A critical overview of driver recording tools

Ζιακόπουλος, Απόστολος; Tselentis, Dimitrios I.; Kontaxi, Armira; Yannis, George

doi:10.1016/j.jsr.2019.12.021

Cited by 36 publications

(22 citation statements)

References 73 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In contrast to simulator studies, on-road controlled studies, FOTs, and NDSs utilize participants driving real vehicles in naturalistic settings. The major difference is that in an onroad controlled study, the experimenter has a higher level of control on specific variables of interest [45]. For example, in an on-road controlled study, participants are asked to drive on the same route as other drivers while driving in the same experimentally equipped vehicle (in contrast to driving their own personal vehicle).…”

Section: B On-road Controlled Studies and Field Operational Tests (Fot)mentioning

confidence: 99%

HARMONY: A Human-Centered Multimodal Driving Study in the Wild

et al. 2021

View full text Add to dashboard Cite

Effective shared autonomy requires a clear understanding of driver's behavior, which is governed by multiple psychophysiological and environmental variables. Disentangling this intricate web of interactions requires understanding the driver's state and behaviors in different real-world scenarios, longitudinally. Naturalistic Driving Studies (NDS) have shown to be an effective approach to understanding the driver's state and behavior in real-world scenarios. However, due to the lack of technological and computing capabilities, former NDS only focused on vision-based approaches, ignoring important psychophysiological factors such as cognition and emotion. The main objective of this paper is to introduce HARMONY, a human-centered multimodal naturalistic driving study, where driver's behaviors and states are monitored through (1) in-cabin and outside video streams (2) physiological signals including driver's heart rate and hand acceleration (IMU data), (3) ambient noise, light, and the vehicle's GPS location, and (4) music logs, including song features such as tempo. HARMONY is the first study that collects long-term naturalistic facial, physiological, and environmental data simultaneously. This paper summarizes HARMONY's goals, framework design, data collection and analysis, and the on-going and future research efforts. Through a presented case study, we first demonstrate the importance of longitudinal driver state sensing through using Kernel Density Estimation Methods. Second, we leverage the application of Bayesian Change Point detection methods to demonstrate how we can identify driver behaviors and responses to the environmental conditions by fusing psychophysiological information with features extracted from video streams.INDEX TERMS Naturalistic driving study, physiological sensing,driver state detection, shared-autonomy, contextual awareness, human-in-the-loop systems

show abstract

Section: B On-road Controlled Studies and Field Operational Tests (Fot)mentioning

confidence: 99%

HARMONY: A Human-Centered Multimodal Driving Study in the Wild

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Another common issue within the studies that aimed at understanding drivers' behavior in Malaysia is the use of inadequate and biased techniques for data collection such as surveys, questionnaires, simulations, and on-road observations using cameras, which were heavily criticized in the literature [9,10,[22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38]. As a result, collecting naturalistic driving data (NDD) using in-vehicle sensors emerged as a crucial data source with high ecological reliability [39,40].…”

Section: Introductionmentioning

confidence: 99%

Investigating the Effect of Social and Cultural Factors on Drivers in Malaysia: A Naturalistic Driving Study

Al-Hussein

Kiah

Por

et al. 2021

IJERPH

View full text Add to dashboard Cite

Road accidents are increasing every year in Malaysia, and it is always challenging to collect reliable pre-crash data in the transportation community. Existing studies relied on simulators, police crash reports, questionnaires, and surveys to study Malaysia’s drivers’ behavior. Researchers previously criticized such methods for being biased and unreliable. To fill in the literature gap, this study presents the first naturalistic driving study in Malaysia. Thirty drivers were recruited to drive an instrumented vehicle for 750 km while collecting continuous driving data. The data acquisition system consists of various sensors such as OBDII, lidar, ultrasonic sensors, IMU, and GPS. Irrelevant data were filtered, and experts helped identify safety criteria regarding multiple driving metrics such as maximum acceptable speed limits, safe accelerations, safe decelerations, acceptable distances to vehicles ahead, and safe steering behavior. These thresholds were used to investigate the influence of social and cultural factors on driving in Malaysia. The findings show statistically significant differences between drivers based on gender, age, and cultural background. There are also significant differences in the results for those who drove on weekends rather than weekdays. The study presents several recommendations to various public and governmental sectors to help prevent future accidents and improve traffic safety.

show abstract

“…For example, receiving traffic accident information via mobile apps has changed for recording driver behavior. According to recent studies, receiving information about driving behavior through traditional models such as questionnaires, Police report studies, and direct observation has been replaced with new approaches, including [ 17 ]: Driving simulator: This type of device is designed to imitate driving and enables a safe, virtual environment for testing driver behavior characteristics. Naturalistic driving: This includes installing instruments such as In-Vehicle Data Recorders (IVDRs) and On-Board Diagnostics (OBDs) tools in the vehicle to capture information about driving behavior in the real world.…”

Section: Introductionmentioning

confidence: 99%

Mobile applications for road traffic health and safety in the mirror of the Haddon’s matrix

Aghayari

Kalankesh

Sadeghi‐Bazargani

et al. 2021

BMC Med Inform Decis Mak

View full text Add to dashboard Cite

Background Road traffic accidents have been one of the leading causes of death. Despite the increasing trend of road traffic apps, there is no comprehensive analysis of their features and no taxonomy for the apps based on traffic safety theories. This study aimed to explore the characteristics of available mobile apps on road traffic health/safety and classify them with emphasis on Haddon’s matrix. Methods The researchers examined the mobile applications related to road traffic health/safety using qualitative content analysis. Google Play was searched using a combination of the keywords. Haddon’s matrix was applied to analyze and classify those mobile apps residing in the categories of Road Traffic health & Safety, and Road Traffic Training. Results Overall, 913 mobile apps met the inclusion criteria and were included in the final analysis. Classification of the apps based on their features resulted in 4 categories and 21 subcategories. A total number of 657 mobile apps were classified based on Haddon’s matrix. About 45.67% of these apps were categorized as the road traffic health & safety group. Conclusions Haddon’s matrix appears to have the potential to reveal the strengths and weaknesses of existing mobile apps in the road traffic accident domain. Future development of mobile apps in this domain should take into account the existing gap.

show abstract

A critical overview of driver recording tools

Cited by 36 publications

References 73 publications

HARMONY: A Human-Centered Multimodal Driving Study in the Wild

HARMONY: A Human-Centered Multimodal Driving Study in the Wild

Investigating the Effect of Social and Cultural Factors on Drivers in Malaysia: A Naturalistic Driving Study

Mobile applications for road traffic health and safety in the mirror of the Haddon’s matrix

Contact Info

Product

Resources

About