大数据背景下重庆市综合交通模型维护升级

Maintenance and Upgrading of Chongqing Comprehensive Transportation Models Under Big Data Era

利用传统交通调查数据开展交通模型维护升级工作存在抽样率低、样本量小、人工成本高、精度低、实施难度大等多种现实问题。在大数据技术不断更新完善的背景下,有必要探索新的模型维护升级技术和方法。首先,阐述重庆市交通大数据的发展历程、数据类型、数据采集与数据格式。其次,在重庆市综合交通模型的框架结构中,分别利用大数据资源探索公共汽车线网的构建、各等级道路流量延误函数标定、常住人口和就业岗位分析、出行分布特征分析和公共交通出行需求分析等相关技术方法。最后,以重庆市综合交通模型的应用实践成果验证模型的可靠性和准确性。

Transportation models were maintained and upgraded highly relying on traditional traffic survey technology, which has raised a couple of practical issues, including low sample rates, small sample size,high labor cost, low accuracy, and implementation difficulty. As we are stepping into big data era, it is necessary to explore new ways for maintaining and upgrading transportation models. First of all, this paper illustrates the efforts in the big data development progress, data collection, and data structures Chongqing has made so far. Second, it highlights some critical achievements, including using big data to construct bus network, calibrate volume delay functions for various road types, analyze residential population and employment, discover trip distribution patterns and detect public transport demand under Chongqing Comprehensive Transportation Model framework. Finally, the paper demonstrates various real- world applications to justify the reliability and accuracy improvement of updated model.