Investigating the effect of blood alcohol concentration on motorcyclist’s riding performance using an advanced motorcycle simulator

Vu, Anh Tuan; Nguyễn, Minh Thông; Nguyen, Dinh Vinh Man; Khuat, Viet Hung

doi:10.1016/j.trf.2020.06.010

Cited by 11 publications

(7 citation statements)

References 39 publications

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“…This finding raises another issue that a low BAC can in fact pose a safety threat to road users by engaging in risky riding behaviours [ 67 , 68 ]. Although studies have proposed lowering the legal BAC limit imposed on motorcycle riders to reduce alcohol-related crash risks [ 67 ], zero-tolerance regulation was recommended for the entire population [ 69 ]. To reduce risky riding behaviours, such as drunk riding or unlicensed riding, improved detection methods and penalty increases may constitute an effective countermeasure [ 64 ].…”

Section: Discussionmentioning

confidence: 99%

Unhelmeted Riding, Drunk Riding, and Unlicensed Riding among Motorcyclists: A Population Study in Taiwan during 2011–2016

Liu

Wiratama

Chao

et al. 2023

IJERPH

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This study aimed to investigate the association between drunk riding, unhelmeted riding, unlicensed riding, and running-off-road (ROR) crashes. Multiple logistic regression was used to calculate the adjusted odds ratio (AOR) by using the National Taiwan Traffic Crash Dataset for 2011–2016. The results revealed that unhelmeted riding was associated with 138% (AOR = 2.38; CI (confidence interval) = 2.34–2.42) and 47% (AOR = 1.47; CI = 1.45–1.49) higher risks of drunk riding and unlicensed riding, respectively. The risk of unhelmeted riding increased with blood alcohol concentrations (BACs), and riders with the minimum BAC (0.031–0.05%) had nearly five times (AOR = 4.99; CI = 4.74–5.26) higher odds of unlicensed riding compared with those of riders with a negative BAC. Unhelmeted riding, drunk riding, and unlicensed riding were associated with 1.21 times (AOR = 1.21; CI = 1.13–1.30), 2.38 times (AOR = 2.38; CI = 2.20–2.57), and 1.13 times (AOR = 1.13; CI = 1.06–1.21) higher odds of ROR crashes, respectively. The three risky riding behaviours (i.e., unhelmeted riding, drunk riding, and unlicensed riding) were significantly related to ROR crashes. The risk of unhelmeted riding and ROR crashes increased with BACs.

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Section: Discussionmentioning

confidence: 99%

Unhelmeted Riding, Drunk Riding, and Unlicensed Riding among Motorcyclists: A Population Study in Taiwan during 2011–2016

Liu

Wiratama

Chao

et al. 2023

IJERPH

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“…The first group used between 0 and 9 participants [ 62 , 108 , 110 ]. The second group consists of a study that used between 10 and 99 participants [ 114 , 130 ]. All samples have been used across various studies.…”

Section: Methodological Aspects Of Previous Researchmentioning

confidence: 99%

“…The second subcategory of the experimental study is simulation tests. This category refers to articles that utilised a simulator for data collection to determine the factors that are related to driver behaviour [ 118 , 119 , 120 , 121 ], used chassis dynamometers with the standard driving cycle and onboard portable emission measurement systems in real-world driving conditions [ 122 , 123 , 124 ], the MOTORIST riding simulator [ 125 ], the mid-range simulator located at the Monash University Accident Research Centre [ 126 ], and moving-based motorcycle simulators comprising a motion platform, sound system, screen projection, and image-generation software [ 127 , 128 , 129 , 130 , 131 ]. One study attempted to estimate the impact of low BAC on the riding performance of motorcycle drivers by utilising an advanced motorcycle-riding simulator [ 132 ].…”

Section: Taxonomymentioning

confidence: 99%

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A Comprehensive Review on the Behaviour of Motorcyclists: Motivations, Issues, Challenges, Substantial Analysis and Recommendations

Abdulwahid

Mahmoud

Zaidan

et al. 2022

IJERPH

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With the continuous emergence of new technologies and the adaptation of smart systems in transportation, motorcyclist driving behaviour plays an important role in the transition towards intelligent transportation systems (ITS). Studying motorcyclist driving behaviour requires accurate models with accurate and complete datasets for better road safety and traffic management. As accuracy is needed in modelling, motorcyclist driving behaviour analyses can be performed using sensors that collect driving behaviour characteristics during real-time experiments. This review article systematically investigates the literature on motorcyclist driving behaviour to present many findings related to the issues, problems, challenges, and research gaps that have existed over the last 10 years (2011–2021). A number of digital databases (i.e., IEEE Xplore®, ScienceDirect, Scopus, and Web of Science) were searched and explored to collect reliable peer-reviewed articles. Out of the 2214 collected articles, only 174 articles formed the final set of articles used in the analysis of the motorcyclist research area. The filtration process consisted of two stages that were implemented on the collected articles. Inclusion criteria were the core of the first stage of the filtration process keeping articles only if they were a study or review written in English or were articles that mainly incorporated the driving style of motorcyclists. The second phase of the filtration process is based on more rules for article inclusion. The criteria of inclusion for the second phase of filtration examined the deployment of motorcyclist driver behaviour characterisation procedures using a real-time-based data acquisition system (DAS) or a questionnaire. The final number of articles was divided into three main groups: reviews (7/174), experimental studies (41/174), and social studies-based articles (126/174). This taxonomy of the literature was developed to group the literature into articles with similar types of experimental conditions. Recommendation topics are also presented to enable and enhance the pace of the development in this research area. Research gaps are presented by implementing a substantial analysis of the previously proposed methodologies. The analysis mainly identified the gaps in the development of data acquisition systems, model accuracy, and data types incorporated in the proposed models. Finally, research directions towards ITS are provided by exploring key topics necessary in the advancement of this research area.

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“…Rider alcohol consumption leads to longer braking times and, subsequently, higher crash risk (20). Riders who neglected to use their turn signals or smoked while riding were more likely to cause serious crashes (21).…”

Section: Rider Behaviormentioning

confidence: 99%

Factors Associated With the Severity of Motor Vehicle Crashes Involving Electric Motorcycles and Electric Bicycles: A Random Parameters Logit Approach With Heterogeneity in Means

Wang

Jin

Chen

et al. 2023

Transportation Research Record: Journal of the Transportation R

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Exploring the heterogeneity of factors influencing the severity of electric bicycle crashes and electric motorcycle crashes can help target accident prevention policies to improve traffic safety. Therefore, this paper establishes a mean heterogeneity random parameter logit model using crash data from 2016 to 2020 in Guangxi to explore the different factors influencing the severity of crashes involving electric motorcycles and electric bicycles. The results show that the key influences on crash severity differ in electric motorcycle crashes and electric bicycle crashes. At the same time, some common factors affect the two types of crashes to different degrees. In addition, the complex interaction effects of unobserved heterogeneity were considered to explore the random parameters of the two types of crashes. The effect of unobserved heterogeneity on the distribution characteristics of the random parameters was then determined. For example, in electric motorcycle crashes, street lighting at night has a random parameter characteristic. The likelihood of serious crashes decreased when both street lighting at night and vehicle left turn were involved, and decreased when both street lighting at night and no signal control were involved. In electric bicycle crashes, large trucks have a random parameter characteristic. The likelihood of serious crashes increased when both large trucks and motor vehicle lights not turned on were involved, and increased when both large trucks and visibility less than or equal to 200 meters were involved. The results provide a basis for improving the road safety of electric motorcycles and electric bicycles.

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Investigating the effect of blood alcohol concentration on motorcyclist’s riding performance using an advanced motorcycle simulator

Cited by 11 publications

References 39 publications

Unhelmeted Riding, Drunk Riding, and Unlicensed Riding among Motorcyclists: A Population Study in Taiwan during 2011–2016

Unhelmeted Riding, Drunk Riding, and Unlicensed Riding among Motorcyclists: A Population Study in Taiwan during 2011–2016

A Comprehensive Review on the Behaviour of Motorcyclists: Motivations, Issues, Challenges, Substantial Analysis and Recommendations

Factors Associated With the Severity of Motor Vehicle Crashes Involving Electric Motorcycles and Electric Bicycles: A Random Parameters Logit Approach With Heterogeneity in Means

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