Hvilke faktorer påvirker bysykkelbruken?

The shared bicycle trips from Oslo in the 2017-season are analysed, showing which trips are taken the most, what daily and seasonally variations that exists, and how rain and temperature influences the usage of shared bicycles. The travel data are categorized by the speed, length and height difference of the trips. Linear regression analyses were conducted to understand how weather impacts different types of trips differently during different times of day. There are daily and seasonally variances in how the shared bicycles are being used. The weather impacts the number of trips, as well as the type of trips, being taken. Rain has a negative effect on the bicycle usage. Rain negatively impacts the share of long trips and trips taken at a slow pace the most, while trips taken at a fast pace and trips in the morning rush are affected the least. Higher temperatures positively affect the shared bicycle usage, with the largest effect observed in the evenings. Warm weather positively impacts the number of trips taken at a slow pace more than it impacts the number of trips taken at a fast pace. This information is useful in understanding how the weather can affect the attractiveness of the soft modes and is useful in bicycle planning.本研究针对2017运营季奥斯陆的公共自行车出行数据展开分析，梳理了最频繁的出行类型、日间与季节维度的出行变化规律，以及降雨与气温对公共自行车使用的影响机制。出行数据将按照行程速度、里程与高度差进行分类。本研究采用线性回归分析，探究不同时段下天气对不同类型出行的差异化影响。公共自行车的使用情况存在显著的日间与季节差异。天气状况不仅影响出行总量，同时也会改变出行类型结构。降雨对公共自行车使用存在显著负向影响：长距离出行与低速出行的占比受降雨负面影响最为显著，而快速出行与早高峰出行受降雨影响最弱。气温升高则对公共自行车使用产生正向影响，夜间时段的受影响程度最为突出。温暖天气对低速出行总量的正向提升作用，强于对快速出行总量的影响。该研究结果有助于理解天气如何影响慢行交通方式的吸引力，同时可为公共自行车规划提供决策支撑。