Big data in public transportation: a review of sources and methods

To improve the mode share of public transport and reduce the transition to private transport of passengers waiting at bus station, the mechanism of passengers’ decision-making procedure and influence factors of the travel mode choice were analyzed. Some latent variables such as safety, comfort, convenience, flexibility and economy were selected to reflect the satisfaction degree of passengers on the service level of public transport. Taking Jinan City as an example, the questionnaire of passengers’ travel choice behavior at bus station was designed and carried out. Based on the structure equation model (SEM), the relationship between the satisfaction degree and some latent variables such as safety and comfort was discussed. The SEM method analysis shows that, of the influence level of the latent variables to the service level of public transport, flexibility is the most significant variable affecting passenger’s satisfaction degree followed by safety, convenience, comfort and economy. Travel mode choice model of passengers waiting at bus station was established with an integration approach of SEM and nested logit (NL) model. The SEM-NL integration model results reveal that gender, monthly income, purpose of the trip, travel distance, safety and convenience service level have a significant effect on the choice of the upper model (public transport or private transport). Passenger’s age, vehicle ownership and bus ride frequency have great influence on the choice of the lower mode (ORB: original route bus; ARB: alternative route bus; Taxi; and Shared bike). Sensitivity analysis reveals that the transition probabilities from private transport to public transport can reach the highest point (respectively, 69.85%, 68.84% and 35.51%) when safety service reaches level 4, convenience service reaches level 3, or comfort service reaches level 2, indicating that the safety level equal to 4, convenience level equal to 3 and comfort level equal to 2 are the key threshold to increase the public transport mode share. Some proposals such as ensuring good accessibility of public transport, shortening the transfer distance of different routes, creating a comfortable travel environment and integrating bus ticket system have been put forward for the sustainable development of public transport system.

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Research on Passenger’s Travel Mode Choice Behavior Waiting at Bus Station Based on SEM-Logit Integration Model

Transport decision-making problems are typically spatially based and involve a set of feasible alternatives with multiple evaluation criteria. Besides, transport decisions affect citizens’ quality of life, as well as specific interests of general stakeholders (e.g., transport companies), thus needing a participatory approach to decision-making. Geographic Information Systems (GIS) have the ability to visualize spatial data and represent the impact of location based transport alternatives, thus helping experts to conduct robust assessments. Moreover, with the recent diffusion of Volunteered Geographic Information (VGI) and development of Public Participatory GIS (PPGIS) platforms, the process can be enhanced thanks to the collection of a large amount of updated spatial data and the achievement of an active community participation. In this study, we provide an overview based on a structured literature review of the use of VGI and PPGIS in transport studies, exploring the fields of application, role played by GIS, level of public involvement and decision stage at which they are applied. From the overview’s results, we propose a general framework for the evaluation of transport alternatives using GIS from a multiple stakeholder point of view; the main conclusion is the usefulness of the integration between Public Participation, GIS and quantitative evaluation methods, in particular Multi Criteria Decision Analysis, in order to foster technically sound and shared decisions.

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Mapping with Stakeholders: An Overview of Public Participatory GIS and VGI in Transport Decision-Making

With the development of information technique and wireless communication, a vast number of taxis' and ride-sharing cars' trajectory data that provide a rich and detailed source to study on-demand services have been collected. The increasing available trajectory data bring benefits and new challenges to the studies of on-demand services. To provide an overview of the benefits and challenges brought by the trajectory data, we provide a survey on recent studies of trajectory analysis (refer to analyzing trajectory datasets) for on-demand services in this paper. Our purposes are at least trifold. First, we highlight the value of trajectory data in understanding on-demand services and discuss the procedures of retrieving information for the demand part and the supply part from raw trajectory data. Second, we categorize related studies into three parts (the demand part, the supply part, and the mixed part) and review the significant findings. For the demand part, we focus on the models proposed for describing and explaining the spatial-temporal characteristics of observed trips. Methods or models proposed for describing trip statistics, scaling laws of trips, and dynamics of ridership are reviewed. We summarize four types of factors that influence the spatial-temporal patterns of demands. For the supply part, we focus on the models proposed for describing the spatial-temporal characteristics of available taxis/ride-sharing cars and modeling the behavior of drivers (i.e., passenger-search behavior and route choice behavior) to explain the spatial-temporal patterns of taxi/ride-sharing supplies. For the mixed part, we focus on studies that apply the uncovered demands/supplies patterns to design recommendation systems and pricing strategies. Third, we discuss the future directions on collecting/releasing trajectory data and future research directions to advance the understanding of on-demand services.

Trajectory analysis for on-demand services: A survey focusing on spatial-temporal demand and supply patterns

Making transport systems sustainable is a topic that has attracted the attention of many researchers and urban planners. The Association of Southeast Asian Nations (ASEAN) Smart Cities Network (ASCN) was initiated to develop a sustainable transport system in the ASEAN countries. A comprehensive understanding of street networks (SNs) can contribute significantly to the achievement of this initiative. Therefore, this paper measured and compared characteristics of drivable street networks (DSNs) and walkable street networks (WSNs) of the 26 ASCN pilot cities by applying multiple network metrics. The OSMnx tool was used to download and analyse WSNs and DSNs from the OpenStreetMap. The findings present the topological and geometric characteristics of WSNs and DSNs that are diverse and characterized by different factors. The cities with orthogonal street grids, high street density, intersection density, and fewer cul-de-sacs have good accessibility to reach destinations. In contrast, some other cities have more curvilinear and circuitous SNs with many missing links to other streets, which in turn are prone to traffic disruption. The study highlights the important features of SNs that have significant implications for future designs of SNs in the ASCN whose goal is to make cities smart and liveable for ASEAN members.

Analysis of Urban Drivable and Walkable Street Networks of the ASEAN Smart Cities Network

A longer, wider and more complicated change in the travel path is put forward to adapt to the rapidly increasing expansion of metropolises in the field of urban travel. Urban travel requires higher levels of sustainable urban transport. Therefore,this paper explores the circuity characteristics of urban travel and investigates the temporal relationship between time and travel circuity and the spatial relationship between distance and travel circuity to understand the efficiency of urban travel. Based on Guangzhou Taxi-GPS big data, travel circuity is considered in this paper to analyze the circuity spatial distribution and strength characteristics of urban travel in three types of metropolitan regions, including core areas, transition areas and fringe areas. Depending on the different attributes of the three types, the consistency and dissimilar characteristics of travel circuity and influencing factors of travel circuity in metropolises are discussed. The results are shown as follows: (1) by observing the temporal andspatial distribution of travel circuity, it can be found that peaks and troughs change with time, and travel circuity of transition areas is higher than other areas during the peak period. When travelling in these three regions, travel circuity spatial distribution is consistent, which is the core-periphery distribution. When travelling among these three regions, travel circuity spatial distribution is distinct; (2) by analyzing the relationship between time and distance of travel and travel circuity, it can be seen that the shorter the travel time or travel distance, the greater the travel circuity, resulting in a lower travel efficiency; (3) the influence of six factors, including population, road and public transportation, on travel circuity is significant. Whether it is the origin point or destination point, when its location is closer to the city center and the station density of grid is lower, the travel circuity is higher.

Yongwei Liu

Papers

Circuity Characteristics of Urban Travel Based on GPS Data: A Case Study of Guangzhou