The DRIVE-SAFE project: signal processing and advanced information technologies for improving driving prudence and accidents

In this paper, we will talk about the Drivesafe project whose aim is creating conditions for prudent driving on highways and roadways with the purposes of reducing accidents caused by driver behavior. To achieve these primary goals, critical data is being collected from multimodal sensors (such as cameras, microphones, and other sensors) to build a unique databank on driver behavior. We are developing system and technologies for analyzing the data and automatically determining potentially dangerous situations (such as driver fatigue, distraction, etc.). Based on the findings from these studies, we will propose systems for warning the drivers and taking other precautionary measures to avoid accidents once a dangerous situation is detected. In order to address these issues a national consortium has been formed including Automotive Research Center (OTAM), Koç University, Istanbul Technical University, Sabancı University, Ford A.S., Renault A.S., and Fiat A. Ş

Driver’s Distraction and Understandability of Using GPS Navigation

GPS navigation is available on smartphone application providing turn-by-turn navigation instruction on smartphones and the distraction from GPS usage while driving also became an issue. In this paper, we present the strategy to mitigate the level of distraction by manipulating the type of display visual (2D and 3D) and placement (right, steer and left). We conducted field experiments in left-hand real traffic with 12 subjects. Our result illustrated that 3D conditions implied much fewer frequency of eye glances (FOG) than 2D conditions. Furthermore, steer conditions has much higher FOG than right and left placement conditions, but we found no significant effects on the ease of understanding (EOU) for visual display difference and the number of error for all conditions

Safe driving in a green world : a review of driver performance benchmarks and technologies to support ‘smart’ driving

Road transport is a significant source of both safety and environmental concerns. With climate change and fuel prices increasingly prominent on social and political agendas, many drivers are turning their thoughts to fuel efficient or ‘green’ (i.e., environmentally friendly) driving practices. Many vehicle manufacturers are satisfying this demand by offering green driving feedback or advice tools. However, there is a legitimate concern regarding the effects of such devices on road safety – both from the point of view of change in driving styles, as well as potential distraction caused by the in-vehicle feedback. In this paper, we appraise the benchmarks for safe and green driving, concluding that whilst they largely overlap, there are some specific circumstances in which the goals are in conflict. We go on to review current and emerging in-vehicle information systems which purport to affect safe and/or green driving, and discuss some fundamental ergonomics principles for the design of such devices. The results of the review are being used in the Foot-LITE project, aimed at developing a system to encourage ‘smart’ – that is safe and green – driving

Driven to distraction: Determining the effects of roadside advertising on driver attention

There is growing concern that roadside advertising presents a real risk to driving safety, with conservative estimates putting external distractors responsible for up to 10% of all accidents. In this report, we present a simulator study quantifying the effects of billboards on driver attention, mental workload and performance in Urban, Motorway and Rural environments. The results demonstrate that roadside advertising has a clear detrimental effect on lateral control, increases mental workload and eye fixations, and on some roads can draw attention away from more relevant road signage. Detailed analysis of the data suggests that the effects of billboards may in fact be more consequential in scenarios which are monotonous or of lower workload. Nevertheless, the overriding conclusion is that prudence should be exercised when authorising or placing roadside advertising. The findings are discussed with respect to governmental policy and guidelines.Final report of a study funded by The Rees Jeffreys Road Fun

Design of a data-driven communication framework as personalized support for users of ADAS

Recently the automotive industry has made a huge leap forward in Automated Driver Assistance Systems (ADAS) development, increasing the level of driving processes automation. However, ADAS design does not imply any individual support to the driver; this results in a poor understanding of how the ADAS works and its limitations. This type of driver uncertainty regarding ADAS performance can erode the user\u27s trust in the system and result in decreasing situations when the system is in use. This paper presents the design of a data-driven communication framework that can utilize historical and real-time vehicle data to support ADAS users. The data-driven communication framework aims to illustrate the ADAS capabilities and limitations and suggests effective use of the system in real-time driving situations. This type of assistance can improve a driver\u27s understanding of ADAS functionality and encourage its usage

Voice-controlled in-vehicle infotainment system

Abstract. Speech is a form of a human to human communication that can convey information in a context-rich way that is natural to humans. The naturalness enables us to speak while doing other things, such as driving a vehicle. With the advancement of computing technologies, more and more personal services are introduced for the in-vehicle environment. A limiting factor for these advancements is the impact they cause towards driver distraction with the increased cognitive stress load. This has led to developing in-vehicle devices and applications with a heightened focus on lessening distraction. Amazon Alexa is a natural language processing system that enables its users to receive information and operate smart devices with their voices. This Master’s thesis aims to demonstrate how Alexa could be utilized when operating the in-vehicle infotainment (IVI) systems. This research was conducted by utilizing the design science research methodology. The feasibility of voice-based interaction was assessed by implementing the system as a demonstrable use-case in collaboration with the APPSTACLE project. Prior research was gathered by conducting a literature review on voice-based interaction and its integration to the vehicular domain. The system was designed by applying existing theories together with the requirements of the application domain. The designed system utilized the Amazon Alexa ecosystem and AWS services to provide the vehicular environment with new functionalities. Access to cloud-based speech processing and decision-making makes it possible to design an extendable speech interface where the driver can carry out secondary tasks by using their voice, such as requesting navigation information. The evaluation was done by comparing the system’s performance against the derived requirements. With the results of the evaluation process, the feasibility of the system could be assessed against the objectives of the study: The resulting artefact enables the user to operate the in-vehicle infotainment system while focusing on a separate task. The research proved that speech interfaces with modern technology can improve the handling of secondary tasks while driving, and the resulting system was operable without introducing additional distractions to the driver. The resulting artefact can be integrated into similar systems and used as a base tool for future research on voice-controlled interfaces

A user experience‐based toolset for automotive human‐machine interface technology development

The development of new automotive Human-Machine Interface (HMI) technologies must consider the competing and often conflicting demands of commercial value, User Experience (UX) and safety. Technology innovation offers manufacturers the opportunity to gain commercial advantage in a competitive and crowded marketplace, leading to an increase in the features and functionality available to the driver. User response to technology influences the perception of the brand as a whole, so it is important that in-vehicle systems provide a high-quality user experience. However, introducing new technologies into the car can also increase accident risk. The demands of usability and UX must therefore be balanced against the requirement for driver safety. Adopting a technology-focused business strategy carries a degree of risk, as most innovations fail before they reach the market. Obtaining clear and relevant information on the UX and safety of new technologies early in their development can help to inform and support robust product development (PD) decision making, improving product outcomes. In order to achieve this, manufacturers need processes and tools to evaluate new technologies, providing customer-focused data to drive development. This work details the development of an Evaluation Toolset for automotive HMI technologies encompassing safety-related functional metrics and UX measures. The Toolset consists of four elements: an evaluation protocol, based on methods identified from the Human Factors, UX and Sensory Science literature; a fixed-base driving simulator providing a context-rich, configurable evaluation environment, supporting both hardware and software-based technologies; a standardised simulation scenario providing a repeatable basis for technology evaluations, allowing comparisons across multiple technologies and studies; and a technology scorecard that collates and presents evaluation data to support PD decision making processes

A Voice and Pointing Gesture Interaction System for Supporting Human Spontaneous Decisions in Autonomous Cars

Autonomous cars are expected to improve road safety, traffic and mobility. It is projected that in the next 20-30 years fully autonomous vehicles will be on the market. The advancement on the research and development of this technology will allow the disengagement of humans from the driving task, which will be responsibility of the vehicle intelligence. In this scenario new vehicle interior designs are proposed, enabling more flexible human vehicle interactions inside them. In addition, as some important stakeholders propose, control elements such as the steering wheel and accelerator and brake pedals may not be needed any longer. However, this user control disengagement is one of the main issues related with the user acceptance of this technology. Users do not seem to be comfortable with the idea of giving all the decision power to the vehicle. In addition, there can be location awareness situations where the user makes a spontaneous decision and requires some type of vehicle control. Such is the case of stopping at a particular point of interest or taking a detour in the pre-calculated autonomous route of the car. Vehicle manufacturers\u27 maintain the steering wheel as a control element, allowing the driver to take over the vehicle if needed or wanted. This causes a constraint in the previously mentioned human vehicle interaction flexibility. Thus, there is an unsolved dilemma between providing users enough control over the autonomous vehicle and route so they can make spontaneous decision, and interaction flexibility inside the car. This dissertation proposes the use of a voice and pointing gesture human vehicle interaction system to solve this dilemma. Voice and pointing gestures have been identified as natural interaction techniques to guide and command mobile robots, potentially providing the needed user control over the car. On the other hand, they can be executed anywhere inside the vehicle, enabling interaction flexibility. The objective of this dissertation is to provide a strategy to support this system. For this, a method based on pointing rays intersections for the computation of the point of interest (POI) that the user is pointing to is developed. Simulation results show that this POI computation method outperforms the traditional ray-casting based by 76.5% in cluttered environments and 36.25% in combined cluttered and non-cluttered scenarios. The whole system is developed and demonstrated using a robotics simulator framework. The simulations show how voice and pointing commands performed by the user update the predefined autonomous path, based on the recognized command semantics. In addition, a dialog feedback strategy is proposed to solve conflicting situations such as ambiguity in the POI identification. This additional step is able to solve all the previously mentioned POI computation inaccuracies. In addition, it allows the user to confirm, correct or reject the performed commands in case the system misunderstands them

A DATA-DRIVEN APPROACH TO SUPPORTING USERS’ ADAPTATION TO SMART IN-VEHICLE SYSTEMS

The utilization of data to understand user behavior and support user needs began to develop in areas such as internet services, smartphone apps development, and the gaming industry. This bloom of data-driven services and applications forced OEMs to consider possible solutions for better in-vehicle connectivity. However, digital transformation in the automotive sector presents numerous challenges. One of those challenges is identifying and establishing the relevant user-related data that will cover current and future needs to help the automotive industry cope with the digital transformation pace. At the same time, this development should not be sporadic, without a clear purpose or vision of how newly-generated data can support engineers to create better systems for drivers. The important issue is to learn how to extract the knowledge from the immense data we possess, and to understand the extent to which this data can be used.Another challenge is the lack of established approaches towards vehicle data utilization for user-related studies. This area is relatively new to the automotive industry. Despite the positive examples from other fields that demonstrate the potential for data-driven context-aware applications, automotive practices still have gaps in capturing the driving context and driver behavior. This lack of user-related data can partially be explained by the multitasking activities that the driver performs while driving the car and the higher complexity of the automotive context compared to other domains. Thus, more research is needed to explore the capacity of vehicle data to support users in different tasks.Considering all the interrelations between the driver and in-vehicle system in the defined context of use helps to obtain more comprehensive information and better understand how the system under evaluation can be improved to meet driver needs. Tracking driver behavior with the help of vehicle data may provide developers with quick and reliable user feedback on how drivers are using the system. Compared to vehicle data, the driver’s feedback is often incomplete and perception-based since the driver cannot always correlate his behavior to complex processes of vehicle performance or clearly remember the context conditions. Thus, this research aims to demonstrate the ability of vehicle data to support product design and evaluation processes with data-driven automated user insights. This research does not disregard the driver’s qualitative input as unimportant but provides insights into how to better combine quantitative and qualitative methods for more effective results.According to the aim, the research focuses on three main aspects:•\ua0\ua0\ua0\ua0\ua0 Identifying the extent to which vehicle data can contribute to driver behavior understanding.\ua0 •\ua0\ua0\ua0\ua0\ua0 Expanding the concepts for vehicle data utilization to support drivers.•\ua0\ua0\ua0\ua0\ua0 Developing the methodology for a more effective combination of quantitative (vehicle data-based) and qualitative (based on users’ feedback) studies. Additionally, special consideration is given to describing the drawbacks and limitations, to enhance future data-driven applications

Future directions for the development of Virtual Reality within an automotive manufacturer

Virtual Reality (VR) can reduce time and costs, and lead to increases in quality, in the development of a product. Given the pressure on car companies to reduce time-to-market and to continually improve quality, the automotive industry has championed the use of VR across a number of applications, including design, manufacturing, and training. This paper describes interviews with 11 engineers and employees of allied disciplines from an automotive manufacturer about their current physical and virtual properties and processes. The results guided a review of research findings and scientific advances from the academic literature, which formed the basis of recommendations for future developments of VR technologies and applications. These include: develop a greater range of virtual contexts; use multi-sensory simulation; address perceived differences between virtual and real cars; improve motion capture capabilities; implement networked 3D technology; and use VR for market research