vehicle location
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2022 ◽  
Vol 60 ◽  
pp. 402-409
Author(s):  
Sara Mozzoni ◽  
Massimo Di Francesco ◽  
Giulio Maternini ◽  
Benedetto Barabino

2021 ◽  
Author(s):  
Ruben Leon ◽  
Alexis Tinoco ◽  
Daniela Cando ◽  
Manolo Paredes ◽  
Fernando Lara

Author(s):  
Pedro Baptista ◽  
Margarida Rodrigues ◽  
Marcelo Costa ◽  
Pedro Martins ◽  
Maryam Abbasi

Author(s):  
Dr. Pradnya Mathurkar ◽  
Akansha B. Somkuwar ◽  
Ashwini R. Thakre ◽  
Pranali M. Wasnik

A vehicle tracking system is very useful for tracking the movement of a vehicle from any location at any time. An efficient vehicle tracking system is designed and implemented for tracking the movement of any equipped vehicle from any location at any time. The proposed system made good use of popular technology that combines a smartphone with an Arduino UNO. This easy to make and inexpensive compared to others. The designed in vehicle device works using Global Positioning System (GPS) and Global System for Mobile Communication(GSM) technology that is one of the most common ways for vehicle tracking. The device is embedded inside a vehicle those positions is to be determined and tracked in real time. A vehicle tracking system is an electronic device installed in a vehicle to enable the owner or a third party to track the vehicle's location. This paper proposed to design a vehicle tracking system that works using GPS and GSM technology, which would be the cheapest source of vehicle tracking and it would work as anti-theft system. It is an embedded system which is used for tracking and positioning of any vehicle by using Global Positioning System (GPS) and Global system for mobile communication (GSM). An Arduino UNO is used to control the GPS receiver and GSM module. The vehicle tracking system uses the GPS module to get geographic coordinates at regular time interval. The GSM module is used to transmit and update the vehicle location to a database. This paper gives minute by minute update about vehicle location by sending SMS through GSM modem. This SMS contain latitude and longitude of the location of vehicle. Arduino UNO gets the coordinates from GPS modem and then it sends this information to user in text SMS. GSM modem is used to send this information via SMS sent to the owner of the vehicle. Location is displayed on LCD. And then Google map displays location and name of the place on cell phone. Thus, user able to continuously monitor a moving vehicle on demand using smartphone and determine the estimated distance and time for the vehicle to arrive at a given destination.


2021 ◽  
Author(s):  
Bassim Ibrahim.

Vehicle arrival time is one of the most important factors of intelligent transportation systems (ITS). Accurate transit travel information is important because it attracts additional customers and increases the satisfaction of transit users. A passenger waiting for a train or bus, a person waiting for a cab, a customer waiting for a courier to come to his/her home to pickup or deliver a package, a business office waiting for a truck for goods and a home user waiting for his/her shipment for which he/she did online shopping are a few examples of how important vehicle arrival time is in different areas of life. Most companies are investing a lot of money to improve their systems for better, faster and reliable customer service. As the cost of ITS components have decreased, the automatic vehicle location (AVL) system, which is one component of ITS, has become more widely used. Many transit agencies use an AVL system to track their vehicles in real-time. Tracking systems technology was made possible by the integration of three technologies: global positioning system (GPS), global system for mobile communication (GSM) and the geographic information system (GIS). This project shows detailed research in the area of automatic vehicle location and implements a low cost vehicle tracking system using GPS and GPRS. The system reads the current position, speed and direction using GPS, the data is sent via GPRS service from a GSM network to a server using TCP/IP protocol and the server saves this information to the database on a regular time interval. The web-based application then uses this data and calculates the approximate arrival time. The system allows a user to view the present position of the vehicle using Google Maps and calculates the arrival time. Also, bus location can be monitored in real time by route supervisors. This will allow supervisors to make better service adjustment decisions because they will be able to see how the route is operating. The test bed was a bus route running in the downtown of Toronto.


2021 ◽  
Author(s):  
Bassim Ibrahim.

Vehicle arrival time is one of the most important factors of intelligent transportation systems (ITS). Accurate transit travel information is important because it attracts additional customers and increases the satisfaction of transit users. A passenger waiting for a train or bus, a person waiting for a cab, a customer waiting for a courier to come to his/her home to pickup or deliver a package, a business office waiting for a truck for goods and a home user waiting for his/her shipment for which he/she did online shopping are a few examples of how important vehicle arrival time is in different areas of life. Most companies are investing a lot of money to improve their systems for better, faster and reliable customer service. As the cost of ITS components have decreased, the automatic vehicle location (AVL) system, which is one component of ITS, has become more widely used. Many transit agencies use an AVL system to track their vehicles in real-time. Tracking systems technology was made possible by the integration of three technologies: global positioning system (GPS), global system for mobile communication (GSM) and the geographic information system (GIS). This project shows detailed research in the area of automatic vehicle location and implements a low cost vehicle tracking system using GPS and GPRS. The system reads the current position, speed and direction using GPS, the data is sent via GPRS service from a GSM network to a server using TCP/IP protocol and the server saves this information to the database on a regular time interval. The web-based application then uses this data and calculates the approximate arrival time. The system allows a user to view the present position of the vehicle using Google Maps and calculates the arrival time. Also, bus location can be monitored in real time by route supervisors. This will allow supervisors to make better service adjustment decisions because they will be able to see how the route is operating. The test bed was a bus route running in the downtown of Toronto.


2021 ◽  
Vol 11 (10) ◽  
pp. 4594
Author(s):  
Xianyun Xu ◽  
Huifang Chen ◽  
Lei Xie

During the procedure, a location-based service (LBS) query, the real location provided by the vehicle user may results in the disclosure of vehicle location privacy. Moreover, the point of interest retrieval service requires high accuracy of location information. However, some privacy preservation methods based on anonymity or obfuscation will affect the service quality. Hence, we study the location privacy-preserving method based on dummy locations in this paper. We propose a vehicle location privacy-preservation method based on dummy locations under road restriction in Internet of vehicles (IoV). In order to improve the validity of selected dummy locations under road restriction, entropy is used to represent the degree of anonymity, and the effective distance is introduced to represent the characteristics of location distribution. We present a dummy location selection algorithm to maximize the anonymous entropy and the effective distance of candidate location set consisting of vehicle user’s location and dummy locations, which ensures the uncertainty and dispersion of selected dummy locations. The proposed location privacy-preservation method does not need a trustable third-party server, and it protects the location privacy of vehicles as well as guaranteeing the LBS quality. The performance analysis and simulation results show that the proposed location privacy-preservation method can improve the validity of dummy locations and enhance the preservation of location privacy compared with other methods based on dummy locations.


Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3077
Author(s):  
Ikram Ullah ◽  
Munam Ali Shah ◽  
Abid Khan ◽  
Carsten Maple ◽  
Abdul Waheed

Location privacy is a critical problem in the vehicular communication networks. Vehicles broadcast their road status information to other entities in the network through beacon messages to inform other entities in the network. The beacon message content consists of the vehicle ID, speed, direction, position, and other information. An adversary could use vehicle identity and positioning information to determine vehicle driver behavior and identity at different visited location spots. A pseudonym can be used instead of the vehicle ID to help in the vehicle location privacy. These pseudonyms should be changed in appropriate way to produce uncertainty for any adversary attempting to identify a vehicle at different locations. In the existing research literature, pseudonyms are changed during silent mode between neighbors. However, the use of a short silent period and the visibility of pseudonyms of direct neighbors provides a mechanism for an adversary to determine the identity of a target vehicle at specific locations. Moreover, privacy is provided to the driver, only within the RSU range; outside it, there is no privacy protection. In this research, we address the problem of location privacy in a highway scenario, where vehicles are traveling at high speeds with diverse traffic density. We propose a Dynamic Grouping and Virtual Pseudonym-Changing (DGVP) scheme for vehicle location privacy. Dynamic groups are formed based on similar status vehicles and cooperatively change pseudonyms. In the case of low traffic density, we use a virtual pseudonym update process. We formally present the model and specify the scheme through High-Level Petri Nets (HLPN). The simulation results indicate that the proposed method improves the anonymity set size and entropy, provides lower traceability, reduces impact on vehicular network applications, and has lower computation cost compared to existing research work.


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