Wang Jie, Huang Helai, Zeng Qiang
School of Traffic and Transportation Engineering, Central South University, Changsha, Hunan, China.
School of Civil Engineering and Transportation, South China University of Technology, Guangzhou, Guangdong, China.
Accid Anal Prev. 2017 Jan;98:223-231. doi: 10.1016/j.aap.2016.10.018. Epub 2016 Oct 19.
This paper aimed to (i) differentiate the effects of contributory factors on crash risks related to different transportation modes, i.e., motor vehicle, bicycle and pedestrian; (ii) explore the potential contribution of zone-level factors which are traditionally excluded or omitted, so as to track the source of heterogeneous effects of certain risk factors in crash-frequency models by different modes.
Two analytical methods, i.e. negative binomial models (NB) and random parameters negative binomial models (RPNB), were employed to relate crash frequencies of different transportation modes to a variety of risk factors at intersections. Five years of crash data, traffic volume, geometric design as well as macroscopic variables at traffic analysis zone (TAZ) level for 279 intersections were used for analysis as a case study.
Among the findings are: (1) the sets of significant variables in crash-frequency analysis differed for different transportation modes; (2) omission of macroscopic variables would result in biased parameters estimation and incorrect inferences; (3) the zonal factors (macroscopic factors) considered played a more important role in elevating the model performance for non-motorized than motor-vehicle crashes; (4) a relatively smaller buffer width to extract macroscopic factors surrounding the intersection yielded better estimations.
本文旨在（i）区分促成因素对不同交通方式（即机动车、自行车和行人）相关碰撞风险的影响；（ii）探索传统上被排除或忽略的区域层面因素的潜在贡献，以便追踪不同交通方式碰撞频率模型中某些风险因素的异质性影响来源。
采用两种分析方法，即负二项式模型（NB）和随机参数负二项式模型（RPNB），将不同交通方式的碰撞频率与交叉路口的各种风险因素联系起来。作为案例研究，使用了279个交叉路口的五年碰撞数据、交通流量、几何设计以及交通分析区（TAZ）层面的宏观变量进行分析。
研究结果包括：（1）不同交通方式的碰撞频率分析中显著变量集不同；（2）遗漏宏观变量会导致参数估计有偏差和推断错误；（3）所考虑的区域因素（宏观因素）在提升非机动车碰撞模型性能方面比机动车碰撞发挥了更重要的作用；（4）提取交叉路口周围宏观因素时相对较小的缓冲宽度能产生更好的估计。
