Liya Yao

Research on the Behavior Characteristics of Pedestrian Crowd Weaving Flow in Transport Terminal

Due to the poor transfer organization in urban public transport terminal, pedestrian crowd are often forced to weaving in their transfer flow lines. Frequent weaving behaviors not only decrease passengers’ transfer comfort, but may also trigger serious crowd disaster such as trampling. In order to get accurate understanding of the weaving features of pedestrian crowd and analyze the relevant evolution law, researches have been conducted on the basis of field investigation. First, the typical weaving phenomenon were defined and classified, and a microscopic parameters system of pedestrian crowd weaving flow was constructed. The detection and quantification methods of multiple indicator parameters were also given. Then, correlation between different behavioral parameters was analyzed based on the survey data of weaving pedestrian crowd on the stairs of DongZhiMen (DZM) hub. The basic characteristics and evolution law of the weaving behaviors were then discussed, and conclusions were drawn.

Entropy-based estimation of transfers in a terminal

An intermodal transportation terminal is a facility that provides commuters with easy transfer between transit modes and providers such as buses, light rail, subway, taxis, airport shuttles, and commuter rail. The probability of a passenger transferring from one mode to another and the estimation of total transfer demand are of great importance to both practitioners and researchers when determining optimal design alternatives as well as the best control and management policies for daily operation of the terminal. This article presents a study that uses an entropy-based optimization approach to estimate the transfer demands between the available transportation modes in an intermodal transportation terminal. The development and calibration of the entropy model is presented in the first part of the article, which is followed by a case study of the SiHui Intermodal Terminal in Beijing, China.

Properties Analysis on Travel Intensity of Land Use Patterns

Quantization of the relationship between travel intensity and land use patterns is still a critical problem in urban transportation planning. Achieved researches on land use patterns are restricted to macrodata such as population and area, which failed to provide detail travel information for transportation planners. There is still problem on how to reflect the relationship between transport and land use accurately. This paper presents a study that is reflective of such an effort. A data extraction method is developed to get the travel origin and destination (OD) between traffic zones based on the mobile data of 100,000 residents in Beijing. Then Point of Interests (POIs) data in typical traffic zones was analyzed combined with construction area investigation. Based on the analysis of travel OD and POI data, the average travel intensity of each land use pattern is quantified. Research results could provide a quantitative basis for the optimization of urban transportation planning.

Estimation of transit ridership based on spatial analysis and precise land use data

This paper focuses on land use as the primary variable for transit ridership estimation, with 100 000 points of interest (POIs) in Beijing being extracted from a digital map and classified into five categories according to main transit trip purposes. To better quantify the characteristics of the land surrounding a transit station and further assist sustainable zoning, a multi-level catchment area delineation method that includes pedestrian, traffic, and potential areas is applied. The built areas of different categories of POIs within various catchment areas are used to describe precise land use characteristics of 24 randomly selected transit stations in Beijing. A direct ridership model that involved land use characteristics is developed and combined with the ridership calculated using Beijing transit auto fare collection (AFC) data. Model validation with 10 other randomly selected stations meets initial expectations, indicating that the proposed model has the potential for use to provide a quantitative link between land use and travel demand.