Cristina Olaverri-Monreal

Making Vehicles Transparent Through V2V Video Streaming

The advent of infrastructureless vehicle-to-vehicle (V2V) communication has opened the opportunity to design driver-assistance systems that collect information from sensors residing in neighboring vehicles. Windshield-installed cameras are one example of a sensor that is becoming common in modern vehicles. Remotely accessing real-time images of these cameras using V2V communication enables a significant increase in the visual awareness of each driver. In this paper, we propose and evaluate the performance of a driver-assistance system that leverages on V2V communication and windshield-installed cameras to transform vision-obstructing vehicles into transparent tubular objects. This cooperative system is able to increase the visibility of drivers intending to overtake, thus making such critical maneuvers safer. Our system uses an augmented reality human-machine interface that is able to convey the increased visibility perspective in a straightforward fashion. We also show that the required latency for this intervehicle communication can be obtained using the Dedicated Short-Range Communications (DSRC) proposed for vehicular environments.

IC-DEEP: A serious games based application to assess the ergonomics of in-vehicle information systems

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 an in-vehicle environment. We present the IC-DEEP (In-Car Ergonomics Evaluation Platform), which is an implementation approach in form of a Serious Game (SG) to autonomously assess, under low-time and low-cost conditions, the factors that can jeopardize the driving performance when manipulating or receiving information from in-vehicle information systems (IVISs). We evaluate the feasibility of the proposed approach and draw conclusions on its effects on behavioral changes and IVIS assessment.

How Electric Vehicles Affect Driving Behavioral Patterns

The gradual introduction of fully electrically powered vehicles into the market has extended the opportunities for sustainable mobility and a new technological era. In this paper we investigate the changes in driver behavior patterns compared with patterns of traditional vehicles with combustion engines after having acquired the necessary adjustments needed for driving an electric vehicle. We aim to expound upon the differences present in driving habits after the individual has become adjusted to the driving patterns of an electric vehicle. Results showed that there is a significant difference in the driving habits of an internal combustion vehicle and that of an electric vehicle. Particularly a development from stronger accelerating and decelerating within the first experiences with electric vehicles to a more calm driving after 5 months of experience was noticeable in acceleration and braking maneuvers. Additionally, results for constant driving proved that interaction with electric vehicles with one-pedal driving capability is not a barrier for efficient driving with constant velocity.

Forward collision warning systems using heads-up displays: Testing usability of two new metaphors

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 cars HUD when he violates the predefined safety distance, to avoid a possible forward collision, and proposes two different visualization metaphors based on traffic signals. The metaphors are compared, with and without warning sounds, through computer simulations performed by 22 participants from different age groups and driving experiences. One of the metaphors corresponds to a variant of the traffic sign C10 that forbids circulating from the preceding vehicle shorter than a certain minimum headway, whereas the other corresponds to the road safety marks, which recommend the safety distance to be observed from the vehicle ahead. Results show that the metaphor derived from the safety marks, with warning sounds, is preferred by the participants, and was considered the most useful, intuitive and adequate to a forward collision warning. We also found that this metaphor was preferred by all participants that were 42 or more years old, whereas participants between 28 and 41 years old were divided between the two metaphors, with warning sounds.

Driver-centric VANET simulation

Inter-vehicle communication is becoming increasingly relevant in the research and development of novel, innovative vehicular applications. To support the driver in his/her primary driving task in an effective non distracting way, these applications need to be evaluated in a realistic context from a drivers perspective of the VANET environment. In this paper we propose an innovative driver-centric simulation tool that integrates a VANET simulator with a driving simulator using communication technologies to relay information about the vehicle to the VANET environment and vice versa. The driver behavior is reflected in the VANET simulation system affecting the mobility of the cars in the vicinity and providing the intelligent driving model with new realistic features.

User experience evaluation in an automotive context

Tough competition in the automobile market makes it very important to exceed customer expectations with in-vehicle devices or applications in order to stand out in an already saturated market. Research on human-machine interaction (HMI) showed that user satisfaction is not only influenced by usability factors but also by user experience (UX). Since UX in the automotive context has not yet been comprehensively investigated, this article presents a feasible research method for the measurement of UX. We rely on the fulfillment of psychological needs as a user experience measurement and conducted three online surveys to develop a questionnaire for that purpose. We analyze nine need scales, each with 10 items, and reduced the item count afterwards for a shorter form of the questionnaire. Results reveal that the method successfully measured the intended needs. Future work with respect to a further extension and improvement of the method is discussed.

P2V and V2P communication for Pedestrian warning on the basis of Autonomous Vehicles

The use of smartphones in a road context by drivers and Vulnerable Road Users (VRU) is rapidly increasing. To reduce the risks related to the influence of smartphone usage in a situation where traffic needs to be considered, a collision prediction algorithm is proposed based on Pedestrian to Vehicle (P2V) and Vehicle to Pedestrian (V2P) communication technologies, which increases the visual situational awareness of VRU regarding the nearby location of both autonomous and manually-controlled vehicles in a user-friendly form. The proposed application broadcasts the devices position to the vehicles nearby, and reciprocally, the vehicles nearby broadcast their position to the device in use, supporting pedestrians and other VRU to minimize potential dangers and increase the acceptance of autonomous vehicles on our roads. Results regarding the evaluation of the proposed approach showed a good performance and high detection rate, as well as a high user satisfaction derived from the interaction with the system.

In-vehicle displays: Driving information prioritization and visualization

Systems developed to be operated in a vehicular environment have gradually begun to include further applications, which can be found in other mobile environments, such as smart phones and tablets. This continued growth could overwhelm the driver and affect road safety. Thus, it is crucial to ensure that these devices provide the type of information drivers need. This paper focuses on the presentation of in-vehicle information while driving. Function clusters and information prioritization for different modules in Driver Information Systems are primarily investigated through driver preferences analysis. Results are evaluated outlining implications for proper location of information on the in-vehicle displays.

Driver Capability Monitoring in Highly Automated Driving: From State to Capability Monitoring

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 system is then used to predict the collision probability in the situation where drivers resolve the TOR doing a keep lane maneuver (KLM) and brake to avoid the collision. Since this maneuver can be executed safely even under fast reactions, we use it as a reference to determine if is it safe for transferring the vehicle control to the driver.

Sensing Bluetooth Mobility Data: Potentials and Applications

Information related to mobility dynamics constitutes an important factor to be considered in traffic management to improve the efficiency of existing systems. We present a proof-of-concept deployment of sensors using the Bluetooth technology to detect traffic flow conditions. Besides traditional method consisting of a network of stationary sensors, we present a novel approach that uses sensors deployed in moving vehicles that allows new type studies and captures new insights of mobility. Both approaches complement the most common methods of traffic sensing while being more cost-effective and easily available. Early experimental results show the variety of information available through both approaches spanning from Origin/Destination matrices and travel times to insights into emerging mobile neighborhoods. These metrics are important to improve traffic management increasing the efficiency of urban mobility networks.