Road safety management system optimization methodology

There are few studies on the violation of truck drivers, especially the hazmat truck driver, although truck driver's violation may cause serious casualties. This paper aims to investigate hazmat truck drivers' violation behavior and identify associated risk factors. Different data sources in intelligent transportation system (ITS) including hazmat transportation management system and traffic safety management system are extracted and emerged together. Three years (2016-2018) of violation data that comprised 11612 trip record in China are employed in this research. Based on Bayesian theory, this study proposes zero-inflated ordered probit (ZIOP) model and three alternative models to exploring the relationship between hazmat truck drivers' violation frequency and the key risk factors. The results show that ZIOP model can handle excessive zero observation problem of violation data properly and differentiate between `always-zero group' drivers and drivers who did not violate the traffic rules during research period but would do so in different surroundings. The results also indicate that the violation probability and the violation frequency level of hazmat truck drivers are influenced by driver characteristics, freight order attributes, and drivers' violation records. This research provides guidance for driving training and safety education of hazmat truck drivers, and will be helpful in building better driving simulation models.

In recent years, with the extending highway construction scale in mountain areas, there is lack of traffic safety facilities in some mountain areas. The problems of unreasonable and irregular traffic guarantee engineering construction stand out. Especially in rural highway in mountain areas with complex topography, the traffic accident rates are increasing, causing lots of dead and economic losses. Studying deeply on rural highway traffic safety problems in mountain areas and improving rural highway traffic safety level are the problems that we need to solve urgently. This essay analyzes the law of rural highway traffic accidents in mountain areas and makes a conclusion that the existing problems in rural highway safety managements in mountain areas at present. Based on this, this essay analyzes systematically the influent factors of rural highway traffic safety and a conclusion can be drew that the frequent rural highway traffic accidents in mountain areas not only are caused by bad line type for roads and no security arrangements are set. At last, based on macro-management level, it proposes a series of positive highway safety management countermeasures including strengthening traffic safety education, establishing traffic safety management system, improving passenger transport policy and management system, formulating dangerous sections inspection mechanisms.

Traffic safety system management

The main focal points of improving the traffic safety management system are as follows. First, one must coordinate the interaction among all functional branches, their structural divisions and subsidiaries involved in the transportation process, based on common approaches to managing processes related to traffic safety. Second, one should implement the approaches and requirements that are congruent with international standards; to maintain a positive level of traffic safety culture through awareness of the importance and social responsibility of the holding employees when performing work that affects traffic safety, with simultaneous integration of mandatory and strict rules of conduct in all production processes. Third, one is to improve the regulatory framework. Train traffic safety is ensured at all stages of the life cycle of rolling stock, traffic support systems and infrastructure elements. Nevertheless, failures and malfunctions are detected during the operation. This article presents one of the methods for increasing the train traffic safety in the automation and telemechanics system.

Using bus critical driving events as surrogate safety measures for pedestrian and bicycle crashes based on GPS trajectory data

From 3 lakh vehicles in 1985, to about 53 lakh now, vehicle population in Bangalore has increased more than five fold during the last two decades. While the vehicle population is growing by at least one lakh every year, total road length has remained the same. Many of the arterial roads and junctions are operating over the capacity and to upgrade the city's traffic management system and resulted in the creation of the Bangalore Traffic Improvement Project, B-TRAC 2010 by Bangalore City Traffic Police. The BTRAC Project was conceptualized to address traffic congestion in Bangalore by employing the latest traffic management technologies. The components of BTRAC which are a reality on ground include the state-of-the-art Traffic Management Center which is the hub of transportation management system in Bangalore, Intelligent Transport Systems, Surveillance and Enforcement Cameras, Signage, Road Markings, Street Furniture, Junction Improvements and Capacity Building. Various traffic and road safety education and training activities have also been conducted with citizens and traffic personnel throughout the city for generating awareness about traffic rules and familiarising them with the latest technologies being adapted. As a result of such consolidated traffic control and management effort, Bangalore today has a full-fledged traffic maintenance system. This has resulted in creating transparency in enforcing traffic rules and levying adequate and timely penalties. BTRAC has resulted in better management of traffic, ensuring safety and security on roads and prevention of road accidents, with the monitoring and regulation of flow of vehicles in a systematic manner. BTRAC has reduced the occurrence of road accidents in Bangalore and is creating a safe road environment for commuters. The absolute number of road accidents witnessed a growing trend till the year 2007 and then followed a declining trend over the consecutive years with 5230 cases being reported in 2013 and 5004 cases in 2014. Even the fatal accident rate is showing a declining trend over the past five years.

Real-time traffic management systems with integrated proactive decision support capabilities are expected to operate with ( a) limited prediction accuracy ( b) decision-making latency, and ( c) partial coverage of the managed area. Such deficiencies are difficult to avoid in most real-world traffic network management applications, and there is a need to quantify the effect of these deficiencies on the performance of traffic network management systems. This paper studies the effectiveness of a proactive traffic management system. Various levels of prediction accuracy of the traffic network state, decision-making latency, and partial area coverage are considered. A traffic management system that emulates real-time operations is developed. The system adopts a closed-loop rolling horizon framework, which integrates network state estimation and prediction modules as well as decision support capabilities. A set of simulation experiments considers a hypothetical highway network. The results show that the effectiveness of the traffic management system can be affected by the deficiencies. However, the impact could be smaller if these deficiencies are kept under certain levels.

Fuzzy Power Heronian function based CoCoSo method for the advantage prioritization of autonomous vehicles in real-time traffic management

A hybrid machine learning model for predicting Real-Time secondary crash likelihood

The frequency of road traffic accidents (RTAs) is higher in China than in other countries, and traffic safety is a more complex issue. Our study of RTA severity differences among 31 provinces in China identifies the most important traffic management issues in each province. Provinces with the highest RTA risk were identified from RTA mortality data for 31 provinces during 2004–2013. Then provinces with the highest risk according to mortality/per capita GDP, mortality/10,000 vehicles, and mortality/100,000 persons were determined to eliminate the effect of differences in economic development, vehicle numbers, and population on mortality rates. The results show that Guangdong, Zhejiang, Jiangsu, Shandong, Sichuan, Anhui, Fujian, and Hebei have the highest RTA risk in China. Tibet, Anhui, Guangxi, Qinghai, Sinkiang, Gansu, Zhejiang, and Guangdong have the highest risk trend. Thus, Anhui, Zhejiang, and Guangdong have both the highest RTA risk and the highest risk trend. We discuss environmental, road, vehicle, and human causes of RTAs for the province groups. Improving traffic management, strengthening the deterrent effect of legal penalties, and establishing a road safety culture could reduce RTAs in China.

The issues of optimizing management approaches for effective implementation of road traffic safety management systems in enterprises are considered. The authors examine internal and external factors affecting road safety and explore methods to enhance management approaches to ensure a high level of safety. Special attention is paid to process and risk-oriented approaches, as well as the importance of interaction with stakeholders. It is noted that a successful safety management strategy involves integrating safety into all areas of enterprise activities and continuously monitoring the system. Research confirms that adopting such a risk-oriented approach significantly enhances the effectiveness of road safety management systems. Reduction of risks and improvement of safety are the outcomes of implementing this strategy, enabling enterprises to more efficiently control and manage potential road hazards. Future research plans include focusing on developing new methods to assess the effectiveness of safety management systems, aimed at further improving the functionality and reliability of such systems. Additionally, there are plans to conduct a detailed study on the impact of innovative technologies on the functioning of road safety systems, to implement the most effective technical solutions. There are also plans to expand the application of safety management systems across various types of enterprises to ensure an optimal level of safety for a wide spectrum of road users. This may include not only transportation companies but also construction, logistics, and other industries involved in the transportation of goods and services. Taking into account the prospects of further research, it is expected that they will contribute to further improving road safety and ensuring stability for all road users, which is a crucial step in providing safety and comfort on highways.

Background: Road traffic accidents have been one of the main causes of death worldwide. However, most of the crashes are both predictable and preventable. With the widespread use, mobile phone is considered as a major road safety risk. However, varieties of apps have recently been developed for improving the road traffic health and safety. Despite an increasing trend of these apps, there is no comprehensive analysis of their features and no taxonomy or classification of them based on the traffic safety theories or frameworks. The aim of this study was to explore characteristics of available mobile apps on the road traffic health and safety and classify them based on the Haddon’s Matrix. Methods: To conduct this research, a comprehensive and systematic review of the mobile applications developed for the road traffic health and safety was carried out through using the qualitative content analysis. Google Play was searched through using a combination of the keywords to retrieve the road traffic apps. In order to extract the app features, their description was examined, and their content was analyzed. Then they were classified in four main categories including Road Traffic Health & safety, Road Traffic Training, Road traffic Navigation, and Other Road Traffic apps. Finally, the Haddon’s matrix was applied to analyze and classify those mobile apps residing in two main categories of the traffic health & safety, and the traffic training. Haddon’s matrix is a relevant framework for structured analyses of traffic injury events. In the Haddon’s matrix, the contributions of human, vehicle/equipment and environmental factors to the injuries in the three phases pre-crash, crash and post-crash has been presented. Results: In this study, 916 mobile apps met the inclusion criteria and were included in the final analysis.19 subcategories were identified for classifying the included apps based on their features and functionalities. In total, 620 of the mobile apps were grouped on the basis of Haddon’s matrix. About 61.76% of these apps were categorized as the traffic health & safety group. Among the subcategories of the traffic health & safety group, the highest number of apps (194) was the real-time traffic alerting apps. Behavior based feed-backing subcategory was ranked the second among the traffic health and safety apps with 75 apps. When the researchers applied factors and phases of Haddon’s framework for analyzing the apps, it was found that the Haddon’s factors have been taken into account in the apps grouped into two main categories of the apps including traffic training and traffic health & safety applications. The highest percentage of Haddon’s matrix factor considered for the intervention through the apps was related to the physical & social environment (23.69%) in the traffic training category. The features of 259 apps were classified in the Event/ Driving phase of Haddon’s matrix. Most of the apps in this phase was related to the real-time traffic alerting subgroup. These apps performed in real time while driving. The lowest number of the apps in driving phase was observed in the behavior based feed backing subcategory, which inform drivers about their driving behavior in real-time. Sixteen apps had features that categorized them in both Pre-event / Pre-driving and Event / Driving phases. In addition, 20 apps were found to have feature for intervening in both Event / Driving and Post-event / Post –driving phases. All 235 apps in the traffic training category were in pre-event/ pre-driving phase, which requires users to use these apps before driving. Conclusion: Applying Haddon’s matrix on analyzing and classifying the traffic health and safety apps revealed strengths and weaknesses of the existing related mobile apps in terms of the factors that must be considered for intervention toward prevention and reduction of road traffic accidents as the main public health issue.

There is an established consensus among traffic safety researchers that a nonlinear relationship exists between traffic exposure and safety. This relationship is reflected by the safety performance functions (SPFs) calibrated for various classes of roads and intersections. One of the main uses of SPFs is to identify locations with potential for accident reduction. While this application is certainly important, the use of SPFs provides no information related to the nature of the accident occurrence. Without being able to relate accident frequency and severity to roadway geometrics, traffic control devices, roadside features, roadway condition, driver behavior, or vehicle type, it is not possible to develop effective countermeasures. A methodology was developed to provide guidance in diagnostics of safety problems, recognition of accident patterns, and development of appropriate countermeasures. Considering that traffic accidents can be viewed as random Bernoulli trials, it is possible to detect deviation from the statistical process by computing observed cumulative probability for each of the accident characteristics. Detection of an accident pattern at an intersection suggests the presence of an element in the roadway environment that triggered a deviation from a random statistical process in the direction of reduced safety. Identification of such an element always provides a critical clue to accident causality.

Traffic safety is considered as one of the important problems in the development of cities. Thus, a reliable estimation of traffic safety is crucial to be proposed. As predicting outcome indicators, two relative indicators, accident rate per 10000 cars and accident rate per 10000 capita, are introduced in this paper. Based on the theory of support vector machine (SVM), the improved SVM models are proposed. To improve the efficiency of learning, the least support vector machine (LSSVM) is introduced; to improve the model's robustness further, the weighted least support vector machine (WLSSVM) is introduced. As an example, using the traffic safety data collected from 2006 to 2010, the models' effectiveness and feasibility were verified by comparing and analyzing.

This chapter reviews the International Civil Aviation Organization air traffic management (ATM) work programme along with ATM developments taking place around the world. It examines the various elements of the ATM system and suggests some of die research, trials and demonstrations. Airspace management is traditionally recognized mainly as involving a dynamic or tactical sharing of airspace by civil and military users. Air Traffic Services itself is comprised of several subelements, one of these being air traffic control. The increasing number of long-range interregional flights may require integration of regional Air Traffic Flow Management systems and procedures. Free Right is the guiding vision, mission and operational concept of the Federal Aviation Administration, based on Communications, Navigation, Surveillance/Air Traffic Management systems (CNS/ATM). Africa is composed of many delicate national economies separated by vast wilderness areas. The main scope of Airspace management will be toward a strategic planning function of airspace infrastructure, and flexibility of airspace use.