The influence of road familiarity on distracted driving activities and driving operation using naturalistic driving study data

Jian, Wu; Xu, Hao

doi:10.1016/j.trf.2017.11.018

Cited by 61 publications

(23 citation statements)

References 21 publications

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“…In addition, the use of the instructors' professional vehicle results in a reduction of performance [64]. However, familiarity with the road increases distractibility while driving [65] as well as reaction time [66]. In addition, risk perception and ability to respect speed regulation are reduced [67,68].…”

Section: Plos Onementioning

confidence: 99%

Standardized on-road tests assessing fitness-to-drive in people with cognitive impairments: A systematic review

et al. 2020

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The on-road assessment is the gold standard because of its ecological validity. Yet existing instruments are heterogeneous and little is known about their psychometric properties. This study identified existing on-road assessment instruments and extracted data on psychometric properties and usability in clinical settings. Method A systematic review identified studies evaluating standardized on-road evaluation instruments adapted for people with cognitive impairment. Published articles were searched on PubMed, CINHAL, PsycINFO, Web of Science, and ScienceDirect. Study quality and the level of evidence were assessed using the COSMIN checklist. The collected data were synthetized using a narrative approach. Usability was subjectively assessed for each instrument by extracting information on acceptability, access, cost, and training. Results The review identified 18 published studies between 1994 and 2016 that investigated 12 different on-road evaluation instruments: the Performance-Based Driving Evaluation, the Washington University Road Test, the New Haven, the Test Ride for Practical Fitness to Drive, the Rhode Island Road Test, the Sum of Manoeuvres Score, the Performance Analysis of Driving Ability, the Composite Driving Assessment Scale, the Nottingham Neurological Driving Assessment, the Driving Observation Schedule, the Record of Driving Errors, and the Western University's On-road Assessment. Participants were mainly male (64%), between 48 and 80 years old, and had a broad variety of cognitive disorders. Most instruments showed reasonable psychometric values for internal consistency, criterion validity, and reliability. However, the level of evidence was poor to support any of the instruments given the low number of studies for each.

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Section: Plos Onementioning

confidence: 99%

Standardized on-road tests assessing fitness-to-drive in people with cognitive impairments: A systematic review

et al. 2020

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“…By using the collected big data, typologies of urban areas for persons with impairments can be derived and specific metrics can be developed (e.g., please see [83]). Here, perceptions of disabled people on the physical environment also play a key role, and naturalistic studies can be carried out to analyze the behavior of disabled people in real-world conditions (e.g., please see [84,85]).…”

Section: Use Of Geoinformation Tools and Technologies As Enablers Formentioning

confidence: 99%

Improvement of Disability Rights via Geographic Information Science

Kocaman

Özdemir

2020

Sustainability

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Rights, legal regulations, and practices often arise from societal and scientific developments, and societal transformations may originate from new legal regulations as well. Basic rights can be re-defined with advancements in science and technology. In such an evolutional loop, where mutual supply is obvious, combined legal and technological frameworks should be exercised and developed for practicing human rights. The main aim of this article is to propose a conceptual and methodological framework for the improvement of disability rights in the light of recent advancements in geographic information science (GIScience), in particular for those with motor disabilities, for whom questions related to “where” are essential. The concept of disability is discussed, considering different aspects, and a new methodological framework is proposed in which Geographic Information Systems (GIS), volunteered geographic information (VGI) and citizen science are at the core. In order to implement the framework at the national and international levels, a spatial data model should be developed first. The new data collection and interpretation approaches based on VGI, citizen science, and machine learning methods may help to realize equal rights for people with motor disabilities, by enabling improved access to education, health, and travel.

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“…The traditional traffic sensors such as loop detectors and cameras mainly provide macro traffic data such as traffic flow rates, average speeds (or spot speeds), and occupancy [35]. The performance of cameras can be greatly influenced by light conditions [36]. The most common approach for real-time traffic data collection is using active sensors such as radar-based method or Light Detection and Ranging (LiDAR)-based method.…”

Section: Roadside Lidar For Hrmtd Data Collectionmentioning

confidence: 99%

Raster-Based Background Filtering for Roadside LiDAR Data

Jian

et al. 2019

IEEE Access

Self Cite

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The roadside deployed light detecting and ranging (LiDAR) has been a solution to fill the data gap for the transition period from the unconnected-vehicles environment to the connected-vehicles system. For the roadside LiDAR system, background filtering is an initial but important step. This paper presented a raster-based method for background filtering with roadside LiDAR data. The proposed method contains four major parts: region of interest (ROI) selection, rasterization, background area detection, and background array generation. The location of the background points was stored in a 3D array. The performance of the raster-based method was tested with the data collected at different scenarios. The comparison to the stateof-the-art also confirmed the robustness of the proposed method. INDEX TERMS Background filtering, roadside LiDAR, connected-vehicles.

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The influence of road familiarity on distracted driving activities and driving operation using naturalistic driving study data

Cited by 61 publications

References 21 publications

Standardized on-road tests assessing fitness-to-drive in people with cognitive impairments: A systematic review

Standardized on-road tests assessing fitness-to-drive in people with cognitive impairments: A systematic review

Improvement of Disability Rights via Geographic Information Science

Raster-Based Background Filtering for Roadside LiDAR Data

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