Naturalistic Driving Studies: An Overview and International Perspective

Ehsani, Johnathon P.; Harbluk, Joanne L.; Bärgman, Jonas; Williamson, Ann; Michael, Jeffrey P.; Grzebieta, Raphael; Olivier, Jake; Eusebio, Jan; Charlton, Judith Lynne; Koppel, Sjaanie Narelle; Young, Kristie Lee; Lenné, Mike; Haworth, Narelle; Rakotonirainy, Andry; Elhenawy, Mohammed; Larue, Grégoire S.; Senserrick, Teresa; Woolley, Jeremy; Mongiardini, Mario; Stokes, Christopher; Boase, Paul; Guo, Feng

doi:10.1016/b978-0-08-102671-7.10651-7

Cited by 6 publications

(3 citation statements)

References 18 publications

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“…Methods such as Naturalistic Driving (ND) allow collecting data to analyze collision risk events in scenarios where there is not enough collected accident data. Thus, ND can be applied in the context of interest, considering that the method's complexity and the amount of required resources are manageable [15].…”

Section: Introductionmentioning

confidence: 99%

Design, Development and Validation of an Intelligent Collision Risk Detection System to Improve Transportation Safety: The Case of the City of Popayán, Colombia

et al. 2022

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Several approaches from different perspectives have been used to solve problems with traffic accidents (TA), which mainly affect low- and middle-income countries. Conditions of certain cities, regarding road infrastructure, enforcement of traffic safety regulations, and motor vehicle numbers, influence the increase in TAs. Therefore, medium-sized cities in developing countries (context of interest), which commonly have worrying conditions, are a relevant scenario. One of the approaches to reduce TAs has been the use of data analysis through Machine Learning (ML); however, these techniques require a large amount of data, and medium-sized cities commonly do not have enough. Techniques such as Naturalistic Driving (ND) can be applied as a data collection method. This work proposes an intelligent collision risk detection system (ICDRS) using ND and ML to improve sustainability and safety of transportation in medium-sized cities. The ICRDS design considered the limitations of the context of interest and uses two data collection devices in the vehicle. The ICRDS validation included the design and execution of tests using ND. This validation identified if the collected data in a certain time interval contained high-risk collision events (sudden acceleration, sudden braking, aggressive left or right turn, aggressive left or right lane change). The system implementation results were satisfactory. The developed ML algorithm obtained an average value 0.98 in all the metrics. Two data sets of driving on routes were collected. In addition, the performed tests were able to identify city areas with high accident rates.

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Section: Introductionmentioning

confidence: 99%

Design, Development and Validation of an Intelligent Collision Risk Detection System to Improve Transportation Safety: The Case of the City of Popayán, Colombia

et al. 2022

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“…Naturalistic data constitute a greater proportion of past studies where most previous studies utilized them as their validation tools for the mathematical models of road user behavior. Naturalistic studies are usually conducted either using instrumented vehicles [20] or traffic data collection devices including drones [21] and installed cameras on fixed objects like light poles [22]. Using instrumented vehicles provides the advantage of studying road user behavior over a longer period of time and with high quality and the capability of tracking a large number of road user parameters [23].…”

mentioning

confidence: 99%

“…However, the downside is that this method is expensive and drivers are usually aware that they are being watched [20] and this might make them alter their behavior [24]. On the other hand, video and sensor-based studies offer this opportunity to record road user behavior in an unnoticed manner, gaining more knowledge of road user behavior and its features while avoiding behavioral adaptation [24].…”

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confidence: 99%

Testing the validity of multi participant distributed simulation for understanding and modeling road user interaction

Kalantari,

Lin,

Mohammadi

et al. 2023

Preprint

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Understanding driver-pedestrian interactions at unsignalized locations has gained additional importance due to the advancements that have happened recently in vehicle automation. To investigate these interactions, we previously developed a novel experimental study paradigm and a set of computational models, including four game-theoretic models (i.e., two conventional and two behavioral game-theoretic models) and a logit model. The aim of this study is to validate both the lab study and the models with naturalistic data to understand to what extent the results that come out of the lab are comparable to real traffic data. In the experimental study, several pairs of one driver and one pedestrian interacted with each other under different kinematic conditions and at zebra crossings in a virtual environment. The naturalistic data collection was conducted at two marked crossings (normal versus zebra staggered crossing) using state-of-the-art sensors capturing road user type, trajectory, and speed over time. Overall, the results indicated there is a fine relative validity of the experimental study where road users showed similar patterns of non-verbal communication in both studies. Similar to the lab data, crossing type played a role in interaction outcomes and metrics such as pedestrian crossing speed and vehicle delay. Pedestrians crossed more often and walked faster at staggered zebra compared to normal zebra in real traffic. In both studies, vehicle delay was affected by kinematics and location. However, vehicle delay was longer in the lab compared to real traffic. Also, unlike the lab study, pedestrian approach speed was measured and found to be the predictor of their crossing speed and the delay of the drivers. Additionally, all the computational models performed close to each other and well as opposed to the lab study. The behavioral game-theoretic models performed slightly better than the others in terms of prediction accuracy; this replicated our previous findings about road user behavior complexity which is a pivotal point for the virtual testing of automated vehicles.

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Intelligent collision risk detection in medium-sized cities of developing countries, using naturalistic driving: A review

Paredes¹,

Chamorro²,

Salazar-Cabrera³

et al. 2022

Journal of Traffic and Transportation Engineering (English Edit

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Naturalistic Driving Studies: An Overview and International Perspective

Cited by 6 publications

References 18 publications

Design, Development and Validation of an Intelligent Collision Risk Detection System to Improve Transportation Safety: The Case of the City of Popayán, Colombia

Design, Development and Validation of an Intelligent Collision Risk Detection System to Improve Transportation Safety: The Case of the City of Popayán, Colombia

Testing the validity of multi participant distributed simulation for understanding and modeling road user interaction

Intelligent collision risk detection in medium-sized cities of developing countries, using naturalistic driving: A review

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