Department of Civil Engineering, LKC Faculty of Engineering and Science, Universiti Tunku Abdul Rahman (UTAR), Building KB, Level 8, Room 17(2), Jalan Sungai Long, Bandar Sungai Long, 43000 Kajang, Selangor, Malaysia.
Department of Civil Engineering, LKC Faculty of Engineering and Science, Universiti Tunku Abdul Rahman (UTAR), Building KB, Level 8, Room 17(2), Jalan Sungai Long, Bandar Sungai Long, 43000 Kajang, Selangor, Malaysia.
Accid Anal Prev. 2018 Apr;113:106-116. doi: 10.1016/j.aap.2018.01.025. Epub 2018 Mar 7.
This study had developed a passenger safety perception model specifically for buses taking into consideration the various factors, namely driver characteristics, environmental conditions, and bus characteristics using Bayesian Network. The behaviour of bus driver is observed through the bus motion profile, measured in longitudinal, lateral, and vertical accelerations. The road geometry is recorded using GPS and is computed with the aid of the Google map while the perceived bus safety is rated by the passengers in the bus in real time. A total of 13 variables were derived and used in the model development. The developed Bayesian Network model shows that the type of bus and the experience of the driver on the investigated route could have an influence on passenger's perception of their safety on buses. Road geometry is an indirect influencing factor through the driver's behavior. The findings of this model are useful for the authorities to structure an effective strategy to improve the level of perceived bus safety. A high level of bus safety will definitely boost passenger usage confidence which will subsequently increase ridership.
本研究使用贝叶斯网络为公交车开发了一个专门考虑各种因素的乘客安全感知模型，这些因素包括驾驶员特征、环境条件和公交车特征。通过测量纵向、横向和垂直加速度来观察公交车驾驶员的行为。使用 GPS 记录道路几何形状，并借助谷歌地图进行计算，而乘客则实时对公交车的安全状况进行评分。总共提取了 13 个变量并用于模型开发。所开发的贝叶斯网络模型表明，公交车类型和驾驶员在调查路线上的经验可能会影响乘客对公交车安全的感知。道路几何形状是通过驾驶员行为产生的间接影响因素。该模型的研究结果有助于当局制定有效的策略，提高公交车安全感知水平。高水平的公交车安全肯定会增强乘客的使用信心，从而增加客流量。
