Vehicle Tracking Services Research Articles

Design of a Public Vehicle Tracking Service Using Long-Range (LoRa) and Intelligent Transportation System Architecture

Public transport vehicles are involved in a high percentage of traffic accidents in intermediate cities, mainly due to speeding and lack of control over their routing. In addition, many passengers of these vehicles report poor quality of service. To try to improve this, the authors propose a system to provide a public transport vehicle tracking service with high quality regarding accessibility, safety, and comfort. They developed an ITS architecture for this type of city following a methodology, they constructed a detailed service diagram using the ITS architecture and quality requirements, and finally, they selected the adequate wireless communication technology for the service. They determined that an IoT-based system, with LoRaWAN technology and considering the developed ITS architecture, provides the service with the required characteristics. They also analyzed the use of the proposed service design in the case of an intermediate Colombian city, determining the required components, network, and budget.

Experimental Evaluation of LoRa in Transit Vehicle Tracking Service Based on Intelligent Transportation Systems and IoT

Long-range (LoRa) technology is a low power wide area network (LPWAN) technology that is currently being used for development of Internet of things (IoT)-based solutions. Transit transport, mainly in medium-sized cities where transit vehicles do not have exclusive lanes, is a service that can be improved with a tracking service using technology such as LoRa. Although some proposals exist, there is not enough experimental information to validate the LoRa technology as adequate. This article: (a) evaluates the operation of LoRa technology in a transit vehicle tracking service in a medium-sized city, based on an Intelligent Transportation Systems architecture and IoT; and (b) investigates optimal LoRa technology configuration parameters for the service. Experiments were performed in a semi-controlled environment using LoRa devices and a gateway, by measuring the received packets and the receive signal strength indicator (RSSI) and modifying: (a) distance; (b) number of devices; and (c) the main LoRa transmission parameters. Obtained results show the ideal values of parameters vary considerably with distance and number of devices used. There were very few settings of the experiments in which the RSSI and packet levels were adequate while distance and number of devices were both changed.

Sustainable transit vehicle tracking service, using intelligent transportation system services and emerging communication technologies: A review

Abstract The most salient problems of transit vehicle service in Latin American intermediate cities include: the high number of passengers involved in traffic accidents; traffic congestion caused by transit vehicles, and pollution generated by these vehicles, which increases in high congestion scenarios. To improve upon this situation, a research was conducted on the transit vehicle tracking service, which is a basic service for implementing mobility solutions for the aforementioned problems, the most relevant characteristics of this service for the context of Latin American intermediate cities were identified, and an implementation was proposed. This paper presents the four stages of the study: (a) a review of the state-of-the-art of services or systems related to vehicle tracking, including wireless communications technologies, implemented sustainability approaches, usage of special algorithms for efficiency improvement, and the intelligent transportation system (ITS) architecture used as a basis; (b) the process of identifying relevant characteristics of the service for a given context; (c) proposal of an ITS architecture for this service in an intermediate city, its requirements and the suggested technologies; and (d) development of experiments for validating usage of the key suggested technologies. The review allowed to identify the main service characteristics, with regard to vehicle positioning technologies, the recommended wireless communication technology (long range, LoRa), energy consumption considerations, and use of artificial intelligence (AI) to calculate waiting time of users at bus stops. Finally, an ITS architecture for the city of Popayan (Colombian city) considering the aforementioned characteristics is proposed, and the experiments related to the use of these technologies are described in detail.

Traffic Light Controlling for Emergency Vehicle Line Based on GPS Tracking and Position Using GPRS Network

In big and metropolitan city, traffic jam is common problem and often to be occured. And that is the most critical problem for emergency vehicles. Where time and urgency are the most priority to be handled. In this research, emergency vehicle was utilized with any GPS device. The vehicle tracking service is provided for real time tracking. We use open source vehicle tracking framework/server Traccar. The same as with common GPS device, the emergency vehicle continusously sends its latitude, longitude and speed to GPS server. The research focused on Traffic Light Device which built of ESP32 microcontroller, GPRS module Air202 and battery power supply with charging function. While emergency vehicle reports its position to GPS server, the traffic light device continuously checks the emergency vehicle’s position data from the GPS server. The idea is to take the advantage of GPS server API, where traffic light device using HTTP GET communication with implementation of embedded cookies, session and keep alive to access the GPS server API. Traffic light device then calculates straight distance to emergency vehicle based on its predefined fixed latitude and longitude. If emergency vehicle located within the user defined threshold radius of traffic light device, then the traffic light turn green to allow emergency vehicle for passed its line. As the result of this research, traffic light device has been successfully read emergency vehicle device’s location data and measured their distance within 1 to 2 seconds.

Where Will You Park? Predicting Vehicle Locations for Vehicle-to-Grid

Vehicle-to-grid services draw power or curtail demand from electric vehicles when they are connected to a compatible charging station. In this paper, we investigated automated machine learning for predicting when vehicles are likely to make such a connection. Using historical data collected from a vehicle tracking service, we assessed the technique’s ability to learn and predict when a fleet of 48 vehicles was parked close to charging stations and compared this with two moving average techniques. We found the ability of all three approaches to predict when individual vehicles could potentially connect to charging stations to be comparable, resulting in the same set of 30 vehicles identified as good candidates to participate in a vehicle-to-grid service. We concluded that this was due to the relatively small feature set and that machine learning techniques were likely to outperform averaging techniques for more complex feature sets. We also explored the ability of the approaches to predict total vehicle availability and found that automated machine learning achieved the best performance with an accuracy of 91.4%. Such technology would be of value to vehicle-to-grid aggregation services.

An Integrated Methodology Using PROMETHEE and Kano’s Model to Rank Strategic Decisions

This paper puts forward a framework that assists managers to prepare action plans using attributes of Kano’s Model and to order them by utilizing multi-criteria decision analysis. The framework was applied in a company, a division of which provides a vehicle tracking service. Data were collected on its top 10 customers, all of which are large companies. The results show the proposed framework contributes to the decision-making process, since it enables the order of the actions to be rationalized, and takes the multiple criteria relevant to the company into consideration. Moreover, the fact that it is difficult to rank the 20 actions needed without the approach proposed in this article reinforces the need for and the importance of the framework and other complementary contributions in order to overcome this difficulty.

A cost-effective decentralized vehicle remote positioning and tracking system using BeiDou Navigation Satellite System and Mobile Network

Most existing production vehicle tracking services rely on the Global Positioning System (GPS) and a proprietary server/client infrastructure. This type of inflexible and centralized architecture incurs severe vender-dependency and high service cost. In this paper, we propose a cost-effective decentralized vehicle remote positioning and tracking system architecture. This architecture only consists of two components: (1) a vehicle terminal for collecting real-time vehicle location from a navigation satellite system and report it to a user terminal via the existing mobile network and (2) a user terminal on a mobile phone for analyzing the location information from (1) and inform the owner. We prototype the positioning and tracking system using the BeiDou Navigation Satellite System (BDS) and Global System for Mobile Communication(GSM) Network. Experiment results illustrate that the system is capable of tracking vehicle location and warning the owner if the vehicle unexpectedly moves more than 100 m at low cost. With maximum vender-neutrality and high-availability as the design philosophy, the system is able to utilize multiple available navigation satellite systems and mobile networks.

Caracterização de padrões do comportamento espacial de veículos (monitorados) em movimento - PCEVM

Resumo No Brasil existe a perspectiva de crescimento expressivo do volume de dados a ser processado pelas prestadoras de serviços de rastreamento de veículos em decorrência do aumento natural do uso de sistemas de rastreamento. Esse crescimento gera a necessidade da incorporação de ferramentas analíticas nos sistemas de gerenciamento do rastreamento e monitoramento de veículos e na gestão de risco, para aumentar a sua eficiência e atender ao crescimento do mercado. O presente estudo tem como objetivo o desenvolvimento de um modelo para identificação do Padrão de Comportamento Espacial de Veículos em Movimento – PCEVM, utilizando uma ferramenta de análise espacial para auxiliar o processo de tomada de decisão no monitoramento de veículos e na gestão do sistema de transporte urbano. Embora os resultados obtidos sejam válidos para a particular configuração apresentada neste artigo, a metodologia de análise proposta permite a caracterização de padrões espaciais de movimentação de veículos na área e no período considerados, o que é útil, por exemplo, para planejadores municipais, empresas de logística e empresas seguradoras. Conclui-se que o resultado da comparação entre o posicionamento coletado em tempo real com o modelo de distribuição espacial obtido na caracterização dos padrões de comportamento espaciais é capaz de detectar anormalidades do comportamento de movimentação do veículo e oferecer subsídios para a tomada de decisão em sistemas de monitoramento e gerenciamento de veículos, que visem à segurança patrimonial e pessoal, identificando comportamentos de movimentação não esperados ou de comportamentos de risco.

Virtual Sensors

Recent advances in mobile networks and an increase in the number of GPS-equipped vehicles have led to exponential growth in real-time data generation. In the past decade, several online mapping and vehicle tracking services have made their data available to third-party users. This paper explores opportunities for use of real-time traffic data provided by online services and introduces a virtual sensor methodology for collecting, storing, and processing large volumes of network-level data. To assess the validity of the collected data with the proposed methodology, this paper compares these data with data from physical loop detectors and electronic toll tag readers. Statistical analyses show a strong correlation between the travel time measurements from infrastructure-based sensors and virtual sensors. A travel time reliability analysis is then conducted with the virtual sensor data methodology. The results are promising for future research and implementation.