Traffic Safety Problems Research Articles

Bicycling tasks relation to stability measures during alcohol intoxication

Bicycling accidents are a major traffic safety problem and are deemed ‘an unacceptable human and social price for EU citizens’. One of the major causes for bicycling accidents is loss of balance. A related influencing factor is alcohol intoxication. It is a primary, long term, safety objective to develop safety systems for the cyclist. The present work aimed to understand how to measure cyclists’ instability via steering and leaning inputs, while considering that steering and leaning might vary depending on the cycling task being performed. Of 28 participants, 19 were given doses of alcohol up to 1.0‰ and 9 remained sober (control group). Breath alcohol concentration was measured. The participants repeated the cycling test track session five times (with each block lasting 35 minutes). The track session contained three different tasks: cycling slalom, straight, and slowly. Speed, yaw rate, and roll rate were assessed continuously. Yaw rate and roll rate were relatively sensitive for the different cycling tasks. The threshold level of the angular velocity measurements was related to the cycling task performed. Alcohol intoxication at 0.7‰ had a significant impact on performance. The rather simple measurements used can detect instability. Instability should be measured differently depending on the cycling task performed. The study represents a small step towards a safety system for cyclists.

Modeling and Performance Study of Vehicle-to-Infrastructure Visible Light Communication System for Mountain Roads.

Visible light communication (VLC) is considered to be a promising technology for realizing intelligent transportation systems (ITSs) and solving traffic safety problems. Due to the complex and changing environment and the influence of weather and other aspects, there are many problems in channel modeling and performance analysis of vehicular VLC. Unlike existing studies, this study proposes a practical vehicle-to-infrastructure (V2I) VLC propagation model for a typical mountain road. The model consists of both line-of-sight (LOS) and non-line-of-sight (NLOS) links. In the proposed model, the effects of vehicle mobility and weather conditions are considered. To analyze the impact of the considered propagation characteristics on the system, closed-form expressions for several performance metrics were derived, including average path loss, received power, channel capacity, and outage probability. Furthermore, to verify the accuracy of the derived theoretical expressions, simulation results were presented and analyzed in detail. The results indicate that, considering the LOS link and when the vehicle is 50 m away from the infrastructure, the difference in channel gain between moderate fog and dense fog versus clear weather conditions is 1.8 dB and 3 dB, respectively. In addition, the maximum difference in total received optical power between dense fog conditions and clear weather conditions can reach 76.2%. Moreover, under clear weather conditions, the channel capacity when vehicles are 40 m away from infrastructure is about 98.9% lower than when they are 10 m away. Additionally, the outage probability shows a high correlation with the threshold data transmission rate. Therefore, the considered propagation characteristics have a significant impact on the performance of V2I-VLC.

Design, development, and evaluation of a multi-lingual web-based database for informing people regarding driving-impairing medicines

Objective Driving under the influence of drugs (DUID) is a growing traffic safety problem in many countries. It is estimated that 5 to 10% of medicinal drugs may impair driving due to their side effects. Despite the high number of medicinal drugs prescribed in Iran, there is a lack of a database that could provide specialized information regarding medicinal drugs and driving. Therefore, the present study aimed to design, develop, and evaluate a database for informing the general public, drivers, and healthcare providers regarding driving-impairing medicines. Methods The Drugs-and-traffic-safety (DATS) database, which has been developed by Road Traffic Injury Research Center (RTIRC), was designed using Java, HTML, JavaScript and MySql database. After completing the testing process, pharmaceutical data (i.e., generic and brand names, route of administration, anatomical classification, etc.), the level of influence of medicinal drugs on driving, and driving-related recommendations based on the level of influence for consumers were entered into the database. A cross-sectional study, and a qualitative study as semi-structured interviews and expert panels were conducted in different target groups to evaluate the DATS. Finally, the evaluation results were used to improve the database. The quantitative and qualitative data were analyzed using SPSS 25.0 and MAXQDA-10, respectively. Results The DATS was the only web-based database that could be accessed online via different browsers. The database included information about 1,255 medicinal drugs, and their influence on driving was shown with four colors, i.e., green (insignificant or no effect), yellow (mild effect), orange (moderate effect), and red (severe effect). The database was designed in multiple languages, which could enable users to search for medicinal drug names in both Persian and English. Based on the quantitative results, the mean score of the DATS was 75.10 ± 16.01 (out of 100) from the public viewpoint, indicating that the users were relatively satisfied with the database. Some themes and subthemes were extracted from the qualitative section of the study which revealed the users found DATS a practical, useful, and user-friendly tool. Conclusion Considering the positive feedback of users about DATS in the quantitative and qualitative evaluations, implementing DATS in Iran could provide useful advice in terms of the influence of medicinal drugs on driving to the public and traffic users. Therefore, it can raise public awareness of the risk of driving under the influence of medicinal drugs.

Does expanding wild venison consumption substitute livestock meat consumption? Evidence from the demand systems analysis of meat products in Hokkaido, Japan

In many countries, growing deer populations cause environmental, economic, and traffic safety problems. This study sheds light on the potential implications of expanding the consumption of venison from hunted wild deer through deer population management efforts. It focuses on changes in environmental impacts resulting from changes in the demand for livestock meat due to increased consumption of wild venison. We analyzed the demand system between them using the Quadratic Almost Ideal Demand System (QUAIDS) model and scanner data from a grocery store chain in Hokkaido Prefecture, Japan. The results show that wild venison is a substitute good for pork and lamb. By contrast, wild venison is a complementary good for imported and domestic beef. Based on the estimated demand system model, we conducted an environmental footprint analysis to estimate the changes in environmental impacts when venison consumption increased. This shows that the greenhouse gas, water, and land footprints would increase, indicating greater environmental impacts, under a scenario of expanded venison consumption. The results demonstrate that increased venison consumption does not necessarily reduce the net environmental impacts of meat consumption, which depends on the demand system for meat products and the environmental footprint intensities of the respective products.

Speed Corridor Enforcement System (SCES) - A Case Study of the Highways of Kosovo

Background Traffic safety remains a significant global concern. Despite advancements in vehicle technology, road infrastructure improvements, and initiatives to raise driver awareness, traffic accidents continue to pose socio-economic problems. Objectives The aim of this study was to suggest the potential benefits of implementing a Speed Corridor Enforcement System on highways in Kosovo, aiming to reduce accidents and promote driver awareness. Methods To accomplish the stated objective, there is employed a scientific research methodology supported by surveys, statistics, and analysis methods. The sources of information comprise both primary and secondary data, which were gathered from scientific literature, online sources, and relevant studies in the field. Results The significant socio-economic challenges arising from traffic accidents are discussed, highlighting the necessity for a comprehensive and multidimensional approach to effectively address this issue. Additionally, the proposal of implementing Speed Control Enforcement Systems on the highways of Kosovo, which are part of Intelligent Transport Systems, is emphasized as a solution. Emphasis is placed on the importance of adopting advanced technological solutions alongside comprehensive strategies to effectively tackle the complex problem of traffic safety. Conclusion Considering the alarming 53.41% increase in accidents in Kosovo, the implementation of the speed identification system in corridors could have initially prevented and reduced accidents by a percentage similar to those observed in the reference countries.

Analysis of Road Infrastructure Problems in Urban City, Karachi

Road infrastructure is a significant part of the economic development of countries. Better performance of road communication system is significant part of all over the world. Developed countries make a significant effort for designing a well-managed traffic arrangement for the individuals. Furthermore, an efficient transport system is the key element for improving the country's economic conditions. Sustainable and efficient traffic management system is the backbone for humanizing the economic growth of developing countries. In case of Pakistan, Karachi is the main industrial hub for whole country's economy and accommodates enormous number of migrants. Due to this reason the population of city is increasing day by day. This paper presents the current situation of road infrastructure troubles in Karachi. The urban city is facing several numbers of issues that were already documented by researchers such as traffic congestion and road safety problems. On an urgent basis an efficient mass transit system is required to reduce the traffic jam conditions. The transport system of Karachi requires instant proper management rules and designed transport facilities. The aim of the paper is to identify the main traffic problems of the large urban city, Karachi, which is faced by the people in their daily life and to suggest recommendations for reducing the current situation related to traffic management strategies. The research methodology for this paper will be based on qualitative analysis of the road infrastructure troubles that are identified by the individuals through interviews and detailed group meetings.

The impact of driver turnover on traffic safety

This article discusses socio-economic approaches to ensuring road safety, which is one of the main problems facing road transport in our republic. In the road traffic system, the driver is the controlling link, so the problem of traffic safety should be considered not only as a technical one, but also as a social one, coordinating a link of other links. For this reason, the driver was chosen as the subject of the study. First of all, an analysis of road accidents that occurred in our country over the past two years was presented, according to the social indicator of the driver. At the next stage, the main indicators of the study were determined and research methods were developed for each indicator: Methods for studying statistical accounting and reporting, Interviewing, Questionnaire method. In conclusion , the study presents the results of a sociological study reflecting the problems of individual safety in the road traffic system. An assessment is given for road safety socio-economic factors. A sociological model of accident rates and driver stability is proposed .

Study of traffic safety on the street and road network of Ternopil

The road safety issues in the city of Ternopil are studied in this article. The found actual deficiencies were structured according to the main indicators. Based on the analysis of the movement of traffic flows in the morning period, the most problematic sections of the SRN (street and road network) were identified. In general, the speed of traffic flows along the SRN in the evening peak period was found significantly lower than in the morning peak period. To analyze road traffic safety in the city of Ternopil, a cartographic method was applied. Based the obtained results, the road accidents in Ternopil mostly occur along main streets without clearly defined places of concentration. In this regard, a conditional indicator of the danger of transport corridors of Ternopil was derived, which allows analyzing the predominant location (clustering) of road accidents with victims in each district of the city. The current policy and practices of Ternopil in the field of road safety management need improvement. However, the volume of performed measures does not fully cover the need in traffic safety insurance and information provision of traffic participants. In general, it can be stated that proactive actions in the field of ensuring traffic safety are just starting in Ternopil (“starting city”). Thus, it differs favorably from the vast majority of other regional centers, in which the problem of traffic safety has not been even discussed so far. In addition, the plan for sustainable urban mobility is under consideration in the Ternopil City Territorial Community.

Analysis of selected road traffic safety problems in Poland and Mazovia

In Poland, the risk of road safety is still one of the highest in the EU and, despite a 36% decrease in the number of fatalities, requires further intensive work to reduce the risk associated with travelling on the roads. In 2021, the National Road Safety Program for 2022-2030 was announced, which should be followed by regional programs. The article presents a set of information needed to diagnose traffic safety at the province level. Using the example of the Masovian Province, basic statistical data, road safety trends, basic risk indicators, the structure of accidents and fatalities from various perspectives were presented. In addition, the costs of accidents and collisions that occurred in the Masovian Province were shown. Based on the analyses conducted, the characteristic features and main road safety problems in the province were identified. The analyses and their results presented show that the annual costs of all road accidents in the Masovian Province, although decreasing, still significantly exceed the expenses planned in the province budget for a given year. Therefore, reducing the number of road incidents, especially accidents, and their consequences may bring significant savings to the province budget.

Road Rage and Anger-Provoking Situations in Sulaimani City- Iraq

Driver behavior factors, including road rage factor, are often responsible for increasing traffic accidents that result in deaths, physical injuries, psychological problems, and financial losses. In order to improve traffic safety problems in our country, road rage issues related to anger-provoking situations were explored. To collect data, two questionnaire survey forms related to road rage level, traffic characteristics, and demographics of the drivers were prepared. The road rage questionnaire form included 12 questions related to popular anger-provoking situations. Six Likert scales were scored starting from 0% to 100%. Out of 600 spread forms, 463 valid forms were accepted to be analyzed. Different participants having different gender, age, education level, driving experience, vehicle type, daily travel time, vehicles’ price, traffic accidents, and the road rage history were contributed. A statistical software program (SPSS 26) was utilized to analyze the data. It was obtained that there are significant correlations among road rage-provoking anger questions and the total overall rate of the road rage. On the other hand, the results showed that male drivers are angrier than female drivers during driving. The older the drivers, the less overall road rage values were obtained. The overall road rage value decreased as the education level of the drivers raised to higher level. Driver skills had significant effects on the results of the overall road rage value of the drivers in which the drivers having 4 to 6 years of driving license were angrier than the other drivers, while drivers having driving license more than 6 years had the less feeling of anger during driving. Regarding types of vehicles, the bus, taxi, and then truck drivers had more overall road rage values than PC and SUV drivers. As the drivers traveled more distances, the obtained results of the overall road rage values became greater. The drivers who have high-price vehicles were angrier than those have low-price vehicles. The Drivers’ accident history did not significantly relate to overall road rage values. In addition, the drivers who did not have any road rage history in their real life had the smallest overall road rage values; while those drivers faced physical fighting and engaged police stations due to road rage problems had the greatest overall road rage value.

Play&Go Corporate: An End-to-End Solution for Facilitating Urban Cyclability

Mobility plays a fundamental role in modern cities. How citizens experience the urban environment, access city core services, and participate in city life, strongly depends on its mobility organization and efficiency. The challenges that municipalities face are very ambitious: on the one hand, administrators must guarantee their citizens the right to mobility and to easily access local services; on the other hand, they need to minimize the economic, social, and environmental costs of the mobility system. Municipalities are increasingly facing problems of traffic congestion, road safety, energy dependency and air pollution, and therefore encouraging a shift towards sustainable mobility habits based on active mobility is of central importance. Active modes, such as cycling, should be particularly encouraged, especially for local recurrent journeys (e.g., home–to–school, home–to–work). In this context, addressing and mitigating commuter-generated traffic requires engaging public and private stakeholders through innovative and collaborative approaches that focus not only on supply (e.g., roads and vehicles) but also on transportation demand management. In this paper, we present and end-to-end solution, called Play&Go Corporate, for enabling urban cyclability and its concrete exploitation in the realization of a home-to-work sustainable mobility campaign (i.e., ) targeting employees of public and private companies. To evaluate the effectiveness of the proposed solution we developed two analyses: the first to carefully analyze the user experience and any behaviour change related to the mobility campaign, and the second to demonstrate how exploiting the collected data we can potentially inform and guide the involved municipality (i.e., Ferrara, a city in Northern Italy) in improving urban cyclability.

Uncertainty propagation of flutter derivatives and structural damping in buffeting fragility analysis of long-span bridges using surrogate models

Buffeting of long-span bridges caused by the wind turbulence could result in problems of large deformation, fatigue, traffic safety and user comfort. The calculation of buffeting responses is greatly affected by multiple uncertainties, especially the randomness of flutter derivatives and structural damping. In buffeting analysis, these uncertainties are typically propagated using the brute-force Monte Carlo (MC) method, which requires enormous computational resources for a complicated structure involving multiple uncertainties. This study develops an efficient framework based on surrogate models to account for these uncertainties in buffeting responses and the assessment of structural fragility in a mixed climate. Two surrogate models, Kriging and polynomial chaos expansions (PCE), are applied in this framework. Comparison with the direct MC method shows that the Kriging model rather than the PCE model is the proper surrogate model, and the surrogate model contributes significantly to saving computing time from 17 h to 1 min for MC simulations.It is also observed that uncertainties propagated from structural parameters to responses will be more notable as the wind speed increase. Buffeting fragility curves of this bridge show that it’s easier for responses in acceleration to achieve and exceed thresholds, indicating that performance related to user comfort might not be satisfied. By introducing the probability distributions of non-typhoon and typhoon winds at the site of the bridge, it is found that considering single climate may underestimate structural risk. The framework based on surrogate models in this paper can be further generalized to additional PBWE frameworks addressing different wind and structural engineering issues.

Nonlinear impact analysis of built environment on urban road traffic safety risk

With the rapid development of economy, the increasing number of motor vehicles and the total road mileage, which leads to the increasingly prominent traffic safety problems. In order to explore the quantitative relationship between the built environment and the risk of urban road traffic safety, this paper reconstructs the built environment system based on the ‘5D' element model of the built environment combined with the factors influencing traffic safety risks, and describes the built environment from multiple aspects such as density, diversity &traffic design etc, and then build the gradient lift decision tree model to explore the importance and dependency of variables. The empirical analysis selects a district in Chongqing as the research unit, and the results show that: the RMSE the model was 0.0036, the MAPE was 1.9%, and the determination coefficient R2 was 0.84. GBDT algorithm results shows: the cumulative importance of population density, road facilities, intersection density, secondary road and branch road density, average intersection distance, land use mix, and economic density reaches 77.87%. Some variables show obvious nonlinearity and threshold effect.

Takeover quality prediction based on driver physiological state of different cognitive tasks in conditionally automated driving

In conditionally automated driving, traffic safety problems would occur if the driver does not properly take over the control authority when the request of automated system arises. Therefore, this study proposes XGBoost learning method considering risk potential field to predict the takeover quality in conditionally automated driving under different levels of cognitive non-driving related tasks (NDRTs). Thirty participants drive on two experimental conditions: manual driving is following an automated driving during which the driver is asked to perform NDRTs. Drivers’ physiological features of different cognitive states are exploited to model multi-level takeover quality prediction. This investigation also gives an insight into the main effects of the selected prediction variables on the takeover quality. The proposed model performance within different time windows is assessed using multiple evaluation metrics and compared with other methods. Results show that the prediction accuracy within the time windows of 7–10 s, 5–7 s, 3–5 s and 1–3 s is 0.87, 0.85, 0.85 and 0.90, respectively. The XGBoost model has the best performance of different time windows under each level of takeover quality compared to the other three machine learning models. Our findings can effectively predict the takeover quality and assist automated driving safely in interactions between drivers and automated vehicles.

Spatial and temporal prediction of secondary crashes combining stacked sparse auto-encoder and long short-term memory

Secondary crashes occur within the spatial and temporal impact area of primary crashes, resulting in traffic delays and safety problems. While most existing studies focus on the likelihood of secondary crashes, predicting the spatio-temporal location of secondary crashes could offer valuable insights for implementing prevention strategies. This includes guiding the deployment of emergency response measures and determining appropriate speed limits. The main objective of this study is to develop a prediction method for the spatial and temporal locations of secondary crashes. A hybrid deep learning model SSAE-LSTM is proposed by combining stacked sparse auto-encoder (SSAE) and long short-term memory network (LSTM). Traffic and crash data on the California I-880 highway covering the period of 2017–2021 are collected. The identification of secondary crashes is performed by the speed contour map method. The time and distance gaps between primary and secondary crashes are modeled using multiple 5-minute interval traffic variables as inputs. Multiple models are developed for benchmarking purposes, including PCA-LSTM, which incorporates principal component analysis (PCA) and LSTM, SSAE-SVM, which incorporates SSAE and support vector machine (SVM), and back propagation neural network (BPNN). The performance comparison indicates that the hybrid SSAE-LSTM model outperforms the other models in terms of both spatial and temporal prediction. In particular, SSAE4-LSTM1 (with 4 SSAE layers and 1 LSTM layer) demonstrates superior spatial prediction performance, while SSAE4-LSTM2 (with 4 SSAE layers and 2 LSTM layers) excels in temporal prediction. A joint spatio-temporal evaluation is also conducted to measure the overall accuracy of the optimal models over different permitted spatio-temporal ranges. Finally, practical suggestions are provided for secondary crash prevention.

Review of Vehicle Type Recognition Methods

With the booming social and economic development, the number of domestic and foreign motor vehicles has increased dramatically, resulting in increasing traffic flow, traffic congestion, and traffic safety problems. To better relieve traffic pressure, intelligent transportation has become the mainstream development direction and an important means of modern transportation, of which vehicle type recognition is the core component of intelligent transportation. Therefore, the research on vehicle identification is of great significance in both scientific research and real-life applications, and it is also a challenging task. Among the various detection and recognition methods, deep learning has been proved to be a more effective one, so this paper discusses the current research on deep learning and vehicle model recognition.

Effect evaluation of traffic guidance in urban underground road diverging and merging areas: A simulator study

Traffic accidents occur frequently in urban underground road diverging and merging areas due to the limited vision and complex traffic. Well-designed traffic visual guidance is one of the effective measures to alleviate the traffic safety problems in the diverging and merging areas of urban underground roads. In this study, four different integrated traffic guidance schemes (including signs, marking lines and sidewall guidance) were proposed and their effects on drivers' behaviour were investigated through driving simulator experiments and questionnaire survey. To investigate the influence of different schemes, eight variables about driving behaviour and guidance efficiency were assessed for analysis. Finally, a fuzzy comprehensive evaluation model based on analytic hierarchy process (FCE + AHP) was constructed to evaluate the effect of guidance schemes. Vehicle running state, driver operation behaviour and guidance efficiency were mainly considered. The guidance evaluation results obtained by the model were consistent with the conclusions of the driver subjective questionnaire. The results show that reasonable setting of white dotted lines and colour guidance can help drivers find exits quickly and improve driving stability. However, excessive combination of traffic guidance leads to information overload and produces the opposite effect. This study can provide a generic framework for the design and evaluation of traffic guidance facilities of urban underground roads.

Mandatory lane-changing modelling based on a game theoretic approach in traditional and connected environments

Abstract The paper proposes a model of mandatory lane-changing behaviour based on a non-cooperative game in a traditional environment and analyses its applicability in a connected environment. In order to solve the problem of traffic safety and traffic congestion caused by mandatory lane-changing on urban roads, this paper applies the non-cooperative game theory to describe the game behaviour of the two parties, the lane-changing vehicle and the vehicle behind the target lane, in the connected and traditional environments respectively, and constructs the model considering the safety gain, speed gain and lane-changing gain to obtain a game model and the Nash equilibrium solution. The model is calibrated and tested using NGSIM data, and the results of the study show that the model has a good performance for the decision behaviour of lane-changing vehicles and lag vehicles for mandatory lane-changing behaviour on urban roads.

Дослідження безпеки дорожнього руху у м. Тернополі

The article is devoted to the problem of researching road safety issues in the city of Ternopil with the structuring of established actual deficiencies according to the main indicators. As a result of the analysis of traffic flows in the morning period, the most problematic sections of the street and road network were identified. In general, it is observed that in the evening peak period, the speed of traffic flows on the street and road network is significantly lower than in the morning peak period. In order to analyze road traffic safety in the city of Ternopil, a cartographic method was used, which involves superimposing on the map data arrays regarding traffic accident statistics for 2018-2020. This approach makes it possible to determine the places of concentration of road accidents, however, during the analysis, it was found that road accidents in Ternopil mostly occur along the main streets without clearly defined places of concentration. In this regard, a conditional indicator of the danger of transport corridors of Ternopil was derived, which is determined by the ratio of the number of road accidents with victims to the total length of the street, which also allows analyzing the predominant location (clustering) of road accidents with victims in each district of the city. The current policy and practices of Ternopil in the field of road safety management need improvement. In the city, repair work is regularly carried out to maintain the roadway and technical equipment in proper condition, but the quality and volume of the work performed do not fully cover the need to ensure traffic safety and provide information to road users. In general, it can be stated that Ternopil is a city that is just starting proactive actions in the field of traffic safety ("starting city"). In this, it favorably differs from the vast majority of other regional centers, in which the problem of traffic safety is not even discussed so far, and consideration of this issue in terms of sustainable urban mobility of the Ternopil urban territorial community.

Research on Traffic sign recognition based on CNN Deep Learning Network

With the continuous development of social economy, the road traffic system as one of the basis of national economy is also increasingly developed, which is followed by the traffic safety problems are increasingly prominent. Among them, driving violations such as not obeying traffic signs are the main cause of traffic accidents. In this research, Traffic Sign Recognition (TSR) has become a hot research topic. The research status and application field of traffic sign detection and recognition technology are introduced and analyzed in detail, and the improvement of traffic sign database is introduced. After that, the application of CNN in image processing and traffic sign recognition is introduced, and the existing problems in traffic sign recognition are analyzed. The CNN deep learning network used in this paper can conduct training while identifying targets, effectively improve the recognition accuracy of traffic signs under complex natural conditions and reduce the time consumption.