CORDIS provides links to public deliverables and publications of HORIZON projects.
Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .
Exploitable results
The AIDE Integrated Project (IP) has been set up to address 'human-machine interface' (HMI) issues within a general European joint effort towards the large-scale deployment of Intelligent Road Safety Systems and, ultimately, a significant reduction of road accidents. HMI designs for maximising the safety benefits of new Advanced Driver Assistance Systems (ADAS).
Today, a wide range of ADAS are being developed to enhance the driver's perception of the hazards, and/or partly automating the driving task. These include speed alert, lane support/blind spot detection, automated safe following, pedestrian detection, vision enhancement and driver impairment monitoring. These systems have great potential for reducing accidents, in particular the great portion related to human error.
The safety impact of these systems depends to a great extent to be determined by their interaction with the driver. For example, in order to efficiently support the driver in avoiding crashing into a front obstacle, it is crucial that the warning/feedback given by the system intuitively generates the appropriate response (e.g. an avoidance manoeuvre). New technologies, exploiting new concepts for driver-vehicle interaction in multiple sensory modalities (e.g. visual, tactile and auditory), offer great potential for maximising the potential safety benefits of ADAS. Research and development on how to best exploit these possibilities to maximise the efficiency of ADAS is urgently needed.
Moreover, it is well known that the introduction of new safety functions may induce longer-term changes in driver behaviour. This type of behavioural change, often referred to as behavioural adaptation, may significantly affect the actual (as compared to the expected) safety benefits of a safety measure, both in positive and negative directions. Behavioural effects demonstrated for ADAS include system over-reliance on in-vehicle safety technologies resulting diversion of attention from the driving task and safety margin compensation.
However, the mechanisms underlying these effects are largely unknown and a model for predicting them does not exist. Finally, the potential safety impact of an ADAS ultimately depends on its market penetration rate and whether it is actually used by drivers.
Here, the human-machine interface is of crucial importance; annoying system behaviour (e.g. nuisance warnings) will lead to drivers simply abandoning the system, which hence obviously loses its potential safety benefit. HMI design for minimising workload and distraction imposed by In-vehicle Information Systems (IVIS). In addition to ADAS, a growing number of IVIS are being introduced in modern vehicles. By contrast to ADAS, these systems provide services not directly relevant for the primary driving task and thus impose a secondary tasks on the driver. Moreover, the in-vehicle use of portable computing devices; e.g. hand-held mobile phones and portable digital assistants (PDAs), often referred to as Nomad devices, is increasing rapidly.
These systems have great potential for increasing mobility and comfort. For example, fleet management systems enhance the efficiency of work in the freight industry and road-and traffic information systems potentially facilitate the quality of life for the commuter. However, information systems in vehicles may also compete with the primary driving task for the driver's attention and hence induce dangerous levels of distraction and workload. The safety risks of IVIS are well known, in particular the case of mobile phones.
Given this critical safety impact of mobile phones alone, the introduction of additional information functions such as email, internet access, navigation aids, road and traffic information raises obvious safety concerns. Nomad devices are not even designed for use while driving and are, thus, major potential future on-board distractions. The design of the HMI of IVIS and nomad devices is of key importance for minimising the workload and distraction that they impose on the driver. Methods and criteria are needed to validate these systems with respect to their potential negative safety effects.
The general objective of the AIDE IP is to generate the knowledge and develop methodologies and human-machine interface technologies required for safe and efficient integration of ADAS, IVIS and nomad devices into the driving environment.
The objectives of AIDE were:
- to maximise the efficiency, and hence the safety benefits, of advanced driver assistance systems;
- to minimise the level of workload and distraction imposed by in-vehicle information systems and nomad devices;
- to enable the potential benefits of new in-vehicle technologies and nomad devices in terms of mobility and comfort.
Specifically, the goal of the AIDE IP was to design, develop and validate a generic Adaptive Integrated Driver-vehicle Interface (AIDE) which:
- maximises the efficiency of individual and combined advanced driver assistance systems by means of innovative, integrated and adaptive, human-machine interface concepts that prevent negative behavioural effects (e.g. under-load, over-reliance and safety margin compensation). It also maximises positive effects (e.g. enhanced situational awareness), thereby enhancing the safety benefits of these systems. AIDE should demonstrate significantly enhanced safety benefits compared to existing solutions;
- reduces the level of workload and distraction related to the interaction with individual and combined in-vehicle information and nomad devices, thereby reducing the number of road accidents. AIDE should demonstrate a significant reduction in the imposed workload and distraction compared to existing solutions;
- enables the potential benefits of new in-vehicle technologies and nomad devices in terms of mobility and comfort, without compromising safety.
AIDE IP generated the knowledge and developed methodologies and HMI technologies required for safe and efficient integration of ADAS, IVIS and nomad devices into the driving environment.
These three major lines of development were carried out in parallel exchanging information and data while work progressed towards the final overall DVE-predicting model/simulation:
- develop a basic understanding of the DVE interaction and the behavioural effects of IVIS and ADAS,
- develop this into a model, and
- computer simulation for predicting these effects.
In specific, five support systems; namely, ISA, CC, SL, FCW and LDW were studied. The methods that were used can be broadly grouped, according to the data collected, into two categories: those that provide subjective data on how participants describe their adaptation to a given support system (this is the case in the INRETS - Renault and PSA - TNO studies) and those that provide objective data on participants' driving behaviour after long-term exposure to a particular system based on various measures of vehicle parameters (this is the case in the Leeds - VTI and CERTH/HIT studies).
Searching for OpenAIRE data...
There was an error trying to search data from OpenAIRE
No results available