Applying Analytical Hierarchy Process to Evaluate Adult Occupant Protection on Body Region in ASEAN NCAP Offset Frontal Test Domain

Aziz, Hanida Abdul; Sukadarin, Ezrin Hani; Suhaimi, Nurud Suria; Osman, H.; Noordin, M.N.; Shafiee, I.

doi:10.56381/jsaem.v2i3.93

Cited by 3 publications

(3 citation statements)

References 9 publications

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“…As regards airbags and seatbelt for the nine models, three had not improved their airbag systems. However, the rest had improved their airbag systems signifying its importance to reduce injuries (Aziz et al, 2018;Ahmad et al, 2019). Mitsubishi Pajero Sport uses the double pre-tensioner and load limiter for driver's seatbelt while the rest use a single pre-tensioner seatbelt for both driver and front passenger.…”

Section: Overall Discussionmentioning

confidence: 99%

Comparing ASEAN NCAP Ratings between Editions of the Same Models

Jawi¹,

Kassim²,

Hassan³

et al. 2020

JSAEM

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From a total of 20 car models crash-tested by ASEAN NCAP, seven models from four makes have undergone ASEAN NCAP assessment twice, whereas two car models from two domestic powerhouses had undergone the assessment thrice. This study shall evaluate the improvements to the newer editions which supposedly led to better safety ratings. The focus is on the passive safety systems comprising airbags, seatbelt, and child seats. ASEAN NCAP star rating is mainly based on the Adult Occupant Protection (AOP) and Children Occupant Protection (COP) for passive safety as well as some elements in active safety. The ratings and points earned for the AOP and COP were compared between previous and newer editions of the same car models. An analysis was conducted as to whether or not the different editions used the same protocol. There is a difference between the inaugural and the latest protocols to assess both the AOP and COP. Cars using different protocols were analysed in terms of the chest deflection value, in which the value from the latest protocol shall be calculated using the previous protocol to obtain AOP scores and making the comparison. Overall, the new batch of car models was rated to be safer and mostly the newer edition of the car models obtained better COP scores compared to their predecessors.

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Section: Overall Discussionmentioning

confidence: 99%

Comparing ASEAN NCAP Ratings between Editions of the Same Models

Jawi¹,

Kassim²,

Hassan³

et al. 2020

JSAEM

View full text Add to dashboard Cite

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“…FAHP first ranked the crash factors that most affected the performance of older drivers. Second, the procedure ranked the 14 counties by performing a pairwise comparison between the incident reason for association with the main crash factors and their relative significance ( 38 ). Figure 7 shows the FAHP framework used to rank the 14 counties of Florida.…”

Section: Proposed Methodologymentioning

confidence: 99%

Remediation Ranking of High Crash Fatality Locations Involving Older Drivers in Florida’s Rural Counties

Ebrahimi

Momenitabar

Arani

et al. 2022

Transportation Research Record: Journal of the Transportation R

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In 2019, Florida’s aging road users (65 years or older) accounted for 20% of the population but 37% of all crashes. Florida Department of Transportation has identified aging road users as one of the areas that requires attention in achieving Vision Zero—a strategy to eliminate all traffic fatalities and severe injuries, while increasing safe, healthy, equitable mobility for all. Research has documented that fatality rates in motor vehicle crashes are higher in rural than urban areas. Drivers in rural areas may be more vulnerable because they rely more on driving and consequently are reluctant to stop. This study identifies factors contributing to fatalities among aging drivers in 14 rural Florida counties experiencing high crash rates. The methodology used a multicriteria decision-making model, namely the fuzzy analytic hierarchy process (FAHP), to identify and categorize the causes of fatal crashes among drivers aged 65+, and to rank their 14 rural counties for remediation measures. FAHP methodology calculates crash factor weights and ranks the counties using pairwise comparisons of those factors to compare and quantify them. Results revealed that the top contributing factors to fatal crashes among drivers 65+ were cloudy, foggy, or rainy weather and when roadways were sandy or wet. Driving in the dark and at dawn also increased the risk of fatal crashes within this specified age group. These findings could help policy makers in each location focus on remediation measures such as older driver education and infrastructural improvements to address the most critical factors in fatal accidents.

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“…The procedure first ranks the main crash factors that affect the performance of older drivers. Next, the procedure ranks the 14 counties by performing a pairwise comparison between the incident reason for association with the main crash factors and their relative significance [37]. Figure 7 shows the FAHP framework to rank the 14 counties of Florida.…”

Section: Fuzzy Analytical Hierarchy Process Methodologymentioning

confidence: 99%