Is naturalistic driving research possible with highly instrumented cars? Lessons learnt in three research centres

Valero‐Mora, Pedro M.; Tontsch, Anita; Welsh, Ruth; Morris, Andrew P.; Reed, Steven; Touliou, Katerina; Margaritis, Dimitris

doi:10.1016/j.aap.2012.12.025

Cited by 22 publications

(16 citation statements)

References 11 publications

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“…70, 133 Naturalistic driving techniques objectively measure driver performance over extended periods (weeks or months) in the driver’s own vehicle, where the individual drives as they would normally during the course of everyday life. Study personnel are not in the vehicle.…”

Section: Performancementioning

confidence: 99%

A roadmap for interpreting the literature on vision and driving

Owsley

Wood

McGwin

2015

Survey of Ophthalmology

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Over the past several decades there has been a sharp increase in the number of studies focused on the relationship between vision and driving. The intensified scientific attention to this topic has most likely been stimulated by the lack of an evidence-basis for determining vision standards for driving licensure and a poor understanding about how vision impairment impacts driver safety and performance. Clinicians depend on the scientific literature on vision and driving as a resource to appropriately advise visually impaired patients about driving fitness. Policy makers also depend on the scientific literature in order to develop guidelines that are evidence-based and are thus fair to persons who are visually impaired. Thus it is important for clinicians and policy makers alike to understand how various study designs and measurement methods should be appropriately interpreted so that the conclusions and recommendations they make based on this literature are not overly broad, too narrowly constrained, or even misguided. In this overview, based on our 25 years of experience in this field, we offer a methodological framework to guide interpretations of studies on vision and driving, which can also serve as a heuristic for researchers in the area. Here we discuss research designs and general measurement methods for the study of vision as they relate to driver safety, driver performance, and driver-centered (self-reported) outcomes.

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Section: Performancementioning

confidence: 99%

A roadmap for interpreting the literature on vision and driving

Owsley

Wood

McGwin

2015

Survey of Ophthalmology

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“…However, it is often excessive for most research purposes, which complicates the successive tasks of the handling, managing, processing and analysis of the data. Therefore, we recommend introducing a preliminary phase in any study to give careful consideration to the right balance between the research aims and how the vehicle should be instrumented [22].…”

Section: Discussionmentioning

confidence: 99%

GIS Mapping of Driving Behavior Based on Naturalistic Driving Data

Balsa-Barreiro

Valero‐Mora

Berné-Valero

et al. 2019

IJGI

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Naturalistic driving can generate huge datasets with great potential for research. However, to analyze the collected data in naturalistic driving trials is quite complex and difficult, especially if we consider that these studies are commonly conducted by research groups with somewhat limited resources. It is quite common that these studies implement strategies for thinning and/or reducing the data volumes that have been initially collected. Thus, and unfortunately, the great potential of these datasets is significantly constrained to specific situations, events, and contexts. For this, to implement appropriate strategies for the visualization of these data is becoming increasingly necessary, at any scale. Mapping naturalistic driving data with Geographic Information Systems (GIS) allows for a deeper understanding of our driving behavior, achieving a smarter and broader perspective of the whole datasets. GIS mapping allows for many of the existing drawbacks of the traditional methodologies for the analysis of naturalistic driving data to be overcome. In this article, we analyze which are the main assets related to GIS mapping of such data. These assets are dominated by the powerful interface graphics and the great operational capacity of GIS software.Undoubtedly, one of the most interesting topics related to traffic and transportation issues is road safety [16]. This is highly complex and goes beyond the number of deaths and injuries in crashes within a certain period. Road fatalities have a huge impact, not only in terms of the number of casualties, but also in terms of the costs related to caring for the injured people, the disruption of traffic flows just after accidents, and so forth [17]. For this reason, it becomes increasingly important to deploy prevention policies to manage infrastructures and road flows as well as to provide a quick and efficient response in emergencies [18].Most studies analyze road safety by considering the different elements that are involved, such as the vehicle, driver, road, and infrastructure. However, they generally do it by isolating one of these elements separately or assessing the interaction of two elements at most. Some recent studies suggest the growing need for integrating the maximum number of elements that can affect driving performance to ensure a bigger picture of the whole driving scenario. Thus, more light is shed on why a certain incident happens and under what circumstances [19].In the last few years, the naturalistic driving method has gained more relevance. This research method aims to characterize the driving behavior of people in real-world situations. In order to do that, the different elements and factors involved in the driving performance are recorded using a large array of sensors and video cameras inconspicuously installed in the vehicle. This equipment allows data related to the driving performance to be collected at high temporal rates. These kinds of data are collected using massive and blind strategies. They are massive because their aim is to collec...

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“…This research was focused on incidents and enabled the detailed analysis of such situations, which involve high vehicle dynamical solicitations. This approach allows avoiding classical problems encountered in most of NDS studies due to the large amount of data, like the transfer, the storage and the exploitation (Valero-Mora et al, 2013;Csepinszky et al, 2012).…”

Section: Discussionmentioning

confidence: 99%

“…These NDS studies have shown that the link between crashes and incidents could exist, even though it is difficult to generalize. As explained by Valero-Mora et al (2013), the interest of NDS is real, but the huge amount of data requires a lot of time and resources to be transferred and analysed. They presented the other inconveniences of NDS: the common use of conspicuous and costly equipment, and the fact that participants do not use their own car, which may induce a riskier behaviour.…”

Section: Introductionmentioning

confidence: 99%

Acquisition and analysis of road incidents based on vehicle dynamics

Naude¹,

Serre²,

Dubois-Lounis³

et al. 2019

Accident Analysis & Prevention

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Because motor vehicle crashes have decreased during the last decade in many countries in the world and are more diffuse, local authorities have difficulties to define road safety policies. An experiment with 51 cars of public fleets equipped with a specific Event Data Recorder was carried out in France during one year. The purposes of this research were to evaluate if incident data (critical driving situations) help to understand crashes, and to explore a new way for road infrastructure safety diagnosis. The analysis of 339 genuine incidents and 1237 simple events recorded illustrates the potentiality of such an experiment and provides: some insights about conditions in which incidents occur, a general overview of their distribution according to different road layouts, as well as information on the different levels of accelerations reached. It can be noticed that there is an overrepresentation of incidents in right curves compared to left curves. The simple events involving mostly the infrastructure could be used to detect road defects. Genuine incidents where the vehicle is subjected to important dynamic demands, related to potentially unsafe driving situations, can be used to improve knowledge of the motor vehicle crashes thanks to incident mechanisms analysis.

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Is naturalistic driving research possible with highly instrumented cars? Lessons learnt in three research centres

Cited by 22 publications

References 11 publications

A roadmap for interpreting the literature on vision and driving

A roadmap for interpreting the literature on vision and driving

GIS Mapping of Driving Behavior Based on Naturalistic Driving Data

Acquisition and analysis of road incidents based on vehicle dynamics

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