Illegal Vehicle Research Articles

AI-based method for determining vehicles with illegal muffler from pass-by noise

In Japan, illegal noisy vehicle is controlled by the result of a stationary noise test. The stationary noise test used does not have a simple correlation with pass-by noise due to differences in vehicle conditions. If illegal vehicles can be identified by pass-by noise, it will lead to more effective roadside inspections. Therefore, this study investigated whether it is possible to identify vehicles that exceed the limit value of the stationary noise test limit from pass-by noise using AI. First, we investigated the method using a single sound level meter, and then considered the use of a microphone array to make the method more effective in road traffic flow.

Criminological analysis of the state and particularities of determination of the illegal possession of vehicles in Ukraine under conditions of armed aggression

The article deals with the criminological analysis of the state and peculiarities of determination of the illegal possession of vehicles in conditions of armed aggression. It has been established that the dynamics of illegal vehicle possession in the context of armed conflict are unfavourable. There has been a significant increase in the number of criminal offences committed under article 289 of the Criminal Code of Ukraine. It has been established that the deterioration of criminogenic situation according to the criterion under study was due to the intensification of a number of factors, the leading place among which is occupied by situational factors. Four groups have been defined and described, which are identified with the components of criminogenic situations.
 Supervisory and deficit factors are a group of determinants of illegal vehicle possession that represent complex criminogenic situations, the characteristics of which are inadequate control, supervision of vehicles in a static location. In situations of armed conflict, these determinants are shaped by the urgency of leaving vehicles unattended, prioritising saving lives and health, personal freedom when there is a risk of combat exposure, and the occupation of territory.
 Criminal and combat factors of illegal possession of vehicles are formed as an element of the combat situation; possession of vehicles by civilians occurs either on the battlefield or in connection with the performance by representatives of the aggressor country (combatants and other participants in the armed conflict) of tasks harmful to the interests of Ukraine: illegal possession of vehicles by members of diversionary-intelligence groups or hostile (Russian) combatants during combat operations.
 Occupation factors are most intensively reproduced in the conditions of full-scale armed aggression of the Russian Federation against Ukraine and are associated with the same large-scale and complex victimisation of the population who find themselves in the temporarily occupied territories. This category of citizens is completely deprived of legal guarantees of their rights and freedoms.
 Victim-urban factors are represented by a conglomeration of circumstances of criminogenic significance that form a situation of relaxed control over vehicles in places where they are forced to concentrate, for relatively long periods of time. These situations primarily involve the illegal possession of vehicles by internally displaced persons. The mass displacement of citizens from the northern, eastern and southern regions of Ukraine to the western region has created a shortage of secure, properly equipped parking spaces, making it easier for criminals to gain access to vehicles.

IMF-PR: An Improved Morton-Filter-Based Pseudonym-Revocation Scheme in VANETs.

Vehicle ad hoc networks (VANETs) are special wireless networks which help vehicles to obtain continuous and stable communication. Pseudonym revocation, as a vital security mechanism, is able to protect legal vehicles in VANETs. However, existing pseudonym-revocation schemes suffer from the issues of low certificate revocation list (CRL) generation and update efficiency, along with high CRL storage and transmission costs. In order to solve the above issues, this paper proposes an improved Morton-filter-based pseudonym-revocation scheme for VANETs (IMF-PR). IMF-PR establishes a new distributed CRL management mechanism to maintain a low CRL distribution transmission delay. In addition, IMF-PR improves the Morton filter to optimize the CRL management mechanism so as to improve CRL generation and update efficiency and reduce the CRL storage overhead. Moreover, CRLs in IMF-PR store illegal vehicle information based on an improved Morton filter data structure to improve the compress ratio and the query efficiency. Performance analysis and simulation experiments showed that IMF-PR can effectively reduce storage by increasing the compression gain and reducing transmission delay. In addition, IMF-PR can also greatly improve the lookup and update throughput on CRLs.

Crowd-Sensing Enhanced Parking Patrol Using Sharing Bikes’ Trajectories

Illegal vehicle parking is a common urban problem faced by major cities in the world, as it incurs traffic jams, which lead to air pollution and traffic accidents. The government highly relies on active human efforts to detect illegal parking events. However, such an approach is extremely ineffective to cover a large city since the police have to patrol over the entire city roads. The massive and high-quality sharing bike trajectories from Mobike offer us a unique opportunity to design a ubiquitous illegal parking detection approach, as most of the illegal parking events happen at curbsides and have significant impact on the bike users. The detection result can guide the patrol schedule, i.e., send the patrol policemen to the region with higher illegal parking risks, and further improve the patrol efficiency. Inspired by this idea, three main components are employed in the proposed framework: 1) <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">trajectory pre-processing</i> , which filters outlier GPS points, performs map-matching, and builds trajectory indexes; 2) <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">illegal parking detection</i> , which models the normal trajectories, extracts features from the evaluation trajectories, and utilizes a distribution test-based method to discover the illegal parking events; and 3) <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">patrol scheduling</i> , which leverages the detection result as reference context, and models the scheduling task as a multi-agent reinforcement learning problem to guide the patrol police. Finally, extensive experiments are presented to validate the effectiveness of illegal parking detection, as well as the improvement of patrol efficiency.

A Lightweight and Conditional Privacy-Preserving Authenticated Key Agreement Scheme With Multi-TA Model for Fog-Based VANETs

Recently, the fog computing concept has been introduced into vehicular ad-hoc networks (VANETs) to formulate fog-based VANETs. Since the communication channels between vehicles and fog nodes are open and insecure, it is necessary to construct an authenticated key agreement (AKA) scheme for securing the channels. The existing AKA schemes have two main deficiencies. One is that the computational and communication overhead are not low enough to satisfy the requirements of delay-sensitive applications. The other is that the multi-trusted-authority (multi-TA) model has not been considered. To solve the deficiencies, we propose a lightweight and conditional privacy-preserving AKA scheme, where the main steps are designed with symmetric cryptography methods. The design can reduce the computational and communication overhead of the AKA process. Additionally, we consider the multi-TA model in the AKA process to solve the single-point-of-failure issue. By integrating Cuckoo filter into the multi-TA model, the secrecy of real identities of legal vehicles is guaranteed and the identity revocation function for illegal vehicles is supported in the AKA process. The security proof and analysis show that our proposed scheme satisfies the essential security and privacy requirements of VANETs. The performance analysis shows that our proposed scheme outperforms other related and represented schemes.

A trust based adaptive privacy preserving authentication scheme for VANETs

In vehicular ad hoc networks (VANETs), the exchanged messages among vehicles can effectively improve traffic safety and efficiency. Since the nature of open communication in VANETs, it is necessary to verify the legitimacy of vehicles to prevent illegal vehicles from participating in VANETs. In order to reveal the real identities of malicious vehicles, many conditional privacy preserving authentication schemes have been proposed. While, unconditional privacy preserving is also need for honest vehicles. However, the single conditional or unconditional privacy preserving cannot meet the privacy needs of various vehicles. In this paper, we propose a trust based adaptive privacy preserving authentication scheme. Under the assumption that the external system provides the trust values of vehicles and drivers, the scheme can provide unconditional privacy preserving with different trust levels for high trusted vehicles, while conditional privacy preserving is adopted for low trusted vehicles. In addition, considering the public identities of vehicles and the many-to-many relationship between vehicles and drivers, we introduce a ternary based identity representation method to generate the identities of vehicles, drivers and roadside units. And then, we propose a three entity authentication algorithm to verify the legitimacy of entities. Finally, the formal verification and security analysis are carried out, and the scheme has the characteristics of supervisability and adaptive privacy preserving. Moreover, in order to resist quantum attack, the latest lattice-based encryption and signature algorithms are adopted, and then the computation and communication costs are analyzed in detail.

Moving Target Detection Technology Based on UAV Vision

The detection of moving objects by machine vision is a hot research direction in recent years. It is widely used in military, medical, transportation, and agriculture. With the rapid development of UAV technology, as well as the high mobility of UAVs and the wide range of high-altitude vision, the target detection technology based on UAV vision is applied to traffic management such as vehicle tracking and detection of vehicle violations. The moving target detection technology in this study is based on the YOLOv3 algorithm. It implements moving vehicle tracking by means of Mean-Shift and Kalman filtering. In this paper, the Gaussian background difference technology is used to analyze the illegal behavior of the vehicle, and the color feature extraction technology is used to identify and locate the license plate, and the information of the illegal vehicle is entered into the database. The experiment compares the moving target detection of UAV vision and the traditional target detection in four aspects: recognition accuracy, recognition speed, manual time, and divergent results. The results show that the average accuracy rates of UAV vision-based moving target detection and traditional pattern recognition are 98.4% and 87.8%, respectively. The recognition speeds are 24.9 (vehicles/sec) and 10.6 (vehicles/sec), respectively. However, the artificial time and divergence results of moving target detection based on UAV vision are only 1/3 of the traditional mode. The moving target detection based on UAV vision has a better moving target detection ability.

Vehicle Routing Optimization Based on Multimedia Communication and Intelligent Transportation System

With the maturity and popularity of network technology and multimedia technology, more and more communication tools and means have entered people’s lives. The usual communication tools are often limited to the ability to transmit sound signals. This method does not well express the information between the two parties in some special occasions, such as a noisy environment, where both parties have language or hearing impairments. The multimedia communication system is a technology that combines network communication and multimedia. It utilizes the efficiency of data transmission over the network and the diversity of information in multimedia, making communication between people faster, clearer, and more intuitive. The multimedia communication system is an important part of the application to the intelligent transportation system. Intelligent transportation system is a systematic, real-time, accurate, interactive, and extensive traffic management system established by the comprehensive use of modern high and new technology in the transportation system. With these characteristics, intelligent transportation system has increasingly become an important means to solve modern traffic problems. Based on multimedia communication and intelligent transportation system, this article optimizes the vehicle path and realizes the application of intelligent transportation. The proposed intelligent transportation system realizes functions, such as vehicle speed detection, vehicle behavior semantic analysis, license plate recognition by processing video data, and image data acquired based on multimedia communication, and can capture illegal vehicles and then identify illegal vehicles. The license plate is conducive to promoting the management and control of intelligent transportation and reducing the occurrence of traffic accidents.

Vehicle Detection for Vision-Based Intelligent Transportation Systems Using Convolutional Neural Network Algorithm

Vehicle detection in Intelligent Transportation Systems (ITS) is a key factor ensuring road safety, as it is necessary for the monitoring of vehicle flow, illegal vehicle type detection, incident detection, and vehicle speed estimation. Despite the growing popularity in research, it remains a challenging problem that must be solved. Hardware-based solutions such as radars and LIDAR are been proposed but are too expensive to be maintained and produce little valuable information to human operators at traffic monitoring systems. Software based solutions using traditional algorithms such as Histogram of Gradients (HOG) and Gaussian Mixed Model (GMM) are computationally slow and not suitable for real-time traffic detection. Therefore, the paper will review and evaluate different vehicle detection methods. In addition, a method of utilizing Convolutional Neural Network (CNN) is used for the detection of vehicles from roadway camera outputs to apply video processing techniques and extract the desired information. Specifically, the paper utilized the YOLOv5s architecture coupled with k-means algorithm to perform anchor box optimization under different illumination levels. Results from the simulated and evaluated algorithm showed that the proposed model was able to achieve a mAP of 97.8 in the daytime dataset and 95.1 in the nighttime dataset.

A dynamic key management and secure data transfer based on m-tree structure with multi-level security framework for Internet of vehicles

Nowadays, broadband wireless networks and 5G have improvements in the quality and dependability of network services for high-speed mobile vehicles. Within an open communication environment on the Internet of vehicles named IoV, personal details will be revealed on the Wi-Fi network. Considering information security and privacy, this research concentrates on how to protect secure information transmission in real time through IoV, and also wants to avoid illegal vehicles, passers-by or drivers from joining connection and planting or altering significant data. This research provides a multilevel security infrastructure with M-tree based elliptic curve digital signature algorithm (ECDSA) for securing data transmission in both IoV and cloud environments. While transmitting, this study provides several flexible and scalable schemes to manage security issues, which dynamically adjust the framework depending on the rapidly changing IoV topology and speed up the time to synchronise the reconstruction of the system key, and decrease the quantity of phases to resynchronise the system key. Moreover, most research of key management without secure data transmission, we integrate the M-tree key management with secure data transmission to achieve the secure IoV. Simultaneously, the provided key management for the multi-level security is quite appropriate to adaptable and expandable IoV.

A Smart Parking System‏, Case Study

The Gaza Strip in general, and the Islamic University of Gaza (IUG) in particular, are plagued by a lack of parking places, a lack of management and efficient usage of parking spaces, and illegal vehicle parking. This resulted in lost time and effort, besides traffic congestion. The study's goal is to provide a plan for implementing a Smart Parking System, which manages the parking spots on the IUG campus. To accomplish this goal, the researchers have identified the parking problems that face drivers at IUG, and then they have studied the impact of implementing the Smart Parking System. Researchers have used questionnaires to collect the raw data as one of the important tools in the field of survey. The data were analyzed using the Statistical Package for the Social Sciences (SPSS), as a useful tool for statistical analysis. The first results was the number of parking spaces is 300, which is greater than the number of potential vehicles occupying the university parking spaces at peak hours. Therefore, the issue is not the number of parking places, but how they are used. The result of the questionnaire presents that a large majority of respondents agreed that the IUG campus suffers from a lack of parking spaces, especially in rush hour from 8-10 am. The results indicate that 65.7% of the respondents park their cars near their workplace/study at the campus parking spaces, and 72.6% of the respondents do not use parking spaces with modern technology before. While 92.6% of the respondents encourage parking with modern technologies. Smart Parking System has assisted to resolve the issue of locating a parking spot on the IUG campus, resulting in less traffic congestion and a better flow of traffic. The Smart Parking System can be applied to all of the IUG's parking spaces and in the Gaza strip cities in the future

Fully self-powered instantaneous wireless traffic monitoring system based on triboelectric nanogenerator and magnetic resonance coupling

The self-powered wireless sensor systems are highly sought for the information era, as they are able to link everything together, yet without the need for electric power supply. They have been exploited for applications in various fields, particularly for environment-related ones. Here, we propose a fully self-powered triboelectric nanogenerator (TENG)-based wireless traffic monitoring system for real-time monitoring of illegally entered electric motorbikes on the footpaths, and flow rates of pedestrians and motorbikes, and speed and driving direction of electric motorbikes on non-motorized lanes. The TENG was used to directly convert the energy from pedestrian’s stepping and electric motorbike’s rolling into an oscillating signal with encoded sensing information, and transmit it to the receiver wirelessly via magnetic resonance coupling. Results showed that the multi-variable traffic monitoring system can identify pedestrians and motorbikes, check the illegally entered motorbikes on the footpath, and measure speed of the motorbikes with an accuracy of over 94%, monitor driving direction of electric motorbikes on non-motorized lanes. The self-powered wireless traffic monitoring system is simple in structure, low cost, easy to install, and spontaneous response to the traffic condition, and does not contain electronic devices, microcontrollers and transmission chips but the passive components, hence it has great application potential as a green intelligent traffic monitoring system. The self-powered wireless traffic monitoring system based on TENG, which can monitor real-time electric motorbikes illegally entering in the footpaths, and flow rates of pedestrians and motorbikes, and speed measurement, driving direction of electric motorbikes on non-motorized lanes. • A triboelectric nanogenerator (TENG) based self-powered instantaneous wireless traffic monitoring system is developed which yet does not contain electronic devices, but the passive components. • The traffic recognition monitoring system can identify pedestrians on the sidewalk and illegal vehicles entering the footpath. • The traffic speed monitoring system can realize the function of electric vehicle speed measurement and driving direction judgment.

Number Plate Recognition System using MATLAB

This paper presents a system called NPR (Number Plate Recognition) which is based on image processing and is used to detect the number plates of vehicles and process them to record the information. In a fast-growing world, it has become almost impossible to track illegal vehicles and store vehicle information. This is eventually leading to a rise in the crime rate, especially due to manual errors. The proposed system first captures the vehicle image and the vehicle number plate region is extracted using Image Segmentation in an image. The resulting data is then used to compare with the records on a database to come up with specific information like the vehicle's owner, place of registration, address, etc. Further, the system is implemented and simulated in MATLAB for studying feasibility and accuracy on a real image.

EC-BAAS: Elliptic curve-based batch anonymous authentication scheme for Internet of Vehicles

As an indispensable part of intelligent transportation systems, Internet of Vehicles (IoV) has been widely used in improving the driving experience and road conditions. In the communication of IoV, the security of transmitted messages is critical. Specifically, the messages should be signed and verified before they are accepted by vehicles or road side units. To ensure the privacy of vehicle users, the vehicles’ true identity cannot be leaked. Moreover, considering the high dynamics and open environments of IoV, it is very important to design an efficient anonymous authentication scheme on the basis of security. However, most of the existing schemes struggle with the problems of insufficient security performance and low efficiency. This motivates us to propose a safe and efficient privacy protection scheme for IoV. The proposed scheme is a new batch anonymous authentication scheme designed based on the elliptic curve encryption algorithm, considering both security and efficiency. A distributed signature generation method is also developed in the proposed scheme to relieve the burden of the trusted center. In addition, our scheme can effectively track illegal vehicles and achieve conditional privacy protection. Theoretical analysis and performance evaluation are both carried out to validate our scheme. The results show that our scheme ensures competitive security performance with lower communication and computation overheads compared to representative approaches.

System Model of VANET using Optimization-Based Efficient Routing Algorithm

A wireless networking strategy is the VANET (Vehicular ad hoc network). This approach is used to connect between vehicles and to raise the question of traffic quality. The most important aspect is the connection between V2v and V2i, so it is essential to ensure appropriate protection and privacy techniques. VANET safer, effective and avoid illegal vehicle interference with other cars, this work suggests an authentication scheme based on the hash feature. Only an authenticated vehicle may use the party key agreement scheme using the Chinese residual theorem. The forward and backward confidentiality was done in this manner. Security and privacy are fulfilled by our scheme. The most favorable aim is to create more useful, productive and safer roads across vehicle networks by educating the basic authorities and drivers in the future on a timely basis. Another aim is to identify wireless technology for the development of VANET. The aim is to protect and render feasible commercial requests by means of a variety of short to medium communication systems and/or other VANET networks. This technology will help the primary concern for safe contact in crucial time and meet the QOS criteria of other interactive multimedia applications or e-commerce.

Developments in German Criminal Law: Speed Merchant or Murderer? The Ku’Damm Road Race Case and the New Criminal Legislation Regulating Illegal Motor Racing

AbstractThe Regional Court of Berlin (Landgericht (LG) Berlin) was the first court in Germany to mete out a life sentence for murder—pursuant to § 211 German Criminal Code (StGB)—to two men convicted of killing an uninvolved driver whose car they hit while they were participating in an illegal car race on a public highway. Upon their convictions, the defendants appealed to the German Federal Court of Justice (Bundesgerichtshof; BGH) claiming that they did not intend to kill the person and were thus acting without the necessary mens rea for murder. The question whether or not the case could be qualified as murder, and thus whether or not the existence of a killing with intent had been sufficiently proven by the LG Berlin, was the subject of several appeals and retrials. In its latest decision, the BGH confirmed the murder conviction of one of the defendants, while quashing the other defendant’s conviction and issuing a retrial. This case caused ripples amongst legal scholars as it called for the toughest possible sanctions to be imposed. However, whether the conduct qualifies as murder remains questionable. As a reaction to several similar cases of illegal car races in recent years, the German parliament subsequently passed a new law—§ 315d StGB—proscribing illegal vehicle races, thereby penalizing the participation, organization, or carrying out of an illegal vehicle race. Until that point there had been no provision criminalizing illegal racing.

Study on intelligent traffic search method based on driver facial feature analysis

With the rapid development of Internet technology and biometrics technology in China, artificial intelligence has gradually entered into every aspect of people's life. Big data is used to upgrade intelligent traffic search for people, which improves the efficiency and accuracy of people search for people. Intelligent traffic search is a hotspot in the field of biometric identification and plays an important role in social stability. As an important feature, driver's face image can not only provide great help to the detection of illegal vehicles, but also help to carry out the tracing of missing people, so as to maintain social harmony and stability. Therefore, the intelligent traffic search method based on the analysis of driver's facial features has a broad application prospect and research value. This paper investigates the current international top facial recognition algorithm technology level, and proposes a face image illumination invariant feature extraction algorithm and face feature detection ASM algorithm. The experimental results show that the intelligent traffic search method in this paper has a good recognition rate, and the study in this paper also has a certain guiding significance for the application of image processing in the field of intelligent traffic.

Study on intelligent traffic search method based on driver facial feature analysis

With the rapid development of Internet technology and biometrics technology in China, artificial intelligence has gradually entered into every aspect of people's life. Big data is used to upgrade intelligent traffic search for people, which improves the efficiency and accuracy of people search for people. Intelligent traffic search is a hotspot in the field of biometric identification and plays an important role in social stability. As an important feature, driver's face image can not only provide great help to the detection of illegal vehicles, but also help to carry out the tracing of missing people, so as to maintain social harmony and stability. Therefore, the intelligent traffic search method based on the analysis of driver's facial features has a broad application prospect and research value. This paper investigates the current international top facial recognition algorithm technology level, and proposes a face image illumination invariant feature extraction algorithm and face feature detection ASM algorithm. The experimental results show that the intelligent traffic search method in this paper has a good recognition rate, and the study in this paper also has a certain guiding significance for the application of image processing in the field of intelligent traffic.

WITHDRAWN: An approach to illegally parked vehicle detection

Nowadays illegally parked vehicle is major concern faced in the metropolitan cities worldwide. Illegal parking of vehicles is the crucial reason for the massive traffic jam that can lead to air pollution, vehicle crashing, and the significant parking revenue loss for the city administration. An attempt is necessary to implement the system that detects the illegal vehicle parking by image processing & OCR technique. Designing a comprehensive pre-processing module for image enhancement and normalization, such as smoothing, noise reduction, etc. is needed. Pre-processed image segmentation is required for splitting an image into homogeneous entities like lines, numbers & characters. The extraction of some features from the image that should permit discrimination between different classes is part of feature extraction. Finally, classification rules on training sets & post-processing techniques can be used for getting accurate results.

ESAC: An Efficient and Secure Access Control Scheme in Vehicular Named Data Networking

In Vehicular Ad Hoc Networks (VANETs), the mobility of vehicles and urban obstacles may make the traditional IP-based content delivery mechanisms; work sluggishly. To address this problem, we adopt the Vehicular Named Data Networking (V-NDN) architecture to enable efficient content delivery. However, secure access control and incentive design are rarely taken into account in existing solutions. In this paper, we propose an efficient and secure access control (ESAC) scheme for content delivery in V-NDN. Specifically, we construct the proxy re-encryption method to achieve access control and data confidentiality, while using pseudonyms and the identity-based signature to ensure anonymous authentication and content integrity. Furthermore, the revocation of illegal vehicles and updating operations are performed by the constructed proxy re-encryption method, which significantly reduces communication overhead. Finally, an incentive scheme is designed to improve the utility of NDN in VANETs. The security analysis shows that ESAC can meet the security requirements of the content delivery in VANETs while significantly lowering the overhead.