Date of Award
Doctor of Philosophy (PhD)
Intelligent transportation systems (ITS) use different methods to collect and process traffic data. Conventional techniques suffer from different challenges, like the high installation and maintenance cost, connectivity and communication problems, and the limited set of data. The recent massive spread of smartphones among drivers encouraged the ITS community to use them to solve ITS challenges.
Using smartphones in ITS is gaining an increasing interest among researchers and developers. Typically, the set of sensors that comes with smartphones is utilized to develop tools and services in order to enhance safety and driving experience. GPS, cameras, Bluetooth, inertial sensors and other embedded sensors are used to detect and analyze drivers' behavior and vehicles' motion.
The use of smartphones made the data collection process easier because of their availability among drivers, the set of different sensors, the computation ability, and the low installation and maintenance cost. On the other hand, different smartphones sensors have diverse characteristics and accuracy and each one of them needs special fusion, processing, and filtration methods to generate more stable and accurate data. Using smartphones in ITS faces different challenges like inaccurate readings, weak GPS reception, noisy sensors and unaligned readings.These challenges waste researchers and developers time and effort, and they prevent them from building accurate ITS applications.
This work proposes SenSys a smartphone framework that collects and processes traffic data and then analyzes and extracts vehicle dynamics and vehicle activities which can be used by developers and researchers to create their navigation, communication, and safety ITS applications. SenSys framework fuses and filters smartphone's sensors readings which result in enhancing the accuracy of tracking and analyzing various vehicle dynamics such as vehicle's stops, lane changes, turn detection, and accurate vehicle speed calculation that, in turn, will enable development of new ITS applications and services.
Alasaadi, Abdulla A.. "SenSys: A Smartphone-Based Framework for ITS applications" (2017). Doctor of Philosophy (PhD), dissertation, Computer Science, Old Dominion University, https://digitalcommons.odu.edu/computerscience_etds/34
Available for download on Tuesday, October 09, 2018