Review and assessment of different perspectives of vehicle-pedestrian conflicts and crashes: Passive and active analysis approaches

Sheykhfard, Abbas; Haghighi, Farshidreza; Papadimitriou, Eleonora; Gelder, Pieter van

doi:10.1016/j.jtte.2021.08.001

Cited by 24 publications

(10 citation statements)

References 141 publications

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“…The driving style and behavior of a driver, especially a professional driver, affect the safety of other road users [ 41 , 42 , 43 ]. Depending on the driver’s driving style, traffic conditions, and other road conditions, drivers may experience different values of longitudinal acceleration.…”

Section: Discussionmentioning

confidence: 99%

Experimental Study on Longitudinal Acceleration of Urban Buses and Coaches in Different Road Maneuvers

Frej

Grabski

Jurecki

et al. 2023

Sensors

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A vehicle’s longitudinal acceleration is a parameter often used for determining vehicle motion dynamics. This parameter can also be used to evaluate driver behavior and passenger comfort analysis. The paper presents the results of longitudinal acceleration tests of city buses and coaches recorded during rapid acceleration and braking maneuvers. The presented test results demonstrate that longitudinal acceleration is significantly affected by road conditions and surface type. In addition, the paper presents the values of longitudinal accelerations of city buses and coaches during their regular operation. These results were obtained on the basis of registration of vehicle traffic parameters in a continuous and long-term manner. The test results showed that the maximum deceleration values recorded during the tests of city buses and coaches in real traffic conditions were much lower than the maximum deceleration values found during sudden braking maneuvers. This proves that the tested drivers in real conditions did not have to use sudden braking. The maximum positive acceleration values recorded in acceleration maneuvers were slightly higher than the acceleration values logged during the rapid acceleration tests on the track.

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Section: Discussionmentioning

confidence: 99%

Experimental Study on Longitudinal Acceleration of Urban Buses and Coaches in Different Road Maneuvers

Frej

Grabski

Jurecki

et al. 2023

Sensors

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“…Sheykhfard et al [11] studied the conflict between pedestrians and vehicles by using active methods and passive methods. The results of the active method showed that dangerous behaviors are the most important factors that threaten pedestrian safety, such as illegal speeding, noncompliance with traffic laws, and illegal overtaking by drivers.…”

Section: Research Status At Home and Abroadmentioning

confidence: 99%

A Review of Research on Pedestrian-vehicle Conflict in Non-signal-controlled Road Sections

Yang¹

2022

AJST

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Pedestrian crossings, as the main traffic facilities for pedestrians crossing the street, play an important role in ensuring the safety of pedestrians crossing the street. However, there are many places on domestic crosswalks without signal control, which leads to the interaction between vehicles and pedestrians on the crosswalk, which will not only cause traffic congestion, affect the normal traffic order, but also cause traffic accidents. It is of great significance to improve the traffic efficiency to strengthen the understanding of the seriousness of the conflict between people and vehicles in the non-signal control section, and to prevent the accident of drivers and pedestrians.

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“…The results of the active approach showed that risky behaviors such as unauthorized speeding, illegal crossing, unauthorized overtaking, non-compliance with traffic law are the most significant factor in threatening pedestrian safety. In this study, the findings would lead to better understanding of the road users' behavior for studies on advanced driving assistance systems (ADAS) [55].…”

Section: International Journal Of Research In Science and Technologymentioning

confidence: 99%

Domain-Driven Actionable Knowledge Discovery for Traffic Accidents Using Rules Induction

Yousif¹,

Agarwal²,

Pareek³

2022

IJRST

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Due to the limitation of the methodologies of traditional data mining to satisfy business expectations, the shift from mining data-centered hidden patterns to domain-driven actionable knowledge discovery has become a significant direction of KDD research [22]. Traditional data mining algorithms and tools face major obstacles and challenges to solve real-life business problems and issues as they fail to provide actions that can be taken by people in business based on generated rules [22]. A small set of rules are generated by standard classification algorithms to form a classifier, but these classification algorithms use domain independent biases and heuristics [2]. This research aimed to propose a new approach to find actionable rules from sets of discovered rules. It focused on how a combination of traditional classification data mining and domain-driven data mining approach could be applied in solving real-life problems related to the field of traffic accidents in UAE. Real-life data were collected and pre-processed using the user’s existing knowledge and needs. Classification using Rules Induction was applied on the domain-driven dataset. The discovered rules from this technique were then summarized, combined, and analyzed. The final set of actionable rules from Classification technique for each class was then generated using a proposed interestingness method. To support such a process, the domain driven in-depth pattern discovery (DDID-PK) framework was followed [9]. Based on experimental results, the extracted domain-driven rules were more interesting and actionable than those produced by the traditional classification technique of data mining. In addition, the integration of data-centered classification technique of data mining to domain-driven approach of data mining and actionable knowledge discovery could help the Dubai police authority to reduce traffic accident severity by formulating new policies and traffic rules based on the domain-driven knowledge extracted from some hidden patterns from real data.

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Review and assessment of different perspectives of vehicle-pedestrian conflicts and crashes: Passive and active analysis approaches

Cited by 24 publications

References 141 publications

Experimental Study on Longitudinal Acceleration of Urban Buses and Coaches in Different Road Maneuvers

Experimental Study on Longitudinal Acceleration of Urban Buses and Coaches in Different Road Maneuvers

A Review of Research on Pedestrian-vehicle Conflict in Non-signal-controlled Road Sections

Domain-Driven Actionable Knowledge Discovery for Traffic Accidents Using Rules Induction

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