Among the many approaches towards fuel economy, adoption of electric vehicles (EV) may have greatest impact. However, existing studies on EV predict very different market evolutions, which causes a lack solid ground for strategic decision making. New methodological tools, based Artificial Intelligence, might offer perspective. This paper proposes supervised Machine Learning (ML) techniques to i...

Existing single-lane free flow (SLFF) tolling systems either heavily rely on contact-based treadle sensor to detect the number of vehicle wheels or manual operator classify vehicles. While former is susceptible high maintenance cost due wear and tear, latter prone human error. This paper proposes a vision-based solution SLFF classification by adapting state-of-the-art object detection model as ...

Vehicle tracking is one of the important applications of wireless sensor networks. We consider an aspect of tracking: the classification of targets based on the acoustic signals produced by vehicles. In this paper, we present a naı̈ve classifier and simple distributed schemes for vehicle classification based on the features extracted from the acoustic signals. We demonstrate a novel way of using...

With ever-increasing number of car-mounted electric devices and their complexity, audio classification is increasingly important for the automotive industry as a fundamental tool for human-device interactions. Existing approaches for audio classification, however, fall short as the unique and dynamic audio characteristics of in-vehicle environments are not appropriately taken into account. In t...

Emotions and non-driving related cognitive tasks affect a driver’s control over a vehicle and may result in driving errors and traffic accidents. Presence of a monitoring device that would assess driver’s state could help reduce such errors by providing the driver with alerts and directing other in-vehicle active safety devices. The focus of this study is on the evaluation of speech production-...

The continuous rise in the number of vehicles in circulation brings an increasing need for automatically and efficiently recognizing vehicle categories for multiple applications such as optimizing available parking spaces, balancing ferry loads, planning infrastructure and managing traffic, or servicing vehicles. This paper explores the use of human visual attention mechanisms to identify a set...

Pedestrians are the most vulnerable road users. For evaluating and modifying pedestrian safety in unsignalized crosswalks,the first important issue is to identify and explore factors affecting the interaction behavior of pedestrians andvehicles in conflict areas. By analyzing those factors and determining how they affect road user's behavior, we canrepresent the plans and proc...

This paper presents a learning-based vehicle control system capable of navigating autonomously. Our approach is based on image processing, road and navigable area recognition, template matching classification for navigation control, and trajectory selection based on GPS way-points. The vehicle follows a trajectory defined by GPS points avoiding obstacles using a single monocular camera and main...