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首页> 外文期刊>Journal of Transport and Land Use >Spatial modeling of bicycle activity at signalized intersections
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Spatial modeling of bicycle activity at signalized intersections

机译：信号交叉口自行车活动的空间模型

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This paper presents a methodology to investigate the link between bicycle activity and built environment, road and transit network characteristics, and bicycle facilities while also accounting for spatial autocorrelation between intersections. The methodology includes the normalization of manual cyclist counts to average seasonal daily volumes (ASDV), taking into account temporal variations and using hourly, daily, and monthly expansion factors obtained from automatic bicycle count data. To correct for weather conditions, two approaches were used. In the first approach, a relative weather ridership model was generated using the automatic bicycle count and weather data. In the second approach, weather variables were introduced directly into the model. For each approach, the effects of built environment, road and transit characteristics, and bicycle facilities on cyclist volumes were determined. It was found that employment, schools, metro stations, bus stops, parks, land mix, mean income, bicycle facility type (bicycle lanes and cycle tracks), length of bicycle facilities, average street length, and presence of parking entrances were associated with bicycle activity. From these, it was found that the main factors associated with bicycle activity were land-use mix, cycle track presence, and employment density. For instance, intersections with cycle tracks have on average 61 percent more cyclists than intersections without. An increase of 10 percent in land-use mix or employment density would cause an increase of 8 percent or 5.3 percent, respectively, in bicycle flows. The methods and results proposed in this research are helpful for planning bicycle facilities and analyzing cyclist safety. Limitations and future work are discussed at the end of this paper.
机译：本文提出了一种方法来研究自行车活动与建筑环境，道路和公交网络特性以及自行车设施之间的联系，同时也考虑了交叉口之间的空间自相关。该方法包括考虑到时间变化并使用从自动自行车计数数据获得的每小时，每天和每月的扩展因子，将手动自行车计数归一化为平均季节性日流量（ASDV）。为了校正天气状况，使用了两种方法。在第一种方法中，使用自动自行车计数和天气数据生成相对天气乘车率模型。在第二种方法中，将天气变量直接引入模型。对于每种方法，都确定了建筑环境，道路和交通特性以及自行车设施对骑车人数量的影响。研究发现，就业，学校，地铁站，公交车站，公园，土地混合，平均收入，自行车设施类型（自行车道和自行车道），自行车设施的长度，平均街道长度以及停车位的存在与自行车活动。从这些发现中，发现与自行车活动有关的主要因素是土地使用混合，自行车道的存在和就业密度。例如，有自行车道的路口比没有路口的路口平均多骑自行车的人61％。土地利用结构或就业密度增加10％，自行车流量将分别增加8％或5.3％。这项研究中提出的方法和结果有助于规划自行车设施和分析骑车人的安全性。本文的末尾讨论了局限性和未来的工作。

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