Low cost in-flow traffic monitor for South-East Asia

Souza-Daw, Tony de; Ross, Robert; Nhan, Truong Duy; Hung, Le Anh; Trung, Nguyen Duc Quoc; Chau, Le Hai; Phuong, Hoang Minh; Ngoc, Le Hoang; Phong, Bui Hai; Nguyễn, Hoàng Dũng; Hoang, Thang Manh; Dzung, Nguyen Tien

doi:10.1109/cce.2016.7562662

Cited by 3 publications

(2 citation statements)

References 15 publications

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“…This category is divided into two subgroups of sample size. The first group is the tens, which used between 10 and 99 participants [ 6 , 123 , 127 , 128 , 131 , 141 , 154 , 194 , 200 ]. The second group is the hundreds, which utilises samples between 100 and 999 participants [ 51 , 133 , 237 ].…”

Section: Methodological Aspects Of Previous Researchmentioning

confidence: 99%

“…In another work, the steering, braking, and throttle inputs were evaluated with the use of hardware related to a commercial steering-wheel system for gaming applications [ 127 , 133 , 138 ]. Another study used an adaptive staircase for estimating the individual driver’s gap acceptance thresholds by changing the approaching vehicle’s distance [ 139 ] and using simulator sickness, PC-Crash simulation, MADYMO [ 100 , 140 , 141 , 142 ], and video scenes of the motorcycle within each driving environment. Other research focused on implementing a mobile system to monitor traffic conditions (motorcycle-mounted system) [ 143 ] and initial designs regarding a simple low-cost EDR prototype using just external sensors, such as IMU, GPS, and compass information.…”

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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