Analysis of the Impact of Road Traffic Safety Facilities on Traffic Safety

The development of the national economy is closely tied to infrastructure construction.In recent years,China has seen a significant increase in the number and scale of road construction projects,aimed at facilitating the flow of goods and enabling convenient travel for the masses.However,this surge in road construction also raises concerns about road traffic safety.Road traffic safety facilities play a crucial role in warning and protecting against traffic accidents.To ensure their effective implementation,this paper analyzes the essence of road traffic facilities and their impact on traffic safety.By identifying challenges in the application of traffic safety facilities and adhering to safety facility application principles,suggestions are proposed to enhance traffic safety management.

Impact of countdown signals on traffic safety and efficiency:a review and proposal

Countdown signals for motorized vehicles,which are intended to ensure safety on the road and regulate motor vehicle speed limits at road intersections,are still considered a relatively novel concept.These signals have been adopted by only a few countries,and the number of cities that use them is limited.This review aims to summarize the effects of countdown signals on traffic safety and efficiency and to determine the consistency and differences of existing research propositions on the matter.Based on the review,considerable research presents evidently different conclusions in the areas of driver red-light running and traffic safety.Particularly,some studies propose that countdown signals reinforce traffic safety,whereas others consider that such signals adversely affect traffic safety.Meanwhile,related literature provides varying conclusions on the aspect of traffic efficiency for vehicle headway.At present,the number of studies conducted regarding the driving behaviors of motorists toward countdown-signalized intersections is insufficient.Accordingly,such inadequate diversity in research causes difficulty in completely assessing the benefits and disadvantages of countdown signals.In this paper,an important future research direction on microcosmic driving psychological and physiological data combined with macro-driving behavior is proposed.

Research on Traffic Safety at Tunnel Entrance and Exit

Highway tunnel entrances have a high rate of expressway traffic accidents.In this paper,the reasons for the high incidence of traffic accidents at highway tunnel entrances are analyzed in detail,and corresponding solutions are proposed,hoping to provide some reference to relevant parties.

Order Exponential Evaluation Model for Road Traffic Safety in City Clusters

This study presents an order exponential model for estimating road traffic safety in city clusters.The proposed model introduces the traffic flow intrinsic properties and uses the characteristics and regular patterns of traffic development to identify road traffic safety levels in city clusters.Additionally,an evaluation index system of city cluster road traffic safety was constructed based on the spatial and temporal distribution.Then Order Exponential Evaluation Model(OEEM),a comprehensive model using order exponent function for road traffic safety evaluation,was put forward,which considers the main characteristics and the generation process of traffic accidents.The model effectively controlled the unsafe behavior of the traffic system.It could define the levels of city cluster road traffic safety and dynamically detect road safety risk.The proposed model was verified with statistical data from three Chinese city clusters by comparing the common model for road traffic safety with an ideal model.The results indicate that the order exponent approach undertaken in this study can be extended and applied to other research topics and fields.

Assessment of Traffic Safety State of Ship Based on Unascertained Measure

Using the theory and method of unascertained measure, an unascertained measure model and the related confidence rule are established to assess the safety state of ship. Thus, the dangerous factors in the hull system can be identified, and the accident possibility, loss, and injury degree can be forcasted. An application result shows that the the proposed method is effective in assessment of the traffic safety of ships, and it is more simple in computation than the fuzzy synthetic evaluation method. The proposed method can provide a scientific basis for realizing shipping transportation security and formulating preventive measures.

Research on Highway Traffic Safety and Facility Optimization

Traffic safety is one of the problems that need to be addressed in the construction and development of expressway.The key content of the design of traffic safety facilities is optimizing traffic safety facilities to reduce the probability of traffic safety accidents.Based on the analysis of highway safety facilities design optimization requirements,this paper puts forward the corresponding optimization measures,and explores the innovation of safety facilities design,in hopes of providing reference for the design of highway safety facilities.

Analysis of the Relations between Highway Geometric Design and Traffic Safety in Bangladesh,China,and America

Transportation plays a critical role in the economic sector in Bangladesh.Since its independence,infrastructure has been developing rapidly,includ-ing land,water,and air transportation.National economy is increasing at a relatively high rate,leading to the better-off of people’s lives.As the living standards keep improving,people are more concerned about safety issues in transportation.This article makes an analysis of the status quo of traffic safety in Bangladesh and compares the Bangladeshi code with American code AASHTO from the geometric aspects of horizontal and vertical align-ment,in an effort to provide reference to the highway design in Bangla-desh.Through a reasonable design,the traffic safety will be under control and accident rate as well as economic loss will be minimized.

Analysis of Traffic Accidents in Vietnam

Understanding the causes and solutions of road traffic accidents is important for developing road and action plans in a country. In Vietnam, awareness of traffic participants is the main cause of serious traffic accidents. In recent years, the number of road traffic accidents in Tuyen Quang province with deaths has decreased, but the number of accidents has increased significantly. The article uses data on traffic accidents in Tuyen Quang over the (2016-2023) has been analytically reviewed. From there, analyze accident characteristics and causes of traffic accidents in Tuyen Quang province, and propose solutions to improve traffic safety in Tuyen Quang, Vietnam. The findings can be information for managers and researchers interested in studying the province of Tuyen Quang, Vietnam road traffic safety. Additionally, the findings have led the government to achieve national targets in reducing the number of accidents and serious injuries.

Uncovering the influence of ChatGPT's prompts on traffic safety information using text mining approach

ChatGPT has emerged as a promising advanced large language model that needs prompt to gain information.However,designing a good prompt is not an easy task for many end-users.Therefore,this study intends to determine the amount of information gained because of varied amounts of information in the prompt.This study used two types of prompts,initial and improved,to query the introduction sections of 327 highly cited articles on traffic safety.The queried introduction sections were then matched with the corresponding human-written introduction sections from the same articles.Similarity tests and text network analysis were used to understand the level of similarities and the content of ChatGPT-generated and human-written introductions.The findings indicate the improved prompts,which have the addition of generic persona and information about the citations and references,changed the ChatGPT's output insignificantly.While the perfect similar contents are supposed to have a 1.0 similarity score,the initial and improved prompt's introduction materials have average similarity scores of 0.5387 and 0.5567,respectively.Further,the content analysis revealed that themes such as statistics,trends,safety measures,and safety technologies are more likely to have high similarity scores,irrespective of the amount of information provided in the prompt.On the other hand,themes such as human behavior,policy and regulations,public perception,and emerging technologies require a detailed level of information in their prompt to produce materials that are close to human-written materials.The prompt engineers can use the findings to evaluate their outputs and improve their prompting skills.

Potential Application of iRap for Road Safety Assessment under Mixed Traffic Condition Case Study: Le Van Viet Street in Ho Chi Minh City

Road transport safety policies have emphasized road infrastructure safety design and engineering as a core function.However,in developing countries like Vietnam,this approach has been slower to adopt,resulting in substandard roads.In-depth studies of accident locations indicate that road environment factors contribute significantly to road accidents in Vietnam and road design features are associated with specific accident types and hazards.Proactive and reactive approaches,such as road safety audit,inspection,assessment,and treatment of hazardous locations,are necessary to ensure that the road and its environment are safe.This paper provides an overview of road safety in Vietnam in general,and Ho Chi Minh in particular,including its factors and characteristics,as well as road infrastructure safety improvements.The iRap tool for road safety inspection and assessment is highlighted as a potential method for systematically analyzing road infrastructure deficiencies and providing targeted countermeasures to improve road safety under mixed traffic conditions.

A Multilayer Perceptron Artificial Neural Network Study of Fatal Road Traffic Crashes

This paper examines the relationship between fatal road traffic accidents and potential predictors using multilayer perceptron artificial neural network (MLANN) models. The initial analysis employed twelve potential predictors, including traffic volume, prevailing weather conditions, roadway characteristics and features, drivers’ age and gender, and number of lanes. Based on the output of the model and the variables’ importance factors, seven significant variables are identified and used for further analysis to improve the performance of models. The model is optimized by systematically changing the parameters, including the number of hidden layers and the activation function of both the hidden and output layers. The performances of the MLANN models are evaluated using the percentage of the achieved accuracy, R-squared, and Sum of Square Error (SSE) functions.

Analysis of Traffic Accidents Based on the Integration Model

To enhance the safety of road traffic operations,this paper proposed a model based on stacking integrated learning utilizing American road traffic accident statistics.Initially,the process involved data cleaning,transformation,and normalization.Subsequently,various classification models were constructed,including logistic regression,k-nearest neighbors,gradient boosting,decision trees,AdaBoost,and extra trees models.Evaluation metrics such as accuracy,precision,recall,F1 score,and Hamming loss were employed.Upon analysis,the passive-aggressive classifier model exhibited superior comprehensive indices compared to other models.Based on the model’s output results,an in-depth examination of the factors influencing traffic accidents was conducted.Additionally,measures and suggestions aimed at reducing the incidence of severe traffic accidents were presented.These findings served as a valuable reference for mitigating the occurrence of traffic accidents.

The modifiable areal unit problem in traffic safety:Basic issue, potential solutions and future research

This study fully addressed the modifiable areal unit problem （MAUP） that was well-known in geography but generally ignored by safety analysis. The basic issue of MAUP was introduced firstly with a case study to explicitly demonstrate the existence of the problem in macro level crash modeling, and then four potential strategies, i.e., using disaggregate data as possible, capturing spatial non-stationarity, designing optimal zoning systems, conducting sensitivity analysis to report the scope and magnitude of MAUP, were proposed and illustrated in an integrated way, followed by the future research directions. Results revealed that more efforts are desired to calibrate the state-of-art modeling technique at various levels of aggregation based on spatial homogeneity in traffic safety, transport characteristics, and demographical factors. The awareness of this problem in traffic safety domain is expected to the delineation of basic spatial units （e.g. the traffic safety analysis zones）, as well as to provide new insights into the nature of MAUP in statistics and geography.

Exploring traffic safety climate with driving condition and driving behaviour:a random parameter structural equation model approach

This study aimed to explore traffic safety climate by quantifying driving conditions and driving behaviour.To achieve the objective,the random parameter structural equation model was proposed so that driver action and driving condition can address the safety climate by integrating crash features,vehicle profiles,roadway conditions and environment conditions.The geo-localized crash open data of Las Vegas metropolitan area were collected from 2014 to 2016,including 27 arterials with 16827 injury samples.By quantifying the driving conditions and driving actions,the random parameter structural equation model was built up with measurement variables and latent variables.Results revealed that the random parameter structural equation model can address traffic safety climate quantitatively,while driving conditions and driving actions were quantified and reflected by vehicles,road environment and crash features correspondingly.The findings provide potential insights for practitioners and policy makers to improve the driving environment and traffic safety culture.

Short-term traffic safety forecasting using Gaussian mixture model and Kalman filter

In this paper,a prediction model is developed that combines a Gaussian mixture model(GMM) and a Kalman filter for online forecasting of traffic safety on expressways.Raw time-to-collision(TTC) samples are divided into two categories:those representing vehicles in risky situations and those in safe situations.Then,the GMM is used to model the bimodal distribution of the TTC samples,and the maximum likelihood(ML) estimation parameters of the TTC distribution are obtained using the expectation-maximization(EM) algorithm.We propose a new traffic safety indicator,named the proportion of exposure to traffic conflicts(PETTC),for assessing the risk and predicting the safety of expressway traffic.A Kalman filter is applied to forecast the short-term safety indicator,PETTC,and solves the online safety prediction problem.A dataset collected from four different expressway locations is used for performance estimation.The test results demonstrate the precision and robustness of the prediction model under different traffic conditions and using different datasets.These results could help decision-makers to improve their online traffic safety forecasting and enable the optimal operation of expressway traffic management systems.

Impact of connected and autonomous vehicles on traffic safety of mixed traffic flow:from the perspective of connectivity and spatial distribution

Equipped with high driving automation and advanced communication technologies, connected and autonomous vehicles (CAV) areexpected to possess a shorter reaction time and a wider vision,which are promising to improve traffic safety and efficiency. However,little attention has been paid to the effect of connectivity and spatial distribution on the safety performance of mixed traffic flow. Inthis paper, we attempt to investigate the impact of CAV on traffic safety considering these factors. To this end, a car-following modelfor CAV is proposed first. Then, the cooperative driving strategy for CAVs is designed. Precisely, the feedback gains of the informationare adjusted in real-time and are designed based on the derived stability criterion of the mixed traffic flow. Microscopic simulations ofmixed traffic flow in traffic oscillation are designed and conducted to explore how the distribution and connectivity of CAV affect thesafety performance ofmixed traffic flow. Simulation results show that increasing the penetration rate of CAV is promising to shift thesafety performance ofmixed traffic flow. In addition, the safety performance of mixed traffic flow is related to the spatial distributionand communication range of CAV. Besides, increasing communication range does not inevitably improve the safety performance ofmixed traffic flow when the penetration rate of CAV is low. Moreover, it is also found from the spatial–temporal trajectory of themixedtraffic flow that introducing CAV can mitigate the propagation of the stop-and-go wave and increase the throughput.

Optimization of depreciation subsidy policy strategies for electric two-wheelers for improving traffic safety

To improve the traffic safety of electric two-wheelers(ETW),China has promulgated ETW standardization policies.This policy requires local governments to take measures to guide the illegal ETWs out of use.Governments have implemented a depreciation subsidy scheme to encourage users to scrap illegal ETWs early.When designing the subsidy scheme,effectively improving the ETWs’traffic safety at the road network level while saving government expenses is essential for the sustainable implementation of the policy.This study proposes an optimization method for depreciation subsidy design incorporating traffic safety evaluation.Based on the policy scheme,this study formulates a risk assessment model for the ETW traffic network to characterize the effect of the subsidy on improving safety.Then,we use the bi-level programming approach to model the subsidy strategy design problem.The upper-level problem reflects the goal of policymakers to maximize safety improvement and minimize government expenses.The lower-level problem describes the route choices of ETW users.The optimal subsidy design under different safety-expense trade-offs is analysed based on the Nguyen and Dupuis network and a real network extracted from Changsha City in China.The results show that specific subsidy schemes effectively improve road safety without a large government spending.When themarket price or service life of ETWs increases,the government spending on the same safety goal increases.The government should comprehensively consider the safety effect of financial expense and the situation of the local ETW market before selecting reasonable subsidy strategies.

Will Banning Begging Improve Traffic Safety?

On August 2,Zhuhai,a city in south China’s Guangdong Province, issued road safety regulations banning begging in vehicle lanes. The new regulations allow the police to impose fines on beggers.Drivers who buy anything from vendors or give money to beg- gars will also be fined.

Overview of the identification of traffic accident-prone locations driven by big data

Effective identification of traffic accident-prone points can reduce accident risks and eliminate safety hazards.This paper first systematically compares the research in Chinese and foreign literature,and proposes three types of identification indicators,namely absolute,relative and comprehensive,according to different reference standards.According to the evaluation indicators and modelling methods,the current status of research and problems in identification theory and methods are systematically summarised in terms of mathematical statistics,cluster analysis,machine learning and conflict technology.The study shows that the foreign literature focuses on the innovation of data and indicators and changes from accident point safety management to road network safety management,while the research in Chinese literature focuses on the integration of multiple identification methods and theoretical innovation.Driven by big data,the identification of traffic accident-prone points has been further developed at the meso-micro scale.Morphological image processing methods are widely used,combined with GIS platforms,to accurately mine the spatial attributes and correlations of accidents.Also,considering the spatial and temporal distribution of accidents,the identification results are also transformed from regions to specific road sections and points to achieve more accurate identification.

Road Traffic Accident Patterns and Safety Policies Suggestions in Ho Chi Minh City

Although the number of road traffic accidents,fatalities,injuries has been slightly reduced in recent years,HCMC(Ho Chi Minh City)would still face challenges in reducing and restraining road traffic accidents in the future.This paper presents the results of road traffic accident data analysis over the past 3 years that we collected from the Road-Railway Police Bureau in HCMC.Based on the results,we could be able to deeply understand trends,characteristics,and causes of road traffic accidents.Such a deep understanding is a scientific basis to study and formulate synchronous strategy along with specific solutions to solve road traffic accident problems more effectively in the future.