Efficiency Of Road Transport Research Articles

Research on Obstacle Avoidance Strategy of Automated Heavy Vehicle Platoon in High-Speed Scenarios

Amidst the rapid progression of the road transport industry, the safety and efficiency of heavy-vehicle platoons have garnered significant attention. The study tackles the challenge of obstacle avoidance presented by vehicles owing to their considerable mass, delayed response times, and line-of-sight impediments, by introducing a cooperative obstacle avoidance system for heavy-vehicle platoons based on deep reinforcement learning. The system comprises three primary modules: perception, decision-making, and control. Initially, the perception module acquires real-time environmental data. Subsequently, the decision-making module formulates obstacle avoidance decisions based on the acquired data. Specifically, it implements a two-stage braking obstacle avoidance strategy under low collision risk scenarios, while employing a fifth-degree polynomial for planning and tracking obstacle avoidance paths under high collision risk conditions suitable for steering maneuvers. The control module utilizes the local multi-agent deep deterministic policy gradient (LADDPG) algorithm to train the heavy-vehicle platoon agents, ensuring the formation’s maintenance while mitigating collisions with other vehicles and obstacles. The effectiveness of the proposed system is substantiated through simulation experiments, demonstrating its adaptability to various traffic conditions, selection of suitable obstacle avoidance strategies, and significant enhancement of obstacle avoidance performance and heavy-vehicle platoon stability.

Improving efficiency of road transport through the use of hydrodiodes in hydraulic systems taking into account cavitation phenomena

Introduction. One of the promising ways to reduce dynamic loads during operation of hydraulic crane manipulator installations is the use of hydrodiodes. In hydraulic systems operating at high speeds of the working fluid, cavitation phenomena may occur in the hydrodiode, which are accompanied by increased noise and vibration, and may lead to the destruction of the hydrodiode, which is not acceptable. The paper compares the results of calculating the flow of liquid in the flow part of a vortex hydrodiode, taking into account cavitation phenomena and without cavitation phenomena, with the results of research tests. The analysis of the effect of cavitation on the working processes in a vortex hydrodiode for crane manipulator installations is presented.Materials and method. Computational fluid dynamics (CFD) models using the FLUENT CFD code to study the working processes occurring in the working chamber of a vortex hydrodiode were developed. The commercial CFD code ANSYS FLUENT to simulate the flow of liquid in the flow part of a vortex hydrodiode was used.Results. The paper verifies the results of a numerical experiment with the results of research tests. A quantitative and qualitative analysis of the effect of cavitation on the working processes of a vortex hydrodiode has been carried out.Discussion and conclusion. It has been found that the values of pressure and diode in calculations taking into account cavitation and without cavitation practically do not differ, thus, the effect of cavitation at Reynolds numbers Re<30000 does not significantly affect the quantitative values of the parameters of the vortex hydrodiode and the cavitation calculation module can not be used. However, at higher values of the Reynolds numbers, cavitation appears in the working cavity of the vortex hydrodiode and the calculated values of the parameters of the hydrodiode without cavitation and taking cavitation into account differ significantly. Therefore, when calculating high-speed flows, it is necessary to use the cavitation calculation module. The analysis of the effect of cavitation on the working processes of a vortex hydrodiode showed that in the forward direction of the flow, cavitation does not significantly affect the parameters of the hydrodiode and the place of its formation, the upper inlet region of th tangential chamber. In the opposite direction of flow, cavitation has a significant effect on the pattern of fluid flow in the vortex hydrodiode. Cavitation covers almost the entire inlet volume of the radial tube and partially captures the central part of the vortex chamber

Lane Detection, Segmentation, Pothole Detection and Traffic Sign Recognition for ADAS

Lane detection, a critical aspect of advanced driver assistance systems (ADAS) and autonomous vehicles, is addressed in this work, combining classical computer vision methods with deep learning techniques. The proposed solution, utilizing a UNet-based model trained with TensorFlow and Keras, enhances vehicle perception for intelligent transportation systems. Integrated functionalities for pothole detection and traffic sign detection further contribute to safety and efficiency, enabling vehicles to identify road hazards and comply with regulations. The system encompasses data preprocessing, model training, and real-time video analysis, while a classical lane detection pipeline using OpenCV showcases various stages such as grayscale conversion, Gaussian blur, Canny edge detection, masking, Hough transform, and lane overlay. This comprehensive approach supports road safety, traffic management, and transportation efficiency initiatives, making significant strides in intelligent transportation systems and urban planning.

AUTOMATED DRIVING SYSTEMS: COMPARISON OF TRAINING METHODS’ EFFECTIVENESS

The second decade of the 21st century saw the introduction of vehicles equipped with various driver assistance systems. However, the producers' plans go much further. In January 2023, Mercedes-Benz's DRIVE PILOT system was approved for use on public roads in Nevada (United States) as the first and so far only SAE Level 3 series-production solution. Despite increasing automation, the human factor remains important for the safety and efficiency of road transport. In the coming years, and possibly decades, this will mainly be due to the co-existence of vehicles with varying degrees of automation and necessary driver-vehicle interactions in cases where an automated driving system crosses the boundaries of the operational design domain. The latest research reveals the limitations of driving assistance systems, pointing not only to the need for changes in the technological domain but also to the need to pay more attention to the psychological aspects of using assistance systems in cognitive and behavioral areas. Therefore, an additional element of automation implementation should be considered, which is driver training focused on modern technological solutions. Properly arranged and conducted training can be treated as an additional factor facilitating the implementation of automated mobility. The article describes the methods of assessing the effectiveness of training in terms of familiarizing drivers with the functions that automate driving. The authors present the results of tests carried out on a driving simulator with an implemented Level 4 system (according to SAE classification). Three forms of knowledge transfer were analyzed: practical training, e-learning, and training with a short user manual. The results were compared in terms of driver-vehicle interaction effectiveness (e.g., system activation), ensuring that the driver is sufficiently reactive in dangerous situations and understands the limitations of the system. The research was conducted on a group of 81 drivers aged 18–65. Driver training was one of the main pillars of the Trustonomy project, which received funding from the EU research and innovation program Horizon 2020 under grant agreement No. 815003.

Road Transport Efficiency and Organizational Performance: Does Traffic Infrastructure Management Matter?

The objective of this study is to assess the relationships between road transport efficiency and organizational performance. In addition, the investigation explored the intermediary function of traffic infrastructure management in the relationship between road transport efficiency and organizational performance. A study model was built, drawing on a resource-based approach and stakeholder theories, to investigate the interactions between the constructs. The data was collected from a sample of 30 logistics enterprises located in Ghana. The research model underwent analysis utilizing the partial least squares structural equation modeling technique. The results of the study indicate that there is a strong and statistically significant relationship between road transport efficiency and organizational performance. Once more, the analysis has demonstrated a favorable impact of traffic infrastructure management on the performance of organizations. Furthermore, the management of transportation infrastructure has shown a noteworthy and substantial role in mediating the impact on organizational performance.

An improved adaptive cruise control law

To increase the efficiency of road transport and reduce exhaust emissions, research has been intensified in assisted control systems, where adaptive cruise control (ACC) and cooperative adaptive cruise control (CACC) stand out. While ACC uses data from onboard sensors and radars, CACC also uses data from inter-vehicle wireless communication. In this context, this paper proposes a new control law for ACC systems that provides a competitive performance compared to CACC, despite not requiring wireless communication between vehicles. The new control law formulation employs both the vehicle acceleration and the relative speed, which generalizes similar ones. The design methodology formulated as a convex optimization problem ensures string and internal stability as well closed-loop pole placement if a set of linear matrix inequalities (LMIs) is satisfied. At the end of the paper, simulations demonstrate the effectiveness of the proposed methodology.

МЕТОДИКА ИНТЕГРАЦИИ ПРОИЗВОДСТВЕННО-ТЕХНИЧЕСКИХ БАЗ ОБСЛУЖИВАНИЯ И РЕМОНТА ВЕДОМСТВЕННЫХ АВТОМОБИЛЕЙ

The relevance of this study lies in the fact that motor transport services of federal ministries and departments of the Russian Federation, agencies subordinate to them, law enforcement and supervisory authorities are carried out by departmental road transport. The operation of departmental road transport in modern conditions is based on documents developed for public road transport. In some cases, departmental acts on the organization of the work of vehicles and personnel in relation to the functions and tasks of the relevant department are not systematically used. The operation of departmental road transport is characterized by excessive dispersion of regional production and technical bases for the maintenance, maintenance and repair of a specialized fleet, as a rule, assigned to individual institutions. As a result, more material and technical resources, rolling stock and personnel are involved in the transportation process of departmental road transport than at public road transport. Increasing the efficiency of departmental road transport consists in the consolidation and centralization of regional production and technical bases, as well as in rationing the resource provision of the transport process. The subject of the study is the regularities of the functioning of the production and technical bases units of the departmental structure. The purpose of this study is to increase the efficiency of departmental road transport operation due to the territorial integration of production and technical bases. To achieve this goal, it is necessary to solve a number of tasks, the specifics of which are determined by the features of a specialized departmental road transport on the example of the divisions of the regional Department of the Federal Penitentiary Service for the Rostov region, concluded: a) in the collection, grouping and processing of statistical information from divisions by type, model, number and costs of operation and performance of transportation in the field of transport by specialized rolling stock; b) determination by geographical coordinates of the location of divisions in the region; c) the compilation of an adjacent matrix of distances between divisions. The methodology of the study includes a methodology for the territorial integration of production and technical bases of regional units of departmental road transport based on the «center of gravity» method, taking into account the costs of operating a specialized fleet and determining the head production and technical bases. The obtained research results can be used for other departments, divisions, organizations and services of departmental structures in which a specialized fleet is involved.

Energy-Efficient Reactive and Predictive Connected Cruise Control

Connected and automated vehicles (CAVs) have shown great potential in improving the energy efficiency of road transportation. Energy savings, however, greatly depends on driving behavior. Therefore, the controllers of CAVs must be carefully designed to fully leverage the benefits of connectivity and automation, especially if CAVs travel amongst other non-connected and human-driven vehicles. With this as motivation, we introduce a framework for the longitudinal control of CAVs traveling in mixed traffic including connected and non-connected human-driven vehicles. Reactive and predictive connected cruise control strategies are proposed. Reactive controllers are given by explicit feedback control laws. Predictive controllers, on the other hand, optimize the control input in a receding-horizon fashion, by predicting the motions of preceding vehicles. Beyond-line-of-sight information obtained via vehicle-to-vehicle (V2V) communication is leveraged by the proposed reactive and predictive controllers. Simulations utilizing real traffic data show that connectivity can bring up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$30\%$</tex-math></inline-formula> energy savings in certain scenarios.

AN ASSESSMENT OF VEHICULAR TRAFFIC CONGESTION ALONG ABUJA-NASARAWA ROAD WITH EMPHASIS ON KARU BRIDGE TO AYA INTERCHANGE

Traffic congestion poses a substantial challenge to efficient road transportation, impacting travel times, fuel consumption, and overall productivity. The Abuja-Nasarawa Road, a critical transportation corridor, faces persistent congestion issues attributed to factors such as increased vehicle numbers, inadequate infrastructure, and poor traffic management. The escalating traffic congestion along Abuja-Nasarawa Road adversely affects the region's productivity and economic development. This study aims to analyze the traffic congestion along the Abuja-Nasarawa Road to improve decision-making regarding road use and transportation system planning. The research design combines qualitative and quantitative methods, utilizing a questionnaire and traffic data collection. The study focuses on the AYA Interchange – Karu Bridge section of the road, a critical stretch facing congestion issues. The methodology involves traffic data collection, including vehicle counts, traffic volumes, and average speeds. Results indicate varying traffic flow rates during morning and evening peak hours. Karu Bridge experiences the highest traffic congestion, with a flow rate of 5433 vehicles per hour during the morning. The qualitative analysis reveals the distribution of road users, with 40% being commercial drivers. The findings reveal a prevalence of traffic congestion attributed to the concentration of economic activities in the city center, leading to increased commuter influx. The study recommends measures such as maintaining and expanding the road network, introducing alternative transportation like a railway service, and completing infrastructure projects like the Apo-Karshi Road.

Comprehensive Analysis of Road Surface Irregularities: Cause, Effect and Mitigation Strategies

Abstract: The quality of road facilities is a critical measure of a nation's economic development and overall quality of life. In India, where road transportation is the strength of connectivity, the prevalence of road surface irregularities has emerged as a significant challenge. The present paper aims to systematically examine the multifaceted aspects of road surface irregularities in India. The study begins by providing an overview of the importance of road infrastructure in the Indian context and its insinuations for economic growth and societal well-being. It then delves into the various factors contributing to road surface irregularities, including construction materials, climatic conditions, and traffic volume and maintenance practices. Furthermore, the literature highlights the hostile heightened transportation costs Finally, this paper concludes with insights into the future prospects and challenges in managing effects of road surface irregularities on road users, such as increased accidents, vehicle tear and wear, and road surface irregularities in the Indian context, emphasizing the need for holistic approaches that integrate technological advancements, policy reforms, and sustainable practices to ensure safe and efficient road transportation. This paper serves as a comprehensive examination of the complexities surrounding road surface quality in India and provides valuable insights for policymakers, researchers, and practitioners working towards improving the nation's road infrastructure.

Evaluating the Annual Operational Efficiency of Passenger and Freight Road Transport in Serbia Through Entropy and TOPSIS Methods

Evaluating the Annual Operational Efficiency of Passenger and Freight Road Transport in Serbia Through Entropy and TOPSIS Methods

Leningrad's Transport Infrastructure and Socio-economic Changes in the Life of the City in the 1950s – 1960s.

The article considers urban road infrastructure as one of the factors of socio-economic everyday life of a person. Based on the materials of Leningrad in the 1950s – 1960s, it is studied how the city's transport system was influenced by the settlement of the city center, the reform of working hours and population growth, the problems faced by the city's transport network and the mechanisms for their solution are demonstrated. The degree of effectiveness of overcoming the existing problems in the road and logistics infrastructure of the city is being clarified. Historical-genetic, historical-comparative and retrospective methods are used to solve the tasks set in the article. The analysis carried out in the article demonstrated that despite the considerable efforts of the city authorities, they failed to create an efficient road transport network. The desire of the federal and municipal authorities of Russia to resolve this issue, quite often in cities with a million population does not lead to the desired result. Conducted on the materials of Leningrad 1950 - 1960s, historical analysis shows that, in solving this problem, it is necessary to take into account many factors, both demographic and social. But even under these conditions, as the historical experience of Leningrad showed, when the city authorities made significant efforts to create an extensive road and transport network, logistical problems were not overcome. Therefore, historical experience and modern realities indicate the need to develop new, more effective theoretical models for organizing the movement of the city's population.

Green road transportation management and environmental sustainability: The impact of population density

The objective of the study is to examine the moderating role of population density in the relation between road transportation and environment sustainability of South Asian countries from 1990 to 2014. The study uses environment sustainability (population density) as the outcome (moderator), whereas road infrastructure, road density, energy intensity and transportation energy consumption are explanatory variables. The selection of these variables is motivated by their significance in understanding the relationship between road transportation and environmental sustainability. Road infrastructure and road density capture the physical aspects of transportation systems, while energy intensity and road transportation energy consumption provide insights into the energy efficiency and environmental impact of road transport, respectively. The findings show that a positive impact of road infrastructure and road density exists on environmental sustainability. There is contrarily a negative effect of road transportation energy consumption and energy intensity on environmental sustainability. Population density also harms environmental sustainability. When population density is used as a moderator between road transportation energy consumption, energy intensity and environment sustainability, it increases the coefficients of both energy intensity and road transportation energy consumption, which shows that population density plays an enhancing role between road transportation energy consumption, energy intensity and environment sustainability. The coefficients of road density and road infrastructure changed into a negative from a positive in the presence of population density as a moderator, which states that population density plays an antagonistic role between road density and environmental sustainability. We recommend prioritizing sustainable transportation solutions and policies in densely populated areas. Implementing measures such as promoting public transportation and electric vehicles, and investing in infrastructure that supports active transportation modes like cycling and walking can help mitigate the negative environmental effects of transportation while addressing the challenges posed by population density.

A Taxonomy and Analysis of Misbehaviour Detection in Cooperative Intelligent Transport Systems: A Systematic Review

Cooperative Intelligent Transport Systems (C-ITS) is one of the proposed solutions to improve the safety and efficiency of road transport. However, C-ITS is prone to misbehaviours that can cause devastating effects such as road accidents and potential loss of life. While there are several research studies including technical studies and surveys that discuss misbehaviour detection in C-ITS, they tend to focus on specific aspects of misbehaviour detection and do not provide a comprehensive and unified coverage. With the objective of serving as a reference for future researchers, this study provides a comprehensive survey of misbehaviour detection in C-ITS. It identifies and discusses the key causes of misbehaviour in C-ITS, and the mechanisms used to detect them. Additionally, it proposes a thematic taxonomy on misbehaviour detection based on a comparative analysis of the technical studies. Furthermore, the existing solutions from the state-of-the-art and their shortcomings are also presented. Finally, this study highlights several significant research challenges and discusses future research directions in the area of misbehaviour detection in C-ITS. In doing so, this study contributes to the existing literature in an important field of study.

Raising security of first responders with C-ITS?

Abstract This article recommends social science research-based recommendations for improving first responder safety and occupational health by assessing cooperative intelligent transport systems (C-ITS) for use by emergency services and law enforcement. This involves vehicles using digital technologies to inform each other or via objects such as roadworks signs about traffic situations and dangerous circumstances. The application of information and communication technologies to the road transport sector and its interfaces with other modes of transport shall make a significant contribution to improving environmental performance, efficiency, including energy efficiency, safety, and security of road transport. This article investigates which social science aspects must be considered when implementing C-ITS, so that emergency vehicles such as ambulances can be given automated priority. Since emergency vehicles can communicate with traffic signal systems or other vehicles, safety requirements play a particularly important role. This leads to the question of which challenges subjective safety and technology perceptions regarding first responders are essential for the introduction of C-ITS for first responder organizations and which factors can lead to rejection.

Mitigation strategies for controlling urban particulate pollution from traffic congestion: Road expansion and road public transport

The mismatch between urban transportation demands and local transportation supplies in municipal regions may cause serious traffic congestion and high vehicle exhaust emissions (VEEs). Although it has been found that road expansion and the provision of road public transport can mitigate traffic congestion and VEEs, the effectiveness of these public strategies in alleviating traffic congestion-related VEEs has been empirically compared in few studies. With the use of a panel dataset for 260 prefecture-level cities in China from 2013 to 2018, we fill this gap via empirically examining the effects of several popular strategies that promote the efficiency of urban road transportation, including road expansion and road public transport provision, on urban air pollution of fine particulate matter (PM2.5). Then we further investigate metrics measured by passenger and freight volumes based on local urban road coverage that can suitably reflect the mismatch degree between local transportation demands and supplies. The empirical results indicated a positive and statistically significant correlation between urban PM2.5 levels and road expansion but not between PM2.5 levels and road public transport, suggesting that road expansion may unintentionally increase the transportation volume and thus local PM2.5 levels. Importantly, we found that the passenger and freight volumes per unit road length are negatively and significantly correlated with the local particulate pollution concentration across different model specifications, while the passenger and freight volumes of road transportation do not directly affect local PM2.5 levels. We also employed a series of robustness tests to overcome the concerns associated with measurement errors, omitted variable biases, model misspecifications and endogeneity, and consistent results were obtained. These results indicated that when facing limited public budgets, the passenger and freight volumes per unit road length should be considered to measure the effectiveness of road infrastructure investments in alleviating local particulate pollution caused by traffic congestion.

Game Model of Optimal Quality Experience Strategy for Internet of Vehicles Bandwidth Service Based on DAG Blockchain

With the rapid development of the Internet of Vehicles (IoV), vehicle networks will generate large amounts of data. Vehicle-to-Vehicle (V2V) data sharing can improve driving experience and quality of service, and Vehicle-to-Roadside unit (V2R) communication can improve road transport efficiency. A certain amount of bandwidth is consumed in the process of data sharing between V2V and V2R, and when multiple vehicles request data from the RSU at the same time, there may be network delay or congestion. Therefore, the vehicle obtains data faster by requesting high bandwidth from the RSU. However, since the bandwidth resources of RSUs are limited, optimal bandwidth service strategies need to be investigated. In addition, in order to ensure the safety, efficiency and traceability of data sharing between V2V and V2R, a blockchain-supported IoV needs to be established. Therefore, we design a blockchain-based framework for V2V and V2R transaction framework that integrates DAG blockchain and modern cryptography. The framework ensures security and scalability during the execution of data exchange and completion of bandwidth transactions, improves the service quality of vehicles and realizes decentralized payment. In this work, a two-stage Stackelberg game is established under two pricing schemes of uniform pricing and discriminatory pricing to jointly maximize the benefits of vehicles and RSUs. In Stage I, the RSU sets the corresponding bandwidth service and pricing strategy. In Stage II, the vehicle decides the service demand according to the observed pricing strategy. The optimal bandwidth allocation and pricing strategy between the RSU and the vehicle is determined through the game of both parties, and the existence and uniqueness of the two-stage subgame Nash equilibrium is analyzed by applying backward induction. The correctness of the model is verified by experiments, and the comparative analysis shows that the proposed model has high throughput.

Towards autonomous inland waterway vessels — a comprehensive analysis of regulatory, liability and insurance frameworks

The use of maritime autonomous vessels for the inland waterway (IWW) transport can revolutionise the current logistics supply chain and enable the shifting of the cargo transportation from the less efficient road and rail transport modes. However, the lack of guidelines and requirements for the operation and testing of autonomous vessels must be addressed to enable autonomous operations. This study aims to identify the gaps of the prevailing regulatory, liability and insurance frameworks and propose viable recommendations for the operation and testing of the autonomous IWW vessels. The theoretical case study of a next-generation autonomous ship operating in European IWW along with the required key enabling technologies is considered. A systematic methodological approach is followed focusing on the existing, transition and next-generation stages for developing autonomous vessels. The existing stage deals with classifying the identified gaps considering the categories of high, moderate or low severity, whereas the anticipated new stakeholders with associated risks in the context of autonomous vessels are analysed. The transition stage discusses recommendations to mitigate the identified gaps of the analysed existing frameworks by either developing interpretations, amending existing instruments or proposing new instruments. The proposed recommendations demonstrate a pathway towards upgrading the existing frameworks based on the identified severity levels and hence are expected to be beneficial for the policymakers whilst preparing the roadmap for the design and operation of next-generation autonomous ship (NGAS).

Intelligent, In-Vehicle Autonomous Decision-Making Functionality for Driving Style Reconfigurations

Intelligent connected vehicles (ICVs) constitute a transformative technology attracting immense research effort and holding great promise in providing road safety, transport efficiency, driving comfort, and eco-friendly mobility. As the driving environment becomes more and more “connected”, the manner in which an ICV is driven (driving style) can dynamically vary from time to time, due to the change in several parameters associated with personal traits and with the ICV’s surroundings. This necessitates fast and effective decisions to be made for a priori identifying the most appropriate driving style for an ICV. Accordingly, the main goal of this study is to present a novel, in-vehicle autonomous decision-making functionality, which enables ICVs to dynamically, transparently, and securely utilize the best available driving style (DS). The proposed functionality takes as input several parameters related to the driver’s personal characteristics and preferences, as well as the changing driving environment. A Naive Bayes learning classifier is applied for the cognitive nature of the presented functionality. Three scenarios, with regards to drivers with different personal preferences and to driving scenes with changing environment situations, are illustrated, showcasing the effectiveness of the proposed functionality.

Measurement-Based Analysis on Vehicle-to-Vehicle Connectivity in Tunnel Environment

Vehicular ad hoc network (VANET) brings an excellent solution to ensure road safety and transportation efficiency in critical environment like tunnel. Particularly, radio link connectivity of vehicle-to-vehicle (V2V) significantly influences the performance of VANETs. The communication range of the radio systems is a random variable in reality due to the channel fading effect. Therefore, the connectivity model between vehicles in realistic environment is a key for accurate evaluation of system performances. In this paper, we study the V2V connectivity performance in the presence of channel randomness for tunnel environment. Firstly, based on channel measurement campaign, empirical path loss (PL) and small-scale fading channel models are established. Secondly, we study the influence of large-scale fading parameters on V2V connectivity. Thirdly, based on real small-scale fading characteristics, we derive the V2V connectivity probability between any two vehicles under Nakagami fading channel for one-dimensional VANET, and give the closed-form of V2V connectivity probability. Finally, we study the influences of various parameters (i.e., Nakagami fading factor, vehicle density, and neighbor order) on V2V connectivity performance. Results show that with the Nakagami fading shape factor increases, the connectivity probability increases. The shadowing fading can improve connectivity in the VANET; the path loss exponent, transmission distance, and signal-to-noise ratio (SNR) threshold have a negative impact on connectivity probability. The transmit power, vehicle density, and path loss threshold value have a positive impact on connectivity.