| 1. |
- Seyfi, Mohammad Ali, et al.
(författare)
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Modeling the Motorcycle Crash Severity on Nonintersection Urban Roadways in the Australian State of Victoria Using a Random Parameters Logit Model
- 2023
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Ingår i: Journal of Advanced Transportation. - : Hindawi Limited. - 0197-6729 .- 2042-3195. ; 2023, s. 1-12
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Tidskriftsartikel (refereegranskat)abstract
- Due to a lack of physical protection and balance, motorcycle riders are one of the most vulnerable road users and are more likely to suffer severe injuries than motorists. Between 2009 and 2020, about 60% of motorcycle crashes occurred on nonintersection urban roadways in Victoria, Australia. While considerable research on intersections and their influence on the severity of motorcycle crashes has been conducted, there are limited studies on motorcycle crashes on nonintersection roadways. Since gathering all information from every motorcycle crash may not be possible, heterogeneity can arise from unobserved factors and cause problems in developing reliable crash severity models. Therefore, this study aims to investigate the factors contributing to motorcycle crash severity on Victorian nonintersection urban roadways while considering the heterogeneity of factors. A total of 10,897 nonintersection motorcycles crash data from the beginning of 2009 to November 2020 in the State of Victoria, Australia, were analyzed. A random parameters (mixed) logit model (RPL) was used for evaluating motorcycle crashes. The severity of motorcycle crashes was divided into three categories: fatal injury, serious injury, and minor injury. Also, marginal effects were calculated to see how each parameter estimate affects crash severity outcomes. The RPL model results showed that some factors increased the likelihood of fatal injuries. These factors included not wearing a helmet, being in the older rider age group, riding during the early morning or midnight hours, weekend motorcycle use, riding in the early morning or midnight hours (00:00-6:29 A.M), and insufficient lighting (dark and dusk/dawn). Also, the following factors enhanced the probability of serious injuries: having a pillion passenger, having a motorcycle age of more than 7 years, riding at higher speed limits (more than 50 km/h) or during peak hours in the morning (6:30-8:59 A.M), and being in the younger age group (less than 26 years old). The findings from this study are valuable resources for road safety policy managers to develop effective strategies for improving motorcyclists' safety at nonintersections. This may include improving the light conditions at nonintersection, encouraging the motorcyclist to maintain motorcycles regularly, and educating the motorcyclist to wear a helmet, avoid distractions, and ride responsibly on the weekends.
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| 2. |
- Shirazi, Ardeshir Kohandel, et al.
(författare)
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Heterogeneity in the Preferences of Potential Users of Automated Transit Network (ATN)
- 2023
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Ingår i: Journal of Advanced Transportation. - : Hindawi Limited. - 0197-6729 .- 2042-3195. ; 2023
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Tidskriftsartikel (refereegranskat)abstract
- Many cities in Iran, including the metropolis of Shiraz, are increasingly car-oriented, resulting in traffic congestion and related issues. Considering the current conditions of Iran, an automated transit network (ATN) can be one of the available solutions to this problem. ATN is an advanced type of public transit consisting of automated vehicles moving passengers on a network of dedicated guideways. As a combination of public, personal, and private transport, ATNs may decrease the use of cars and address related problems. In order to design effective policies aimed at achieving the benefits of ATN, it is necessary to have a better understanding of how people accept an ATN system, especially car users. This research aims at advancing future research on the effects of ATNs on travel behavior through identifying the characteristics of users who are likely to accept ATN services, by examining the heterogeneity in the preferences of these people. To achieve this goal, a stated choice survey was conducted and analyzed using multinomial logit (MNL) and mixed logit (ML) models. The results showed that the parameters of trip purpose, owning a hybrid car, and the level of education affect the preferences toward the ATN system. Additionally, from the comparison of the results of the MNL and ML models, it was found that despite the greater ability of the ML model in estimating possible heterogeneities, likely the MNL model can also help to record some heterogeneities more realistically. In the end, the methodological limitations of the study were also acknowledged. Despite the potential hypothesis bias and the status quo bias, the results captured the directionality and relative importance of the attributes of interest.
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