Bus stop optimization visualization method based on multi-source data

Abstract

The invention discloses a bus station optimization visualization method based on multi-source data, and the method comprises the steps: collecting shared bicycle data, urban POI data and urban road network data, and then carrying out the data preprocessing, traffic data calculation and shared bicycle data clustering; designing POI spatial distribution visual mapping, and performing visual coding on urban POI type distribution, urban POI density distribution and shared bicycle density distribution; designing pedestrian volume time sequence evolution visual mapping, analyzing shared single-bus traffic volume evolution near a single bus stop, comparing differences of different stops on a pedestrian volume time sequence evolution mode, and performing visual layout and drawing implementation according to a designed visual mapping rule. According to the invention, a traffic planner can be assisted to establish an overall understanding of the surrounding environment of the station, a potential mode possibly contained is found out to formulate a station optimization strategy, and comparative analysis can be carried out at different alternative stations to determine a more appropriate alternative station.

Description

Technical field[0001]The present invention relates to the field of information visualization and visual analysis, and is specifically an optimized visualization method based on multi-source data.Background technique[0002]As a low-carbon environmentally friendly, fast and convenient transportation is one of the main travel methods of urban residents. However, accompanied by the rapid development of the city, the traffic problem has been highlighted, and the traffic congestion is growing. The increase in residents' travel demand and changes in the distribution of travel time and space have exacerbated urban road congestion. Bus sites are an important part of public transportation planning, optimize non-time-free bus sites, which can shorten passengers waiting time to increase bus utilization to alleviate urban traffic congestion.[0003]The government-related report shows that the "bus + shared bicycle" travel is more than 18.6% higher than the "bus + walk" travel. The emergence and pop...

AI Technical Summary

Problems solved by technology

[0007] 1) Due to the single site selection method of the traditional site and the deviation in the parameter setting of the existing site selection model, etc., there are deficiencies in the site setting itself

At the same time, the existing research on site optimization mainly focuses on using traditional influencing factors (actual research on land use properties, population distribution) to construct models to analyze the rationality of site settings, or site spacing, number of digits, etc. for optimization. The complete process of site optimization does not fully consider the rich data sources in the actual environment, such as the impact of human flow, road network POI, etc. on site setting and optimization

[0008] 2) In the existing traffic visualization research, there are few studies on optimizing the location of bus stops using multi-source data, and the existing research has shortcomings such as simple analysis, single visual view, lack of view interaction linkage, and no systematic analysis process. The analysis effect is not intuitive

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