Publication Hub Archive

GPS

You have reached the Ergoneers Publication Hub for:

Used Tool > GPS

Find all Publications here:

Publication Hub

Total results: 129

Design and development of a low-cost smartphone-based research platform for real-world driving studies

Year: 2017

Authors: M Nefzger

Naturalistic driving studies as a method to explore driving and driver behaviour in a natural environment have become increasingly popular in road safety research. However, data acquisition systems needed for these studies are expensive and require a profound technical expertise for the installation. This thesis reports on an alternative approach towards more affordable naturalistic driving studies – a smartphone-based system called Sensor Platform that leverages the phone’s sensors as well as external sensors to gather relevant driving data. In close cooperation with road safety experts, this project aimed to specify the requirements for such a system, develop a prototype, and evaluate from an user perspective as well as from a technical point of view. A focus group and an in-vehicle user study were conducted to gather the expert’s feedback. In order to judge the accuracy of Sensor Platform, a comparison to an industry-grade data acquisition system was performed on the real road. The analysis of the study data suggests that road safety experts like the high usability and value the time savings. Yet, in comparison to industry-grade data acquisition systems, Sensor Platform is not on par when it comes to data accuracy, mainly due to simpler filtering algorithms. All in all, the thesis adds to the knowledge of mobile data acquisition systems while also providing a basis for future road safety applications such as real-time interventions.

Eye Tracking Glasses
Software

2 versions available

Division of area of fixation interest for real vehicle driving tests

Year: 2017

Authors: Q Xu,T Guo, F Shao, X Jiang

The area of interest (AOI) reflects the degree of attention of a driver while driving. The division of AOI is visual characteristic analysis required in both real vehicle tests and simulated driving scenarios. Some key eye tracking parameters and their transformations can only be obtained after the division of AOI. In this study, 9 experienced and 7 novice drivers participated in real vehicle driving tests. They were asked to drive along a freeway section and a highway section, wearing the Dikablis eye tracking device. On average, 8132 fixation points for each driver were extracted. After coordinate conversion, the MSAP (Mean Shift Affinity Propagation) method is proposed to classify the distribution of fixation points into a circle type and a rectangle type. Experienced drivers’ fixation behavior falls into the circle type, in which fixation points are concentrated. Novice drivers’ fixation points, which are decentralized, are illustrated in the rectangle type. In the clustering algorithm, the damping coefficient λ determines the algorithm convergence, and the deviation parameter p mainly affects the number of clusters, where larger p values generate more clusters. This study not only provides the cluster type and cluster counts, but also presents the borderlines for each cluster. The findings provide significant contribution to eye tracking research.

Eye Tracking Glasses
Simulator

9 versions available

Driven to distraction? A review of speech technologies in the automobile

Year: 2017

Authors: R Young, J Zhang

Speech technologies hold the promise of improving driver performance for many visual-manual secondary tasks, by enabling eyes-free and hands-free interactions. Unfortunately, speech interfaces have enjoyed only incremental growth since the early 2000s in the automotive industry. Instead, mixed-mode interfaces (speech combined with visual) have become increasingly common, and visual-manual interfaces are still dominant. This paper provides a historical overview of speech driver interface studies, including formal testing on a 2014 Toyota Corolla production vehicle, and a new analytical evaluation of the Apple CarPlay interface in the 2016 Cadillac ATS. Results indicate that eyes-free and hands-free speech (i.e., “pure” speech) improves driver performance vs. mixed-mode interfaces. Also, mixed-mode improves driver performance vs. “pure” visual-manual, for the tasks tested. The visual component of the mixed-mode and visual-manual interfaces increases off-road glances, a safety decrement. We recommend that future in-vehicle speech interface products should sensibly limit visual displays from showing information redundant to that provided by the speech interface. In general, we recommend pure speech driver-vehicle interfaces for secondary tasks wherever possible.

Simulator
Software

2 versions available

Driving simulator development with two degrees of freedom motion for driver behavior study

Year: 2017

Authors: MFM Siam, N Borhan, A Sukardi

This paper discusses about the development of a driving simulator with 2 Degree of Freedom (DOF) motion platform as a data collection tool for driver behavior research. The simulator was installed with motion platform, steering wheel, pedals, transmission, screens, computer, simulation software and sound system to record the driving behaviors in simulated traffic environment. Data containing information such as participants’ response time, vehicle speed, acceleration, braking, turn signals use and vehicle positioning were collected. This paper also discusses the benefits of driving simulator development for driver behavior research while addressing its challenge and limitation for future improvement. The paper concludes that the driving simulator development can contribute significantly to road safety research specifically in driver behavior study.

Simulator
Software

2 versions available

ERTMS pilot in the Netherlands–impact on the train driver

Year: 2017

Authors: R Van der Weide, D De Bruijn, M Zeilstra

In 2014 the Ministry of Transport decided for implementation of ERTMS (European Railway Traffic Management System) on the main corridors in Holland. A pilot with ERTMS was performed between the cities of Amsterdam and Utrecht. This paper describes effects of ERTMS on workload and human error of the train driver by comparing driving in conventional (ATB), in ERTMS with Dual Signalling and in ERTMS L2-only train protection. This was done using driving performance data, a simulator experiment, workshops and surveys.

Simulator
Software

1 version available:

Gaze direction when driving after dark on main and residential roads: Where is the dominant location?

Year: 2017

Authors: J Winter,S Fotios,S Völker

CIE Joint Technical Committee JTC-1 has requested data regarding the size and shape of the distribution of drivers’ eye movement in order to characterize visual adaptation. This paper reports the eye movement of drivers along two routes in Berlin after dark, a main road and a residential street, captured using eye tracking. It was found that viewing behaviour differed between the two types of road. On the main road eye movement was clustered within a circle of approximately 10° diameter, centred at the horizon of the lane. On the residential street eye movement is clustered slightly (3.8°) towards the near side, eye movements were best captured with either an ellipse of approximate axes 10° vertical and 20° horizontal, centred on the lane ahead, or a 10° circle centred 3.8° towards the near side. These distributions reflect a driver’s tendency to look towards locations of anticipated hazards.

Simulator
Software

6 versions available

Hazard Perception Test via Driving Simulator

Year: 2017

Authors: N Borhan,MKA Ibrahim, AA Ab Rashid, MFM Siam

Hazard Perception Test (HPT) is one (1) of longstanding approach in many countries to assess individuals’ competency before obtaining driving licenses. In Malaysia, however, HPT is yet to be part of the national licensing system. Previous hazard perception studies using Malaysian samples reported mixed findings on the effectivity of reaction time-based HPT (e.g. Lim, Sheppard & Crundall, 2013; Ab Rashid & Ibrahim, 2017). Unlike these studies that adopted computer-based HPT, current study employed a full-size cabin driving simulator to study hazard perception between two (2) groups of drivers: novice and experienced. Results from 28 (15 novices, 13 experienced) drivers indicated that novice drivers detected hazards faster than their experienced counterpart, even though both groups have the same performance of hazard recognition. Correlational analysis revealed that driving frequency might be a factor contributing to the difference of response time between these two (2) groups. Further analysis also indicates that different road environments contribute to different hazard perception performance. It is recommended that hazard perception test should be put as a part of the national licensing system and the potential of driving simulator as a HPT tool can be explore more.

Simulator
Software

1 version available:

New motion cueing algorithm for improved evaluation of vehicle dynamics on a driving simulator

Year: 2017

Authors: W Brems, N Kruithof, R Uhlmann, A Wagner

In recent years, driving simulators have become a valuable tool in the automotive design and testing process. Yet, in the field of vehicle dynamics, most decisions are still based on test drives in real cars. One reason for this situation can be found in the fact that many driving simulators do not allow the driver to evaluate the handling qualities of a simulated vehicle. In a driving simulator, the motion cueing algorithm tries to represent the vehicle motion within the constrained motion envelope of the motion platform. By nature, this process leads to so called false cues where the motion of the platform is not in phase or moving in a different direction with respect to the vehicle motion. In a driving simulator with classical filter-based motion cueing, false cues make it considerably more difficult for the driver to rate vehicle dynamics. A team with members from the University of Stuttgart, Cruden B.V., and AUDI AG developed a new motion cueing methodology for the use in a driving simulator dedicated to vehicle dynamics. The new algorithm is a track based approach that makes use of the vehicle’s position on the track and does not use high-pass filters. It therefore allows minimization of false cues, thereby giving the driver the best possible information on the handling qualities of the car. In this paper, the basic principles of the algorithm are described, as well as the implementation in a driving simulator. Comparison with data from a handling track shows the advantages of the new methodology over the classical motion cueing approach.

Simulator
Software

2 versions available

Online recognition of driver-activity based on visual scanpath classification

Year: 2017

Authors: C Braunagel, D Geisler,W Rosenstiel

The next step towards the fully automated vehicle is the level of conditional automation, where the automated driving system can take over the control and responsibility for a limited time interval. Nevertheless, take-over situations may occur, forcing the driver to resume the driving task. Despite such situations, the driver is able to perform secondary tasks during conditionally automated driving, hence a low take-over quality must be expected. Methods for Driver-Activity Recognition (DAR) usually extract features for the classification within a moving time window. In this paper, the first DAR architecture based on the driver's scanpath, which is extracted by means of dynamic clustering and symbolic aggregate approximation patterns, is introduced. To demonstrate the potential of this approach, it is compared to a state-of-the-art method based on the data of a driving simulator study with 82 subjects. The classification performance of both DAR approaches was examined for decreasing window sizes with regard to the recognition of different secondary tasks and the separability of drivers using a handheld or hands-free device. Compared to the state-of-the-art approach, the proposed method shows a classification accuracy increase of nearly 20%, a significant improvement of the overall classification performance, and is able to classify the secondary tasks of the driver even for short windows of a duration of 5 s, i.e. with little information.

Simulator
Software

3 versions available

Spatial perception of landmarks assessed by objective tracking of people and Space Syntax techniques

Year: 2017

Authors: L Ourique,S Eloy,R Resende,JM Dias

This paper focuses on space perception and how visual cues, such as landmarks, may influence the way people move in a given space. Our main goal with this research is to compare people’s movement in the real world with their movement in a replicated virtual world and study how landmarks influence their choices when deciding among different paths. The studied area was a university campus and three spatial analysis techniques were used: space syntax; an analysis of a Real Environment (RE) experiment; and an analysis of a Virtual Reality (VR) environment replicating the real experiment. The outcome data was compared and analysed in terms of finding the similarities and differences, between the observed motion flows in both RE and VR and also with the flows predicted by space syntax analysis. We found a statistically significant positive correlation between the real and virtual experiments, considering the number of passages in each segment line and considering fixations and saccades at the identified landmarks (with higher visual Integration). A statistically significant positive correlation, was also found between both RE and VR and syntactic measures. The obtained data enabled us to conclude that: i) the level of visual importance of landmarks, given by visual integration, can be captured by eye tracking data ii) our virtual environment setup is able to simulate the real world, when performing experiments on spatial perception.

Simulator
Software

7 versions available