Browsing by Keyword "intelligent transportation systems"
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Item An Efficient and Scalable Simulation Model for Autonomous Vehicles with Economical Hardware(2021-03) Sajjad, Muhammad; Irfan, Muhammad; Muhammad, Khan; Ser, Javier Del; Sanchez-Medina, Javier; Andreev, Sergey; Ding, Weiping; Lee, Jong Weon; IAAutonomous vehicles rely on sophisticated hardware and software technologies for acquiring holistic awareness of their immediate surroundings. Deep learning methods have effectively equipped modern self-driving cars with high levels of such awareness. However, their application requires high-end computational hardware, which makes utilization infeasible for the legacy vehicles that constitute most of today's automotive industry. Hence, it becomes inherently challenging to achieve high performance while at the same time maintaining adequate computational complexity. In this paper, a monocular vision and scalar sensor-based model car is designed and implemented to accomplish autonomous driving on a specified track by employing a lightweight deep learning model. It can identify various traffic signs based on a vision sensor as well as avoid obstacles by using an ultrasonic sensor. The developed car utilizes a single Raspberry Pi as its computational unit. In addition, our work investigates the behavior of economical hardware used to deploy deep learning models. In particular, we herein propose a novel, computationally efficient, and cost-effective approach. The designed system can serve as a platform to facilitate the development of economical technologies for autonomous vehicles that can be used as part of intelligent transportation or advanced driver assistance systems. The experimental results indicate that this model can achieve real-time response on a resource-constrained device without significant overheads, thus making it a suitable candidate for autonomous driving in current intelligent transportation systems.Item A review of travel time estimation and forecasting for Advanced Traveller Information Systems(2015-02-07) Mori, Usue; Mendiburu, Alexander; Álvarez, Maite; Lozano, Jose A.; BIGDATADue to the increase in vehicle transit and congestion in road networks, providing information about the state of the traffic to commuters has become a critical issue for Advanced Traveller Information Systems. These systems should assist users in making pre-trip and en-route decisions and, for this purpose, delivering travel time information is very useful because it is very intuitive and easily understood by all travellers. The aim of this paper is to present a global view of the literature on the modelling of travel time, introducing essential concepts and giving a thorough classification of the existing techniques. Most of the attention will focus on travel time estimation and travel time prediction, which are two of the most relevant challenges in travel time modelling. The definition and goals of these two modelling tasks along with the methodologies used to carry them out will be further explored and categorised.