Joel Gonçalves

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With the number of in-vehicle information systems and the complexity of their tasks growing at a very high rate in near future, we need a clear understanding of their related distraction or mental workload and its impact on driver performance. Thus, in this paper we introduce these concepts already in the development phase of a product that will be used in(More)
The incorporation of Augmented Reality (AR) in the windshield of automobiles using heads-up displays (HUD) is starting to be implemented by some manufacturers and is proving to be very useful in some situations, including safety distance keeping. This paper reports on a system that warns the driver via the car's HUD when he violates the predefined safety(More)
Mobile applications are becoming increasingly more complex and making heavier demands on local system resources. Moreover, mobile systems are nowadays more open, allowing users to add more and more applications, including third-party developed ones. In this perspective, it is increasingly expected that users will want to execute in their devices(More)
Sensor technology available in smartphones enables the monitoring of mobility patterns, which could be of particular interest for the transportation sector. For example, driving time information can help to determine if a selected path is the most convenient. Moreover, measurements related to the time expended on the road and origin destination matrices can(More)
A collision probability estimator in the advent of an emergency Take Over Request (TOR) that considers the driver reaction time and the driver state is an essential tool for developing driver assistance systems for Highly Automated Driving (HAD). In this paper we present an architecture for capturing the driver state and behavior inside the vehicle. This(More)
Traveling with children in tow can pose a serious distraction to the driver, effectively drawing much of the necessary attention away from the road and causing a disruption in normal driving patterns. In this paper we investigate the driver's capacity to operate a vehicle safely when being exposed to a noise stimulus, specifically in the form of a crying(More)
The development of Advanced Driver Assistance Systems (ADAS) is rapidly growing. However, most of the ADAS require field test, which is expensive, unpredictable and time consuming. In this paper we propose a multiagent-based driving simulator which integrates a human factor analysis suite and enables rapid and low-cost experimentation of mobile-device ADAS.(More)
Fatigue and drowsiness can play an important role in Conditional Automation (CA), as drowsy drivers may fail to properly recover control. In order to provide better insight in the effects of drowsy driving in Take Over Request (TOR), we designed a driving experiment that extends related literature in drowsiness research CA with self-rated subjective(More)