SAE Light Controller - Automatic vehicle location using mobile devices

• Autor(a) principal: Cristiano Dias de Seabra
• Data de Publicação: 2017
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: https://hdl.handle.net/10216/106179
• topic: Engenharia electrotécnica, electrónica e informática; Electrical engineering, Electronic engineering, Information engineering

Automatic Vehicle Location (AVL) is a means for automatically determining and transmitting the geographic location of a vehicle. Nowadays, Global Positioning System (GPS) is the most stable implementation of satellite-based location systems, therefore being the most common way of determining a vehicle's location in AVL systems. Currently, in major cities, public transports have a very accurate, but very expensive, AVL system installed in each vehicle, making it unaffordable for smaller public transport operators to acquire this kind of equipment. On the other hand, GPS-enabled mobile devices are becoming increasingly more ubiquitous while their processing power and batteries are improving. This work intends to propose the use of mobile devices as an alternative to traditional AVL systems for public transports. These devices represent a cheaper option for public transport oper- ators which would provide smaller companies with a more cost-efficient method of keeping track of the positions of their automotive vehicles. Furthermore, this work also intends to propose an algorithm for the identification, in real-time, of deviations from the planned schedule. The first step consists in analysing algorithms for geolocation in order to identify the most accurate one, given the public transport's predefined route. The second step is the implementation of an AVL's interface and functionality for mobile devices for the calculation of the Travel Time Prediction (TTP). The third step is the development of an algorithm, using Kalman filters, that predicts schedule deviations in real-time and informs bus drivers and passengers of them. Finally, the last step is to compare the obtained results of this system with the one already in use on the market, regarding the cost-efficiency relation between them, in order to determine the viability of the developed system for use in public transportation.