic safety facilities. Based on the results, recommendations have been made for the transport management authorities in the aspects of safety management policy-making and facilities maintenance.
Turkey’s expanding population and growing economy have resulted in a significant increase in automobile ownership, leading to a rise in traffic volume and, subsequently, an increase in the number of accidents. The increase in the number of deaths and injuries caused by traffic accidents has motivated authorities and automobile manufacturers to work together to mitigate the impact of traffic accidents. Therefore, the demand for better roads, modern technologies and higher-quality driver training is becoming increasingly urgent for traffic safety. Due to the scale of harm to the country’s economy and society caused by the material and moral losses, resulting from traffic accidents, traffic safety and management is one of the most important government initiatives. One of the responsible units of traffic safety and management in Turkey is the traffic gendarme. This study reviewed the categories of traffic accidents, the number of accidents, and the road network that occurred in a province's gendarme responsibility area in Turkey and linked them with the number of traffic gendarmes in that province. Thus, the study utilised mixed integer programming based on multi-criteria decision-making methods to identify the areas where these traffic gendarmes will be deployed according to established principles.
Road elements are increasingly digitalized to provide drivers advanced assistance especially in the emergent or adverse conditions. It is challenging and expensive to accurately digitalize all the road elements especially on the urban roads with many infrastructures and complex designs, where we may focus on the most important ones at the first stage. This research designs a questionnaire to ask the drivers to rank the importance of the road elements in various driving conditions. Driver characteristics are also collected, including age, driving style, accident experience, and accumulated driving distance, to explore their effect on drivers’ cognition of road elements importance. It is found that driving is a complex activity, and the moving elements (e.g. surrounding cars) are more important than the non-moving ones. Attention should be paid to the road elements even distant from the ego car, to get prepared to the potential driving risk or penalty. Statistical difference between the experienced and non-experienced drivers recommends that driver assistance system should be sufficiently trained in various conditions, to build up autonomous driving tactics and skills. This research promotes the understanding of driving cognition pattern to provide insights into the development of road digitalization.
Heinrich’s Law indicates an empirical ratio between serious accidents, minor accidents and near misses in industrial sites, but has not been discussed in the context of road traffic accidents. Digital tachographs (DTG), a type of IoT device collecting spatiotemporal big data of vehicle trajectories, allow0 for examining a linkage between abnormal driving behaviours and the prevalence of road traffic incidents. According to the Traffic Safety Act implemented in 2011, DTG has been mandatorily pre-installed on most commercial vehicles in South Korea. The data have been analysed to evaluate the data processing method or promote eco-driving or safe driving, but only a few studies have examined an association between driving behaviours and actual traffic accidents using the limited data. We obtained 7,785,124 DTG sensing records from 1,523 commercial taxis driving within the city limits of Seoul at least once in 2013 and integrated them with 57,139 traffic accident cases during the same period. Using the integrated GIS database, we performed a grid-based spatiotemporal mapping and analysis to calculate a ratio among abnormal driving events, minor and major traffic accidents by road type. The findings suggest a potential for enhancing road safety by monitoring and controlling abnormal driving patterns as a precursor for accidents.
This study investigated several factors that may influence driver actions throughout the yellow interval at urban signalised intersections. The selected samples include 2,168 observations. Almost 33% of drivers stopped ahead of the stop line, 60% passed the intersection through the yellow interval, and 7% passed after the yellow interval was complete (red light running, RLR violations). Binary logistic regression models showed that the chance of passing went up as vehicle speed went up and down as the gap between the vehicle and the traffic light and green interval went up. The movement type and vehicle position influenced the passing probability, but the vehicle type did not. Moreover, multinomial logistic regression models showed that the legal passing probability declined with the growth in the green time and vehicle distance to the traffic signal. It also increased with the growth in the speed of approaching vehicles. Also, movement type directly affected the chance of legally passing, but vehicle position and type did not. Furthermore, the driver’s performance during the yellow phase was studied using the k-nearest neighbours algorithm (KNN), support vector machines (SVM), random forest (RF) and AdaBoost machine learning techniques. The driver’s action run prediction was the most accurate, and the run-on-red camera was the least accurate.
To develop effective interventions to transit the instant delivery service riders towards avoiding red light running behaviour, a valid and reliable questionnaire is needed to identify the potential theoretical factors that influence the intention. This study describes the development and validation of the red light running behaviour causes questionnaire based on the theoretical domains framework. First, the exploratory factor analysis was used to identify the initial questionnaire’s underlying structure, including a set of 67 items in 13 domains. Next, confirmatory factor analysis was undertaken to assess the questionnaire’s reliability, discriminant validity and goodness of fit. CFA produced a proper fit with adequate discriminant validity and internal consistency. CFA and Cronbach’s alpha results in the final version of the RLRBCQ consisted of 39 items assessing 13 domains, explaining 69.799% of the variance, and internal consistency reliability values ranging from 0.710 to 0.825. These results suggest that the RLRBCQ demonstrates reliable, stable and valid properties, which can be used to assess potential determinants of avoiding red light running behaviour following the domains of the TDF. It can be utilised by safety managers and practitioners to guide the design of interventions for various traffic safety behaviours.
This paper presents the main challenges of integrating micromobility vehicles into modern traffic and transportation systems. Although micromobility seems to be an effective concept for the first and last mile, the reality points to the potential problems that the integration of micromobility vehicles can create and that must be resolved appropriately. Micromobility vehicles are characterised by extensive development, which is not accompanied by appropriate legal regulations. The street design has its spatial limitations and usually separates non-motorised and motorised users, which is a notion that could be disrupted by new micromobility options. When it comes to Serbia, the existing legislation does not recognise the majority of micromobility vehicles, which results in the lack of safety of these participants and their place in the street profile. The aim of this paper is to provide guidelines for improving the existing regulations and integrating these vehicles into the traffic system of Serbia, with special reference to general recommendations through which micromobility vehicles can be treated in other countries. The results of this paper can be useful to decision-makers but also to all other participants in the process of developing effective policies and strategies for the integration of micromobility vehicles into traffic and transportation systems.
Dockless bike-sharing (DBS) is an effective solution to the “first and last mile” problem in urban transportation. It can be integrated with urban rail transit (URT) to provide passengers with more convenient travel services. This study focuses on the integrated use of DBS and URT in Shenzhen, utilising a multi-buffer zone approach to identify DBS data within URT station catchment areas. By employing ordinary least squares (OLS), geographically weighted regression (GWR) and multiscale geographically weighted regression (MGWR) models, the spatiotemporal heterogeneity of integrated use and its relationship with environmental factors surrounding URT stations were examined. The empirical findings highlight the superiority of the MGWR model in accurately explaining spatial relationships compared to the OLS and GWR models. Furthermore, the study reveals that the impact of built environment factors on integrated use varies during morning and evening peak periods, as well as in terms of access and egress. Specifically, factors such as catering, shopping, companies, residential buildings, bus stops, minor roads, transfer stations and population density were found to influence the integrated use of DBS and URT. These findings not only contribute to the promotion of the DBS-URT integration but also promote the overall development of urban transportation.
Parking search reduces the quality of parking service, as well as traffic network level of service, due to additionally generated traffic. Parking search also entails other negative effects, primarily ecological, social and economic. Even though the importance of this problem has been noted in the past, there is an impression that this issue has not been sufficiently researched and should be additionally analysed in order to properly understand this phenomenon. Therefore, the aim of this paper is to study the factors affecting parking search time that can be influenced through a set of parking management measures. In this paper, an ordinal regression model was developed to estimate these parameters and it was fitted using empirical data collected by interviewing drivers. Main model results show that parking occupancy has the highest impact upon the value of parking search time, indicating the significance of defining proper policies and measures aimed at reaching targeted parking occupancy. Parking frequency is the second parameter observed to be significant, demonstrating the importance of implementing proper parking information systems.
Freight transport significantly contributes to urban traffic but is often overlooked by decision-makers compared to passenger transport. Conventional transportation modelling studies often use aggregate approaches for freight transport, undoubtedly due to the difficulty of data collection. However, the nature of freight transportation is much more complex. For this reason, examining the determinants of freight vehicle preferences with discrete approaches is crucial for the contributions that can be put forward, especially in local studies. To address this apparent gap in the study of local disaggregated approaches to freight transport, we present a discrete modelling-based methodology to investigate the factors that determine freight vehicle preferences for shippers and senders. The estimated nested logit model is constructed with the RU2 approach, the second part of random utility theory, thus avoiding the theoretical inconsistencies that arise when generic coefficients are used. As a result, the model structures provided satisfactory results compared to the literature. It was revealed that the factors affecting freight vehicle choice preferences were influenced by packaging preferences and differed according to freight groups. This local study is the first nested logit study for freight modelling in Istanbul and it is aimed to shed light on future national studies.
In this paper, the influence of traffic flow volume and meteorological conditions on carbon monoxide (CO), particulate matter (PM), ozone (O3) and sulphur dioxide (SO2) concertation is determined based on the measurements conducted at a selected location over a 784-hour period. Multivariate Analysis of Variance (MANOVA) and Analysis of Variance (ANOVA) were applied to the data set. Regression analysis was also used to determine trends in pollutant concentrations as a function of traffic flow and meteorological parameters. Analysis of the obtained data indicates a statistically significant relationship between traffic volume and meteorological parameters on the one hand and pollutants on the other. However, increase in the value of certain input variables does not necessarily result in the increase in pollutant concentration. CO and O3 showed a significant dependence on the number of vehicles, while for SO2 the influence of commercial vehicles was greater than that of passenger cars. The relationship between the number of vehicles and PM was not evident at the study site.
The emergence of global health crises has emphasised the need for efficient and secure methods to verify the individuals’ vaccination and testing status. The research paper proposes an innovative application of the Radio Frequency Identification technology to develop a comprehensive system that ensures the controlled entry of vaccinated and tested individuals into buildings and extends its use to transportation networks. By combining tags, readers and a centralised database, with the extension of using Message Queuing Telemetry Transport, this solution aims to enhance public health safety, restore confidence in public spaces and optimise transportation operations.