Vehicle Tracking Systems Research Papers (original) (raw)

The proposed design offers a complete solution to support and surveillance vehicles remotely. The offered algorithm allows a monitoring center to track vehicles; diagnoses fault remotely, control the traffic and control CO emission. The system is programmed to scan the on-board diagnostic OBD periodically or based on request to check if there are any faults and read all the available sensors, then make an early fault prediction based on the sensor readings, an experience with the vehicle type and fault history. It is so useful for people who are not familiar with fault diagnosis as well as the maintenance center. The system offers tracking the vehicle remotely, which protects it against theft and warn the driver if it exceeds the speed limit according to its location. Finally, it allows the user to report any traffic congestion and allows a vehicle navigator to be up to date with the traffic condition based on the other system’s user feedback.

- by
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- Computer Science, Traffic control, Vehicle Tracking Systems, Tracking Vehicles in Real Time

This is my doctoral dissertation

- by Tongtong Chen
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- Vehicle Tracking Systems, Vehicle Detection

Vehicle detection and tracking is an inevitable application of visual surveillance. There are several techniques in the literature which deal with vehicle detection, but the decrease in visibility due to camera noise and unfavourable climatic conditions due to snow, fog, rain, swaying leaves etc. makes it difficult to detect the moving objects in the scene. This paper
proposes a framework to detect and track multiple moving vehicles despite of occlusions. To detect and segment the moving vehicles make use of dynamically adaptive threshold using the modified full-search sum of absolute difference algorithm, which reduces computational complexity. For tracking all the detected objects uniquely, an algorithm using Kalman filter is proposed, which is able to handle occlusions to a greater extend.

- by Sukanyathara J
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- Computer Vision, Digital Image Processing, Vehicle Tracking Systems

Visual monitoring activities using cameras automatically without human intervention is a big and challenging problem so we need automatic object tracker system. This paper presents a new object tracking system in Real time that systematically combines both motion detection and sound detection. In this system detect motion as well as sound in a real time and if lack of security it is also give alert message through alarm. The proposed method is excellent in real-time performance because it detect the moving objects efficiently and accurately form the video recorded by a shaking camera with changing background and noises.

Our aim is to estimate the perspective-effected geometric distortion of a scene from a video feed. In contrast to most related previous work, in this task we are constrained to using low-level, spatio-temporally local motion features only. This particular challenge arises in many semi-automatic surveillance systems which alert a human operator to potential abnormalities in the scene. Low-level, spatio-temporally local motion features are sparse (and thus require comparatively little storage space) and sufficiently powerful in the context of video abnormality detection to reduce the need for human intervention by more than 100-fold. This paper introduces three significant contributions: (i) we describe a dense algorithm for perspective estimation which uses motion features to estimate the perspective distortion at each image locus and then polls all such local estimates to arrive at the globally best estimate, (ii) we also present an alternative coarse algorithm which subdivides the image frame into blocks, and uses motion features to derive block-specific motion characteristics and constrain the relationships between these characteristics, with the perspective estimate emerging as a result of a global optimization scheme, and (iii) we report the results of an evaluation using nine large sets acquired using existing close-circuit television (CCTV) cameras, not installed specifically for the purposes of this work. Our findings demonstrate that both of the proposed methods are successful, their accuracy matching that of human labelling using complete visual data (by the constraints of the setup unavailable to our algorithms).

Vehicle Tracking Systems (VTS) are used by Fleet operators for fleet management functions such as fleet tracking, routing, dispatching, on-board information and security. VTS technology is also used by the Municipalities to monitor schedule adherence of buses in service, trigger changes of busses' destination sign displays at the end of the line (or other set location along a bus route), and trigger pre-recorded announcements for passengers. Especially for routing, tracking, security, rescheduling and cost efficiency purpose, the public organizations such as ministries, military headquarters in big cities are highly encouraged to use VTS on their vehicles ranging from small cars to midibuses, buses and lorries in order to transport its personnel and equipment. In this study, we aimed to find cost efficiency of using VTS on personnel service vehicles of a public organization. We selected 30 vehicles as a sample study. We put VTS on these vehicles and collected data by observing the vehicles during one year. According to this sample implementation, we aimed to compare the oil consumption and the expenditures of the accidents of the data does not fit a particular parametric family of distributions, specifically; a normal distribution. Therefore, we used Wilcoxon Signed Rank Test to find the results of our study. According to the results of the test, using VTS on vehicles is found to be meaningful to decrease the oil consumption but using VTS is not found cost-efficient on the expenditures of the accidents. We also proposed the optimal distances that will be cost-efficient to use VTS on the vehicles.

- by Hakan Ömer Tunca and +1
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- Transportation Engineering, Statistics, Logistics, Transportation

Traffic accidents, one of the leading sources of deaths in all places. This paper gives alert before the situation is in danger and immediately shares the location where the accident occurred. The alert will be given when the driver is not in the condition to drive and location is traced) using GPS (Global Positioning System) once accident occurred. This system helps to trace the vehicle's location easily and alerts the driver when he consumed alcohol and feels sleepy and also it helps in avoiding accidents and to provide the necessary help as soon as possible after the accident happens.

Traffic accidents, one of the leading sources of deaths in all places. This paper gives alert before the situation is in danger and immediately shares the location where the accident occurred. The alert will be given when the driver is not in the condition to drive and location is traced) using GPS (Global Positioning System) once accident occurred. This system helps to trace the vehicle’s location easily and alerts the driver when he consumed alcohol and feels sleepy and also it helps in avoiding accidents and to provide the necessary help as soon as possible after the accident happens.

- by Lee D. Han
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- Bioinformatics, Natural Language Processing, Machine Learning, Data Mining

This paper is about the detection of traffic rule breach via computer vision which takes the feed from the traffic surveillance system, processes the video feed, detects the breach and alerts the traffic police. The number of traffic accidents is on the rise with the increasing number of vehicles. Traffic breach is the biggest cause of accidents. So, to mitigate this problem our system processes the CCTV camera feed in real-time, detects the traffic rule breach events and sends the push notification to the android based application of the traffic police stationed nearby; so, further actions can be taken. As this system detects breach faster than humans, the concerned authoritarian department will be at ease in implementing safe roads accurately. This system acts as an add-on to the current video surveillance system rather than building new infrastructure. Thus, the output of this system can be used not only or safety and security purposes but as well as for analytical purposes with effective traffic monitoring at a lower cost. Hence, this system aids law enforcement agencies in implementing road safety efficiently and effectively ensuring smooth traffic flow.

- by Sunim Acharya and +2
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- Image Processing, Surveillance, Image Classification, Vehicle Tracking Systems

An integrated GPS-GSM system is proposed to track vehicles using Google Earth application. The remote module has a GPS mounted on the moving vehicle to identify its current position, and to be transferred by GSM with other parameters acquired by the automobile’s data port as an SMS to a recipient station. The received GPS coordinates are filtered using a Kalman filter to enhance the accuracy of measured position. After data processing, Google Earth application is used to view the
current location and status of each vehicle. This goal of this system is to manage fleet, police automobiles distribution and car theft cautions.

This work presents the current state-of-the-art in techniques for tracking a number of objects moving in a coordinated and interacting fashion. Groups are structured objects characterized with particular motion patterns. The group can be comprised of a small number of interacting objects (e.g. pedestrians, sport players, convoy of cars) or of hundreds or thousands of components such as crowds of people. The
group object tracking is closely linked with extended object tracking but at the same time has particular features which differentiate it from extended objects. Extended objects, such as in maritime surveillance, are characterized by their kinematic states and their size or volume. Both group and extended objects give rise to a varying number of measurements and require trajectory maintenance. An emphasis is given here to sequential Monte Carlo (SMC) methods and their variants. Methods for small groups and for
large groups are presented, including Markov Chain Monte Carlo (MCMC) methods, the random matrices approach and Random Finite Set Statistics methods. Efficient real-time implementations are discussed which are able to deal with the high dimensionality and provide high accuracy. Future trends and avenues are traced.

- by Lyudmila Mihaylova
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- Bayesian, MCMC, Monte Carlo Simulation, Probabilistic Markov Modeling

In the current scenario, there are problems during travelling like too heavy to drive the luggage, chances of missing and unauthorized accessing and charging mobile or laptop .So, the self-driving luggage helps their owner during travelling or help to overcome from the problems during travelling such solutions are the luggage follow their owner, tracking system, digital locking system and charging port in the luggage.

- by IJRASET Publication
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- Vehicle Tracking Systems, Authorization

GPS (Global Positioning System) based tracking system has many applications in today's world, including vehicle tracking, child tracking, any equipment tracking, etc. These services offer many advantages to the mobile users to retrieve the information about their current location and process that data to get more useful information. The development of a bus tracking system for android based smartphone with the aim of enabling educational institution students, faculties and staffs to locate their buses with ease and in a convenient manner. The system consists of two sides, server side and client side. The client side provides the facility to the user to track buses remotely through the mobile network or WIFI and the server side's main responsibility is to provide the exact location of the bus to the server. Any type of user can see the live location of their desire bus with only 5 seconds of update interval. This will reduce unnecessary hassle and waiting time for the users. It will provide multiple services to the user based on their category.

- by Ahmed Abid and +1
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- Traffic control, Vehicle Tracking Systems, Tracking Vehicles in Real Time, Vehicle Tracking

This analysis is based on the bus tracking system. The main intention of this work is to create an Internet-Based Tracking web application that would be able to track Nagpur buses more precisely and efficiently than present bus-tracking systems. We got the motivation for our research paper by observing how much precious time the public living in Nagpur wastes by just waiting for the bus on their particular route. There is also a lack of information for the buses that are traveling on their particular route for the public who have already missed their particular bus. The current generation is very technology-oriented and requires time-to-time updates via the internet. So, they can know the exact location of buses. This system will help to know the location of a bus without using GPS, bus schedules (i.e., according to timing), and also give information on routes and bus status. This technology will be very helpful for outsiders, college students, the local people of the city, and employees.

Intelligent bus tracking system using android is an application that tracks a bus and collects the distance to each station. Tracking system involves the installation of an electronic device in a bus, with an installed Android App on any smart phone to enable a user to track the bus location. There are two applications one for server and other for the client. The user can get flexibility of planning travel using the app, to decide on which bus to take or when to catch the bus. The waiting time of the user can be reduced. By using this application user get the information about buses, bus numbers, bus route, bus arrival and bus delay timing information etc [1]. It provides information about which bus coming to the stop. By the presently existing system we are dealing with three terminals, a device on bus, a device at bus stop and a device on the master bus stand so as to keep the track on the all city busses. By employing this tracking system the arrival of the bus is detected near the bus stop and also can be seen on the PC at the master bus stop. GSM modem can also transmit the bus information to the registered mobile numbers. Hence, we can control the bus traffic and can detect the arrival of particular bus at the bus stop. Keywords— GSM, RFID reader, LCD, RS 485, RS 232, Android phone, PC I. INTRODUCTION The transportation system serves as the heart in the economic and social development of the country. In today's world transportation system has a very vital role to play in day to day life. Due to rapid increase in population, there is need for efficient public transportation system. Because of population it keeps increased burden on public transportation like bus etc [2]. Therefore the smart system is necessary which provides real time information of bus to remote user. So we proposed a new system which overcomes the drawback of public transportation system. So our system handle all the data about current location of bus and by using this data the real time tracking of bus can be done and this information is then given to remote user who wants to know the real time bus information. The main advantage of city bus commuting is that it reduces the overall pollution, reduces the traffic on road, also the problem of parking is solved to a certain extent.

- by Sven Vlassenroot
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- Engineering, Data Mining, Intelligent Transportation Systems, Mobility

The quick development of innovation has made our lives less demanding. Innovation has additionally expanded activity risks and street mishaps occur very often which cause tremendous death toll and damage to property on account of poor response from the people in charge of managing such incidents. The mishap recognition undertaking will give an ideal solution for this problem. An accelerometer or a Tilt Sensor can be used as part of an auto caution application with the goal that unsafe driving can be identified. It can be utilized as a crash or rollover finder of the vehicle amid and after a crash. With signals from a sensor, a serious situation because of an accident can be avoided or attended to at the earliest. At the point of time when a vehicle meets with an accident or an auto moves over, the tilt sensor recognizes the flag and promptly sends it to the microcontroller. The microcontroller sends the alarm message through the IoT Module including the location of the accident through the GPS Module to the police or control group by publishing it over the cloud. So, the crisis enable group can promptly follow the area through the GPS Module, subsequent to receiving and accepting the data. The area can likewise be seen on the Google maps. Vital move can be made if this data reaches the control group in time. This venture is valuable in recognizing the accident with the use of sensors. As a future execution, we can add a remote webcam to the current system in order to capture pictures of the scene of the accident.

- by IJAAS Journal
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- Vehicle Tracking Systems, Internet of Things (IoT), Gps Module

Vehicle detection and tracking is an inevitable
application of visual surveillance. There are several techniques in
the literature which deal with vehicle detection, but the decrease
in visibility due to camera noise and unfavourable climatic
conditions due to snow, fog, rain, swaying leaves etc. makes it
difficult to detect the moving objects in the scene. This paper
proposes a framework to detect and track multiple moving
vehicles despite of occlusions. To detect and segment the moving
vehicles make use of dynamically adaptive threshold using the
modified full-search sum of absolute difference algorithm, which
reduces computational complexity. For tracking all the detected
objects uniquely, an algorithm using Kalman filter is p

Large cities with fleet of vehicles require a system
to determine location of movement of passenger vehicles at a
given time. Vehicle tracking systems can be used in theft
prevention, retrieval of lost vehicles, providing trafricoriented
services on lanes. The Vehicle tracking systems
VETRAC enables vehicle drivers or any third party to track
the location of any moving vehicle. Most modern vehicle
tracking systems use GPS[71 modules which is costly in usage
and implementation. Many systems also combine a
communications component such as cellular or satellite
transmitters to communicate the vehicle's location to a
remote user. VETRAC uses WiFi IEEE 802.11 b/g for easy
and accurate location of the vehicle, which provides effective
and simple communication. Vehicle information can be
viewed on electronic maps using the Internet or specialized
software. We have designed and developed an Intelligent
Vehicle Navigation System, which identify an optimally
minimal path for navigation with minimal traffic intensity
using WiFi. The system can also be used as a city guide to
locate and identify landmarks in a new city.

- by Aaron Weinberg
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- Biomedical Engineering, Telecommunications, Performance, Technological forecasting

Dynamic vehicle detection and tracking is crucial for self-driving in urban environments. Compared with traditional beam-model-based algorithms that cannot detect and track dynamic vehicles that are occluded by other objects, in this paper, we develop a novel dynamic vehicle detection and tracking algorithm to solve this problem for our Autonomous Land Vehicle (ALV), which is equipped with a Velodyne LIDAR and a GPS-aid Inertial Navigation System (INS). For detection, our improved two-dimensional virtual scan is presented to detect the potential dynamic vehicles with a scan differencing operation. Then for each potential dynamic vehicle, a novel likelihood-field-based vehicle measurement model is proposed to weight its possible poses. Finally, our newly modified Scaling Series algorithm and a generic particle filter are adopted to estimate the initial pose and the corresponding velocity for each vehicle, respectively. The Scaling Series algorithm coupled with a Bayesian Filter (SSBF) was previously used to handle the tactile localization problem in static background scenes. For tracking dynamic vehicles, we improve the SSBF by adding the ego-motion compensation so that the improved algorithm is able to update the pose and velocity for each vehicle in dynamic background scenes. Both the quantitative and qualitative experimental results validate the performance of our dynamic vehicle detection and tracking algorithm on the KITTI datasets and the Velodyne data collected by our ALV in dynamic urban environments.

- by Tongtong Chen
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- Vehicle Tracking Systems

ABSTRACT The objective of Part Two of this paper is to validate a prototype of an integrated navigation system linking Differential Global Positioning System DGPS and Inertial Measurement Unit IMU, described in more detail in Part One of the sequence. Part Two demonstrates an actual performance of the prototype mounted on a dedicated land vehicle. The paper at first characterises the landborne test-beds. Then it presents the methodology and list some results from the vehicular DGPS/IMU navigation experiments. In the final part the paper addresses the issue of the accuracy and integrity of the navigation solution. It gives the accuracy-wise summary in function of the land-test areas and an institutional summary in terms of the prototype DGPS/IMU system efficiency appraisal. The paper concludes presenting a rationale for a number of vehicle satellite/inertial navigation applications in Poland.
INTRODUCTION Part Two of this paper describes some results of the theoretical and experimental work on the Differential Global Positioning System DGPS integrated with the Inertial Measurement Unit IMU which has been completed by the author in Poland since 1996 . Part of the work has been done within the framework of the European Union Polish-German Joint Research Project (JRP) entitled : "Modernisation and accuracy improvement of the avionic and maritime navigation in Poland" and co-ordinated by the Institute of Flight Guidance and Control of the Technical University, Braunschweig, German y (TUBS.IFF) .Project's main scientific partner has been the Space Research Centre, Polish Academy of Sciences, Warsaw, Poland (PLAS.SRC) . In due course the Project's original aims expressed in its title have been extended in order to address also the need for improvement of the landborne navigation in Poland. The integrated satellite/inertial system, conceived during the Project's duration has been the main research tool. The system has comprised the DGPS and the Low-Cost IMU hardware and the dedicated Kalman filter based integration software. The van based experiments enabled testing of all important issues connected not only with the landborne but also with both waterborne and airborne environments. While the introductory experiments conducted in Germany answered mainly technical questions concerning the system, more advanced experiments conducted in Poland were supposed to be tailored well to specific applications and to have a more institutional background. The experimental data allowed to draw conclusions about three major physical effects that is: signal shadowing and attenuation, signal multipath, and signal jamming or saturation. The accuracy and integrity results allowed to evaluate the prototype DGPS/(Low-Cost IMU) performance and to address the issue of the system application in the landbome navigation in Poland. Notice: below, whenever the abbreviation D or IMU is placed between brackets [ ] it conveys the option of the particular mode of navigation; D signifies Differential GPS mode, IMU is understood below as a Low-Cost-IMU MOTIONPAK.

- by Gaurav Sharma
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- Generation, Vehicle Tracking Systems
- by Chun-yi Su
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- Engineering, Adaptive Control, Stability, Mathematical Sciences

This work presents the current state-of-the-art in techniques for tracking a number of objects moving in a coordinated and interacting fashion. Groups are structured objects characterized with particular motion patterns. The group can be comprised of a small number of interacting objects (e.g. pedestrians, sport players, convoy of cars) or of hundreds or thousands of components such as crowds of people. The group object tracking is closely linked with extended object tracking but at the same time has particular features which differentiate it from extended objects. Extended objects, such as in maritime surveillance, are characterized by their kinematic states and their size or volume. Both group and extended objects give rise to a varying number of measurements and require trajectory maintenance. An emphasis is given here to sequential Monte Carlo (SMC) methods and their variants. Methods for small groups and for large groups are presented, including Markov Chain Monte Carlo (MCMC) ...

- by François Septier and +1
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- Mechanical Engineering, Bayesian, MCMC, Monte Carlo Simulation

This work presents the current state-of-the-art in techniques for tracking a number of objects moving in a coordinated and interacting fashion. Groups are structured objects characterized with particular motion patterns. The group can be comprised of a small number of interacting objects (e.g. pedestrians, sport players, convoy of cars) or of hundreds or thousands of components such as crowds of people. The group object tracking is closely linked with extended object tracking but at the same time has particular features which differentiate it from extended objects. Extended objects, such as in maritime surveillance, are characterized by their kinematic states and their size or volume. Both group and extended objects give rise to a varying number of measurements and require trajectory maintenance. An emphasis is given here to sequential Monte Carlo (SMC) methods and their variants. Methods for small groups and for large groups are presented, including Markov Chain Monte Carlo (MCMC) methods, the random matrices approach and Random Finite Set Statistics methods. Efficient real-time implementations are discussed which are able to deal with the high dimensionality and provide high accuracy. Future trends and avenues are traced.

- by Lyudmila Mihaylova
- •
- Mechanical Engineering, Computer Science, Bayesian, MCMC

GPS (Global Positioning System) based tracking system has many applications in today's world, including vehicle tracking, child tracking, any equipment tracking, etc. These services offer many advantages to the mobile users to retrieve the information about their current location and process that data to get more useful information. The development of a bus tracking system for android based smartphone with the aim of enabling educational institution students, faculties and staffs to locate their buses with ease and in a convenient manner. The system consists of two sides, server side and client side. The client side provides the facility to the user to track buses remotely through the mobile network or WIFI and the server side's main responsibility is to provide the exact location of the bus to the server . Any type of user can see the live location of their desire bus with only 5 seconds of update interval. This will reduce unnecessary hassle and waiting time for the users....

In this paper we are interested in analyzing behaviour in crowded public places at the level of holistic motion. Our aim is to learn, without user input, strong scene priors or labelled data, the scope of "normal behaviour" for a particular scene and thus alert to novelty in unseen footage. The first contribution is a low-level motion model based on what we term tracklet primitives, which are scene-specific elementary motions. We propose a clustering-based algorithm for tracklet estimation from local approximations to tracks of appearance features. This is followed by two methods for motion novelty inference from tracklet primitives: (a) an approach based on a non-hierarchial ensemble of Markov chains as a means of capturing behavioural characteristics at different scales, and (b) a more flexible alternative which exhibits a higher generalizing power by accounting for constraints introduced by intentionality and goal-oriented planning of human motion in a particular scene. Evaluated on a 2h long video of a busy city marketplace, both algorithms are shown to be successful at inferring unusual behaviour, the latter model achieving better performance for novelties at a larger spatial scale.

The need to estimate a particular quantile of a distribution is an important problem which frequently arises in many computer vision and signal processing applications. For example, our work was motivated by the requirements of many semi-automatic surveillance analytics systems which detect abnormalities in close-circuit television (CCTV) footage using statistical models of low-level motion features. In this paper we specifically address the problem of estimating the running quantile of a data stream when the memory for storing observations is limited. We make several major contributions: (i) we highlight the limitations of approaches previously described in the literature which make them unsuitable for non-stationary streams, (ii) we describe a novel principle for the utilization of the available storage space, (iii) we introduce two novel algorithms which exploit the proposed principle in different ways, and (iv) we present a comprehensive evaluation and analysis of the proposed algorithms and the existing methods in the literature on both synthetic data sets and three large real-world streams acquired in the course of operation of an existing commercial surveillance system. Our findings convincingly demonstrate that both of the proposed methods are highly successful and vastly outperform the existing alternatives. We show that the better of the two algorithms (data-aligned histogram) exhibits far superior performance in comparison with the previously described methods, achieving more than 10 times lower estimate errors on real-world data, even when its available working memory is an order of magnitude smaller.

- by Ognjen Arandjelovic
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- Engineering, Applied Mathematics, Computer Science, Algorithms
- by baburao kodavati
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- RFID, Security, Encryption, Vehicle Tracking Systems
- by baburao kodavati
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- RFID, Security, Encryption, Vehicle Tracking Systems