为解决景区停车问题，以张家界武陵源景区的停车需求预测为例，对景区的停车需求预测方法进行了探讨。通过增长率法、二次指数平滑法、多元线性回归分析法三种方法组合预测，得到未来目标年的高峰日游客量和日均游客量。基于此，根据现状数据及未来的发展规划，预测景区各入口的游客量，得到景区各入口处所需的停车泊位数。根据游客游览时间，预测城区留宿人数所占比例，从而得到城区宾馆、旅店所需的停车泊位；并调查晚上城区娱乐点游览人数比例，从而得到其所需的停车泊位数。张家界武陵源景区停车需求预测的实践表明，该方法具有较好的适应性，可为今后类似景区的停车需求预测和相关规范的制定提供一定的借鉴。
Abstract
To solve the parking problem in scenic spots, taking the forecast of parking demand at Wulingyuan scenic spot, Zhangjiajie as an example, the forecast methods to parking demand in scenic spot were discussed. The growth rate method, the quadratic exponential smoothing method and the multivariate linear regression analysis method were combined to predict the peak daily tourist volume and average daily tourist volume in the future target years. On this basis, the tourist volume at each entrance of the scenic spot was predicted according to the current data and future development plans and the number of parking spaces required at these entrances was obtained. According to the visiting time of tourists, the proportion of the number of people staying in urban areas was predicted so as to obtain the number of the parking spaces needed by urban hotels and hostels. The proportion of the number of people visiting the entertainment spots in the city at night was investigated so that the number of parking spaces required was obtained. The practice of parking demand prediction at Wulingyuan scenic spot, Zhangjiajie shows that this method has good adaptability and can provide reference for parking demand forecast of similar scenic spots and making regulations in the future.
关键词
交通规划 /
停车需求 /
预测 /
景区 /
游客量
Key words
transportation planning /
parking demand /
forecast /
scenic spot /
tourist volume
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