Different Kinds Of Vehicles Research Articles

Vehicle Accident Detection and Notification System

As it is observed these days, the roads are crowded with different kinds of vehicles, and as a result, accidents have become more dangerous every day. In this paper, a vehicle accident detection and notification system is designed by using road surveillance camera data and machine learning techniques to use the recorded footage from the surveillance cameras to detect the accident status, activate an alerting sound, and send the notification message as a Google email (Gmail) to the specialist. The system model was made by combining two algorithms, convolutional neural networks (CNN) and support vector machines (SVM), to make a CNN-SVM hybrid model, which was then trained using two datasets. The first dataset contains 4814 images with sizes (28, 28) and extensions (jpg), and the second dataset contains 990 images with sizes (32, 32) and extensions (jpg). The outcomes scores of the evaluation matrices are: accuracy for the first dataset is 99.74% and loss is 1.14%, and for the second dataset, accuracy is 98.88% and loss is 3.39%. When testing it with real-world data, it achieved its objectives in 30 seconds, with accuracy reaching 100%.

Generic Framework for Vehicle Identification System with Deep Learning Models

In contemporary vehicle scenario, different kinds of vehicles are playing vital role for the customers. Day by day, vehicles are increasing with different properties and identifications. Monitoring and maintain the records of vehicles in digital platform is the challenging task as well as a crucial task for the countries. Here, we have to take the scenario of digitalization of vehicles with deep learning network models for identification and maneuvering process. In our country, different states are following multiple vehicle identification like numbering, coloring and imaging. Many researchers were contributing towards this identification mechanism like supervised, unsupervised models for getting optimum accuracy. Text and Image classification are not sufficient to solve this vehicle identification problem. We are incorporating text, image and video related unstructured data set to solve this problem. We have framed a generic architecture for all kind of vehicles analyze the data. For instance, a vehicle is moving towards CCTV camera and it has been recorded as video content. In this paper, we come across video to still pictures and image segmentation and all the identification parameters like White, Yellow and green. We performed both text classification and image classification algorithms to acquire effective result compared to existing algorithms. Bi Directional RNN (LSTM/GRU) and LeNet, Alex Net, Inception, VggNet and ResNet algorithms are analyzed for this entire process. This is one of the globally challenging scenarios for identification with feature extraction, data cleaning and processing. At the end of the result, we achieved 98.94 % accuracy compare than other existing systems.

Monitoring climatic impacts on the moisture uptake of the first Swiss wildlife bridge made of wood

Wildlife bridges represent a major component of any sustainable strategy to counteract the negative consequences of cutting the natural habitat of wildlife into disconnected parts by motorways and rail. This is especially true for a small and densely populated country such as Switzerland with diverse wildlife scattered through its territory. Up to now all wildlife bridges in Switzerland have been made of concrete with steel reinforcement. The wildlife bridge under investigation here is the first one in Switzerland made of wood-based materials. The idea of building a wildlife bridge by using wood-based materials represents besides a challenging technological endeavor also an ecological progress regarding embodied energy. A further advantage which resulted after realizing the construction, was the short interruption time it needed for installation on a motorway in operation. The most urgent question with respect to the wood-based elements is their moisture uptake when subjected to weather conditions. The present paper reports on a long-term monitoring of this wooden wildlife bridge over a period of approximately 2 years. Different kind of sensors, data from a nearby meteorological station, data regarding hourly number of different kind of vehicles passing beneath the wildlife bridge as well as lab measurements have been used to enable a robust and reliable statement on wooden wildlife bridges subjected to Swiss flatland weather conditions.

An extended PSO algorithm for cold-chain vehicle routing problem with independent loading and minimum fuel volume

With the increasing complexity of the distribution environment, customers usually propose higher requirements, such as independent loading of local and foreign cold-chain items in the event of an emergency. Moreover, minimum fuel volume plays an important role in the process of transportation with different speeds and different kinds of vehicles. In this paper, we present a new mathematical model to characterize cold-chain vehicle routing optimization with independent loading of local and foreign items and minimum fuel volume. To address the above mathematical model, an extended particle swarm optimization (PSO) algorithm is proposed by combining original PSO with 2-opt optimization to improve diversity and reduce convergence speed. Six sets of experiments are set to verify the practical performance and stability of the extended PSO algorithm based on three standard datasets of C201, R201, and RC201 from Solomon.

License plate classification based on MobileNetV2

In China, there are various colors of license plates which represent different kinds of vehicles and we construct a model on Edge Impulse platform to deal with problems in actual engineering programs like parking, traffic flow control, city planning, etc. Lots of researchers have proposed different techniques about license plate classification but most of them have difficulties maintaining the balance between the size of the dataset and a decent accuracy. In order to achieve that, this research would combine transfer learning and MobileNetV2 to build a model on edge impulse. Transfer learning, as our models learning method, decrease the size of dataset under the precondition of maintain decent accuracy. MobileNetV2 is a lightweight CNN architecture, developed by Google and it allows our model applying on mobile devices so that our model would have more application prospect. In the process of model designing, the SoftMax function was utilized as the activation function and the Adam optimization algorithm was also applied to optimize the neural network. Training the model with a modest scale of data selected from the CCPD dataset and PKU vehicle dataset, our best-trained model based on MobileNetV2 gives the highest accuracy of 99.0 %.

Analysis of the Impact of Ride-Hailing on Urban Road Network Traffic by Using Vehicle Trajectory Data

The growth of ride-hailing services has made people’s daily commutes more convenient but has increased traffic on the road. However, the data needed to verify the impact of ride-hailing services on the urban road traffic network are lacking. This study matches data on the trajectories of different kinds of vehicles in Xuancheng city in the urban road network by using vehicle information data, ride-hailing information data, and license plate data recorded by the traffic bayonet system from December 26, 2018, to January 25, 2019. We used two indices, the detecting intensity and the detecting rate, to analyze the characteristics of travel based on ride-hailing services in Xuancheng. The results show that the ride-hailing vehicles have obvious travel characteristics of morning peak and evening peak, and in central urban areas and through the proposed indices of the travel time occupation rate and the travel space occupation rate to further quantitatively analyze the spatial and temporal characteristics of travel of different kinds of vehicles. Following this, we calculated the average ratios of different kinds of vehicles on congested sections of the road network and used simple regression to analyze the relationship between this and the average speed on these sections to quantitatively analyze the impact of ride-hailing on traffic congestion. The work here can provide effective decision-making support to the government for managing travel based on ride-hailing services.

Exploring Vehicle Slogans in Al-Mukalla: An Interactional Sociological Analysis

This paper is an attempt to investigate the sociolinguistic features of these slogans using Hymes' SPEAKING model and to highlight how they reflect some aspects of the Hadrami identity. In the academic field, the linguistic analysis of slogans has been explored. However, and to the best of my knowledge, no previous study tackles the vehicle slogans using a sociolinguistic framework. This paper is limited to about thirty chosen slogans which were noticed written on the back glasses of different kinds of vehicles in the streets of Al-Mukalla, the capital city of the coastal part of Hadhramout governorate, Yemen. These slogans were collected by the author and some colleagues during the period from 2016-2018. Within Hymes' model, the variables (S), (P), (E), and (I) were redundant, so they were excluded from the analysis. The other variables; (A)ct sequences, (K)eys, (N)orms, and (G)enres were the ones considered in the analysis. The analysed slogans show that the Hadramis are generally sarcastic considering their everyday life issues and attempt to express their opinions in an indirect way as a strategy of soothing their disappointments and managing to overcome them or al least reduce their negative influence on them.

A Survey: Position based Non DTN and DTN Routing Protocol in VANET

An Intelligent Transportation System (ITS) is an advanced technology which aims to provide modern services such as smart parking, Emergency vehicle alert notification systems, automatic traffic management, direction of safe driving, accident prevention system and many. Vehicular ad-hoc networks (VANETs) play a significant role to implement an ITS system. In Vehicular Ad-hoc network, every vehicle and Road Side Units (RSU) take part in a communication to achieve the ITS services. Since nodes of VANET are different kind of vehicles with various speed, the formation of network will be more dynamic and scalability of network varies continuously. Due to dynamic characteristics of VANET, high density of traffic and more obstacles, routing is one the biggest challenge in urban area than rural area. In this paper we present an outline of VANET, taxonomy of routing, followed by a brief discussion of position based Non DTN and DTN routing protocol. Finally, we conclude the paper with comparison result of various position-based routing protocol.

Informal roads as social-ecological-technological systems (SETS): sustainability challenges and impact on landscape transformations

Following the call to mobilize studies of social-ecological systems and sociotechnical systems, the paper presents the case for studying integrated social-ecological-technological systems (SETS), and dynamic systems that include social, natural and technological (engineering) elements. Using the case study of informal roads in the Baikal region, authors of the article argue that re-focusing on SETS creates additional synergies and convergence options to improve the understanding of coupled systems and infrastructure in particular. Historically, transportation infrastructure has contributed to changes in natural and social systems of Northern Eurasia: Trans-Siberian and Baikal-Amur railroads and Eastern Siberia–Pacific Ocean and Power of Siberia pipelines have been the main drivers of social-ecological transitions. At the local scale, informal roads serve as one of the most illustrative and characteristic examples of SETS. The examination of development and transformation of the informal roads allows exploring the interactions between socioeconomic processes, ecological dynamics and technological advances. The variety of informal roads reflects the importance of specific social, natural or technological factors in the SETS transformation largely unconditioned by policy and regulations thus providing a unique opportunity to better understand sustainability challenges facing infrastructure-based SETS. Relying on interviews and in-situ observations conducted in 2019 in the Baikal region, the following factors affecting sustainability of informal road SETS were identified: social (identification of actors involved in location, construction, maintenance, use and abandonment of informal roads), technological (road cover, width, frequency and nature of use by different kinds of vehicles), environmental (geomorphology and landscape sensitivity and vulnerability). The sustainability challenges of SETS development and transformations are found in changing mobility practices, social structure and economies of local communities, increased occurrences of forest fires and development of erosion and permafrost degradation in local environment and push for development of new technologies of transportation and communication.

Stability study of the compatibility of three chemotherapeutic agents in a mixture solution of different kinds of vehicles in the EPOCH chemotherapy scheme.

BackgroundTo explore the stability of a mixture of three drugs including vindesine, etoposide, and epirubicin, assigned to infusion in an EPOCH chemotherapy regimen and provide a basis for clinical use.MethodsAfter mixing the three chemotherapy drugs with 500 mL of 0.9% sodium chloride or 5% glucose injection, respectively, they were divided into four groups of test solution. According to the Pharmacopoeia of the people’s Republic of China, 2020 Edition, injection fluid should be tested for content, osmolarity, insoluble microparticles and pH, as well as for sterility, bacterial endotoxin and pyrogen, etc. since this experiment focuses on the compatibility of the mixture of the three drugs, sterility and the detection of bacterial endotoxin and pyrogen, etc. were not performed. The test solutions were placed at room temperature, the content was determined using high-performance liquid chromatography, and the pH, osmolarity, and insoluble microparticle changes of the mixed solution were determined. Both imported and domestic epirubicin was used.ResultsThe four groups of test solution have no significant changes in pH, osmolarity, and insoluble microparticles were observed within 48 h, with the contents changing by less than 5%. Compared with the other three groups, the imported epirubicin saline group achieved better results with significant differences in insoluble microparticle detection items of ≥10 and ≥25 µM (P<0.05).ConclusionsThe stability of the three drugs in 500 mL 0.9% sodium chloride and 5% glucose injection at room temperature was good. Imported epirubicin had some advantages in the number of insoluble microparticles and its pH was more suitable when normal saline was used as a vehicle. To reduce irritation to blood vessels by infusion, it is recommended to choose imported epirubicin with 0.9% sodium chloride mixed deployment.

Modeling and Evaluation of the Impact of Motorcycles Mobility on Vehicular Traffic

Traffic simulation can help to evaluate the impact of different mobility behaviors on the traffic flow from safety, efficiency, and environmental views. The objective of this paper is to extend the SUMO (Simulation of Urban Mobility) road traffic simulator to model and evaluate the impact of motorcycles mobility on vehicular traffic. First, we go through diverse mobility aspects and models for motorcycles in SUMO. Later, we opt for the most suitable mobility models of motorcycles. Finally, the impact of motorcycle mobility on different kinds of vehicles is investigated in terms of environment, fuel consumption, velocity and travel time. The result of modeling and evaluation shows that based on the mobility model of the motorcycle, vehicular traffic flow can be enhanced or deteriorated.

Unravelling the Impacts of Parameters on Surrogate Safety Measures for a Mixed Platoon

With the precedence of connected automated vehicles (CAVs), car-following control technology is a promising way to enhance traffic safety. Although a variety of research has been conducted to analyze the safety enhancement by CAV technology, the parametric impact on CAV technology has not been systematically explored. Hence, this paper analyzes the parametric impacts on surrogate safety measures (SSMs) for a mixed vehicular platoon via a two-level analysis structure. To construct the active safety evaluation framework, numerical simulations were constructed which can generate trajectories for different kind of vehicles while considering communication and vehicle dynamics characteristics. Based on the trajectories, we analyzed parametric impacts upon active safety on two different levels. On the microscopic level, parameters including controller dynamic characteristics and equilibrium time headway of car-following policies were analyzed, which aimed to capture local and aggregated driving behavior’s impact on the vehicle. On the macroscopic level, parameters incorporating market penetration rate (MPR), vehicle topology, and vehicle-to-vehicle environment were extensively investigated to evaluate their impacts on aggregated platoon level safety caused by inter-drivers’ behavioral differences. As indicated by simulation results, an automated vehicle (AV) suffering from degradation is a potentially unsafe component in platoon, due to the loss of a feedforward control mechanism. Hence, the introduction of connected automated vehicles (CAVs) only start showing benefits to platoon safety from about 20% CAV MPR in this study. Furthermore, the analysis on vehicle platoon topology suggests that arranging all CAVs at the front of a mixed platoon assists in enhancing platoon SSM performances.

On the nonsmooth dynamics of towed wheels

In this paper, a nonsmooth model of towed wheels is analysed; this mechanism can be a part of different kind of vehicles. We focus on the transitions between slipping and rolling in the presence of dry friction. The model leads to a three-dimensional dynamical system with a codimension-2 discontinuity. The systems can be analysed by means of the tools of extended Filippov systems. The essence of the calculation is to find the so-called limit directions, which show the possible directions of slipping-rolling transitions and their properties. By this method, four different scenarios are found. The results are compared to those from the creep models.

Influence of new energy vehicle subsidy policy on emission reduction of atmospheric pollutants: A case study of Beijing, China

New energy vehicles (NEVs) have great potential to reduce emissions containing atmospheric pollutants. The Chinese Government has implemented a series of subsidy policies to promote NEVs and replace traditional fuel vehicles (TFVs). However, the contribution of NEVs in reducing atmospheric pollutants varies due to differences in mileages and emission factors. Previous literature has rarely studied the influence of NEV subsidy policies on the reduction of atmospheric pollutants, especially with respect to different kinds of vehicles. This paper divides motor vehicles into four categories: buses, taxis, passenger cars, and special vehicles. Taking into account the purchase subsidies and construction subsidies on the charging infrastructure of NEVs, this paper proposes an evaluation index, namely, the comprehensive subsidy efficiency, that measures the effectiveness of the two subsidies in reducing emissions of atmospheric pollutants among different NEVs. In response to Beijing’s plan to prioritize the promotion of battery electric vehicles (BEVs), this paper uses relevant data of BEVs instead of NEVs for the analysis. Taking Beijing as a case study, promotion proportion of NEVs were set according to the comprehensive subsidy efficiency of various NEVs; furthermore, scenario simulation of NEV subsidy policies in 2017 and 2020 was conducted. The results revealed new energy taxis and special vehicles have great a potential to alleviate the greenhouse effect and haze weather, respectively. By prioritizing the promotion of NEVs with higher comprehensive subsidy efficiency, one can achieve greater reduction in the emissions of atmospheric pollutants with equal financial funds. Furthermore, this paper suggests subsidy policies of NEVs from the perspective of reducing emissions of atmospheric pollutants.

Environmental and traffic assessment of adjusting Triple Highway Capacity Manual (HCM) factors at signalized intersections

Kuwait traffic networks has started to develop in the early 60’s. Since it is crucial to determine the parameters that present the local conditions in Kuwait, this study was developed to modify the passenger car equivalent (PCE) values at different signalized intersections in Kuwait and obtain the heavy-vehicle adjustment factor. The headway ratio method was utilized to determine the PCE values for different kinds of vehicles. 1. The PCE values were 1.14, 1.11, 1.26, 1.68 and 1.48 for sport utility vehicles (SUV), pickups, minibuses, trucks, and buses respectively. 2.The heavy vehicle adjustment factor was 0.891. Synchro simulation software was utilized to build different scenarios for improving an existing intersection and compare the network performance for each scenario. Two scenarios were chosen to be the best which are having five lanes with 2.4 m width for the first scenario and 2.7 m width for the second one. 3. Based on Synchro results, fuel consumption and pollutant emissions parameters were used to estimate the cost difference in the two best scenarios, and it was 10.71 and 13.23 Kuwaiti dinar (KD), respectively. Also, the percentage reduction of the emissions were 15.5% and 19.19%, respectively. The impact of adding an extra lane was noticed to be better compared with increasing the lane widths in a significant way. Additionally, it is a must to localize the parameters to represent the local conditions in Kuwait. The heavy-vehicle adjustment factor has an essential effect on the network performance which indicates that the PCE values should be determined accurately.

Distributed multi‐vehicle task assignment in a time‐invariant drift field with obstacles

This study investigates the task assignment problem where a fleet of dispersed vehicles needs to visit multiple target locations in a time-invariant drift field with obstacles while trying to minimise the vehicles' total travel time. The vehicles have different capabilities, and each kind of vehicles can visit a certain type of the target locations; each target location might require to be visited more than once by different kinds of vehicles. The task assignment problem has been proven to be NP-hard. A path planning algorithm is first designed to minimise the time for a vehicle to travel between two given locations through the drift field while avoiding any obstacle. The path planning algorithm provides the travel cost matrix for the target assignment, and generates routes once the target locations are assigned to the vehicles. Then, a distributed algorithm is proposed to assign the target locations to the vehicles using only local communication. The algorithm guarantees that all the visiting demands of every target will be satisfied within a total travel time that is at worst twice of the optimal when the travel cost matrix is symmetric. Numerical simulations show that the algorithm can lead to solutions close to the optimal.

Guest Editorial: Introduction to the Special Section on Machine Learning-Based Internet of Vehicles: Theory, Methodology, and Applications

The articles in this special section focuses on Vehicle (IoV) technologies and applications. With the significant development of smart vehicles, IoV technologies have received widespread attention. The IoV technology refers to dynamic mobile communication systems that communicate between vehicles and public networks using V2V (vehicle-to-vehicle),V2R (vehicle-to-road), V2H (vehicle-to-human) and V2S (vehicleto- sensor) interactions. It enables information sharing and the gathering of information on vehicles, roads, and their surrounds. The actual applications of smart Vehicles and IoV systems meet with many challenges, such as how the big data in IoV can be collected and distributed to the interested vehicles and human beings for the purpose of enhancing the road users’ experience, how huge volumes of data can be processed toward reducing the road congestion and improving traffic management and road safety, how to realize quick and efficient communication between a large amount of different kinds of vehicles and smart devices, how to effectively process the large collections of data in IoV systems, or how to protect the privacy. Many machine learning methods can be used With the significant development of smart vehicles, Internet of Vehicle (IoV) technologies have received widespread attention. The IoV technology refers to dynamic mobile communication systems that communicate between vehicles and public networks using V2V (vehicle-to-vehicle),V2R (vehicle-to-road), V2H (vehicle-to-human) and V2S (vehicleto- sensor) interactions. It enables information sharing and the gathering of information on vehicles, roads, and their surrounds. The actual applications of smart Vehicles and IoV systems meet with many challenges, such as how the big data in IoV can be collected and distributed to the interested vehicles and human beings for the purpose of enhancing the road users’ experience, how huge volumes of data can be processed toward reducing the road congestion and improving traffic management and road safety, how to realize quick and efficient communication between a large amount of different kinds of vehicles and smart devices, how to effectively process the large collections of data in IoV systems, or how to protect the privacy. Many machine learning methods can be used

Limitations of vehicle movement resistances: aerodynamic resistance

In the paper limitations and exemplary methods of aerodynamic drag force minimization in different kinds of vehicles are described. Changes of value of aerodynamic drag coefficient during years are present-ed. Conclusions about future possible new solutions in different kinds of vehicles are formulated.

An Integrated Approach for Sustainable Supply Chain Management with Replenishment, Transportation, and Production Decisions

Sustainable supply chain management is important for most firms in today’s competitive environment. This study considers a supply chain environment under which the firm needs to make decisions regarding from which supplier and what quantity of parts should be purchased, which vehicle with a certain emissions amount and transportation capacity should be assigned, and what kind of production mode should be used. The integrated replenishment, transportation, and production problem is concerned with coordinating replenishment, transportation, and production operations to meet customer demand with the objective of minimizing the cost. The problem considered in this study involves heterogeneous vehicles with different emission costs, various materials with dissimilar emission costs, and distinct production modes, each with their own emission costs. In addition, multiple suppliers with different quantity discount schemes are considered, different kinds of vehicles with different loading capacities and traveling distance limits are present, and different production modes with different production capacities and production costs are included. A mixed integer programming model is proposed first to minimize the total cost, which includes the ordering cost, purchase cost, transportation cost, emission cost, production cost, inventory-holding cost, and backlogging cost, while satisfying various constraints in replenishment, transportation, and production. A particle swarm optimization model is constructed next to deal with large-scale problems that are too complicated to solve by the mixed integer programming. The main advantage of the proposed models lies in their ability to simultaneously coordinate the replenishment, transportation, and production operations in a planning horizon. The proposed particle swarm optimization model could further identify a near-optimal solution to the complex problem in a very short computational time. To the best of the authors’ knowledge, this is the first paper that considers the sustainable supply chain management problem with multiple suppliers, multiple vehicles, and multiple production modes simultaneously. Case studies are presented to examine the practicality of the mixed integer programming and the particle swarm optimization models. The proposed models can be adopted by the management to make relevant supply chain management decisions.

Motorcycle Movement Model Based on Markov Chain Process in Mixed Traffic

&lt;p&gt;Mixed traffic systems are dynamically complex since there are many parameters and variables that influence the interactions between the different kinds of vehicles. Modeling the behavior of vehicles, especially motorcycle which has erratic behavior is still being developed continuously, especially in developing countries which have heterogeneous traffic. To get a better understanding of motorcycle behavior, one can look at maneuvers performed by drivers. In this research, we tried to build a model of motorcycle movement which only focused on maneuver action to avoid the obstacle along with the trajectories using a Markov Chain approach. In Markov Chain, the maneuver of motorcycle will described by state transition. The state transition model is depend on probability function which will use for determine what action will be executed next. The maneuver of motorcycle using Markov Chain model was validated by comparing the analytical result with the naturalistic data, with similarity is calculated using MSE. In order to know how good our proposed method can describe the maneuver of motorcycle, we try to compare the MSE of the trajectory based on Markov Chain model with those using polynomial approach. The MSE results showed the performance of Markov Chain Model give the smallest MSE which 0.7666 about 0.24 better than 4th order polynomial.&lt;/p&gt;