Huang Yizhe, Sun Daniel Jian, Tang Juanyu
a China Institute of Urban Governance, Shanghai Jiao Tong University , Shanghai , China.
b Center for ITS and UAV Applications Research, Shanghai Jiao Tong University , Shanghai , China.
Traffic Inj Prev. 2018 Apr 3;19(3):311-316. doi: 10.1080/15389588.2017.1391382. Epub 2018 Feb 9.
The 3 objectives of this study are to (1) identify the driving style characteristics of taxi drivers in Shanghai and New York City (NYC) using taxi Global Positioning System (GPS) data and make a comparative analysis; (2) explore the influence of different driving style characteristics on the frequency of speeding (who and how?) and (3) explore the influence of driving style characteristics, road attributes, and environmental factors on the speeding rate (when, where, and how?) Methods: This study proposes a driver-road-environment identification (DREI) method to investigate the determinant factors of taxi speeding violations. Driving style characteristics, together with road and environment variables, were obtained based on the GPS data and auxiliary spatiotemporal data in Shanghai and NYC.
The daily working hours of taxi drivers in Shanghai (18.6 h) was far more than in NYC (8.5 h). The average occupancy speed of taxi drivers in Shanghai (21.3 km/h) was similar to that of NYC (20.3 km/h). Speeders in both cities had shorter working hours and longer daily driving distance than other taxi drivers, though their daily income was similar. Speeding drivers routinely took long-distance trips (>10 km) and preferred relatively faster routes. Length of segments (1.0-1.5 km) and good traffic condition were associated with high speeding rates, whereas central business district area and secondary road were associated with low speeding rates. Moreover, many speeding violations were identified between 4:00 a.m. and 7:00 a.m. in both Shanghai and NYC and the worst period was between 5:00 a.m. and 6:00 a.m. in both cities.
Characteristics of drivers, road attributes, and environment variables should be considered together when studying driver speeding behavior. Findings of this study may assist in stipulating relevant laws and regulations such as stricter offense monitoring in the early morning, long segment supervision, shift rule regulation, and working hour restriction to mitigate the risk of potential crashes.
本研究的三个目标是：（1）利用出租车全球定位系统（GPS）数据识别上海和纽约市出租车司机的驾驶风格特征并进行比较分析；（2）探讨不同驾驶风格特征对超速频率的影响（何人以及如何影响？）；（3）探讨驾驶风格特征、道路属性和环境因素对超速率的影响（何时、何地以及如何影响？） 方法：本研究提出一种驾驶员-道路-环境识别（DREI）方法来调查出租车超速违规的决定因素。基于上海和纽约市的GPS数据及辅助时空数据，获取了驾驶风格特征以及道路和环境变量。
上海出租车司机的每日工作时长（18.6小时）远多于纽约市（8.5小时）。上海出租车司机的平均载客速度（21.3公里/小时）与纽约市（20.3公里/小时）相近。两个城市的超速驾驶者工作时长均较短，每日行驶距离较长，不过他们的日收入相近。超速驾驶者通常进行长途出行（>10公里），且偏好相对较快的路线。路段长度（1.0 - 1.5公里）和良好的交通状况与高超速率相关，而中央商务区和二级道路与低超速率相关。此外，上海和纽约市在凌晨4:00至7:00之间都发现了许多超速违规行为，两个城市最严重的时段均为凌晨5:00至6:00。
研究驾驶员超速行为时应综合考虑驾驶员特征、道路属性和环境变量。本研究结果可能有助于制定相关法律法规，如加强凌晨时段的违规监测、长路段监管、轮班规则规定和工作时长限制，以降低潜在碰撞风险。
