Exploring Spatiotemporal Patterns of Long-Distance Taxi Rides in Shanghai

Wu, Hangbin; Fan, Hongchao; Wu, Shengyuan

doi:10.3390/ijgi6110339

Cited by 11 publications

(4 citation statements)

References 16 publications

(16 reference statements)

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“…Therefore, we can conclude from the above that most travel distances are less than 30 min for OCH, and thus, OCH may not be the best mode of transportation for long distances. When faced with a long-duration trip, people prefer to select other transportation modes instead of OCH given the higher cost ( 41 ). There are still some long-duration trips, however, which may result from the lack of other modes of transport or to avoid the traffic peak hours.…”

Section: Resultsmentioning

confidence: 99%

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Evaluating the Nonlinear Impacts of Built Environment on Online Car-Hailing: Focus on the Whole Day

Zhou

2023

Transportation Research Record: Journal of the Transportation R

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Understanding the relationship between the built environment and online car-hailing travel behavior can greatly influence sustainable urban development. These complex impacts are not fully understood from a whole-day perspective. This paper took the central urban area of Nanning, China as a case study, and analyzed the data of 1,154,759 online car-hailing service orders collected by the Nanning Information Center over the course of a week. Thiessen polygons based on road networks were used to divide the research area. A partial dependence plot and random forest regression were used to examine the nonlinear impacts of the built environment (home-work attributes, traffic facility attributes, land use, and diversity) on online car-hailing trip demand throughout the day. The results show that the built environment elements that affect the demand for online car-hailing differ at different times of the day and that they have different ranges of influence. For example, residential areas play an important role in the commuter period for demand with a contribution rate of 33.2%, while the contribution rates for the remaining periods are less than 5%. In the whole day, cultural services, health services, leisure sports services, and catering services are important factors. And if there are enough training institutions to form a separate trading area within a city, this will have a profound impact on travel demand. In comparison to subway stations, bus stations contribute more to the demand. The study results will assist the government in improving urban transportation coordination.

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Section: Resultsmentioning

confidence: 99%

“…There are still some long-duration trips, however, which may result from the lack of other modes of transport or to avoid the traffic peak hours. Those passengers are willing to choose OCH instead of the metro as their first priority, and their second concern is avoiding the metro’s inconvenience resulting from the interchanges ( 41 ).…”

Section: Resultsmentioning

confidence: 99%

Evaluating the Nonlinear Impacts of Built Environment on Online Car-Hailing: Focus on the Whole Day

Zhou

2023

Transportation Research Record: Journal of the Transportation R

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“…These results suggest that urban functions and function mixes may influence the residential travel carbon emissions of taxis and hence commuting carbon emissions. However, some studies have shown that excessive travel distance may lead to a preference for using taxis to travel with a threshold value of 15 km [49], which is similar to the distance from the central city area to Xiasha Cheng. From the results of previous experiments and studies, we speculate that this phenomenon may be due, on the one hand, to the fact that Xiasha Cheng is located far from the main urban area and is a fully functional integrated new city with better jobs, housing, and functions.…”

Section: The Impact Of Urban Spatial Structure and The Construction O...mentioning

confidence: 99%

A Big Data-Based Commuting Carbon Emissions Accounting Method—A Case of Hangzhou

Xue

Xia

et al. 2022

Land

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Commuting carbon emissions are an essential component of urban carbon emissions, and determining how to reduce them is an area of great debate among researchers. The current research lacks a tool and instrument that can extensively account for residents’ commuting. Traditional methods are mainly based on questionnaire surveys, which have low accuracy at spatial and temporal aspects. High accuracy carbon emission accounting methods can effectively assist urban planning and achieve precise urban emissions reductions. This study applies a taxi commuting carbon emissions accounting method divided into two main steps. Firstly, the carbon emissions of taxi trajectories are calculated using taxi trajectory data and a carbon emission calculation method developed based on VSP. Secondly, the taxi trajectory and POI data are used to filter the commuter trajectory with the help of a two-step moving search method. In this way, the taxi commuting carbon emissions were obtained. Then, the spatial distribution characteristics of residential taxi commuting carbon emissions are analysed by spatial autocorrelation tools, which could facilitate low carbon zoning management. A typical working day in Hangzhou was selected as the research object of this study. The results show that (1) morning peak commuting carbon emissions in the main urban area of Hangzhou reached 2065.14 kg per hour, accounting for 13.73% of all taxi travel carbon emissions; and evening peak commuting carbon emissions reached 732.2 kg per hour, accounting for 4% of all taxi travel carbon emissions; (2) At the grid level, the spatial distribution of commuting carbon emissions in Hangzhou shows a single central peak that decays in all directions; and (3) The results at the resident community scale show that urban public transport facilities influence resident community commuting carbon emissions. In areas such as at the urban-rural border, resident community commuting carbon emissions show high levels of aggregation, and in the main urban area, resident community commuting carbon emissions show low levels of aggregation. This study not only provides a new method of commuting investigation but also offers constructive suggestions for future carbon emission reduction under Hangzhou’s urban planning.

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“…Through similarity measurements of trajectory data, valuable information can be mined from large collections of trajectories, such as traffic flows and hot routes [9,10]. It is very useful for many applications, such as urban hotspot detection [11,12], behavior model analysis [13,14], traffic monitoring and prediction [15][16][17], urban planning [18,19] and location optimization [20,21], etc. Advances in location-based applications are increasingly creating new, sophisticated mechanisms that can foster the exchanges of information among travels to provide better services and promote a sustainable economy.…”

Section: Introductionmentioning

confidence: 99%

A Grid-Based Approach for Measuring Similarities of Taxi Trajectories

Wei

Fan

Midtbø

2020

Sensors

Self Cite

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Similarity measurement is one of the key tasks in spatial data analysis. It has a great impact on applications i.e., position prediction, mining and analysis of social behavior pattern. Existing methods mainly focus on the exact matching of polylines which result in the trajectories. However, for the applications like travel/drive behavior analysis, even for objects passing by the same route the trajectories are not the same due to the accuracy of positioning and the fact that objects may move on different lanes of the road. Further, in most cases of spatial data mining, locations and sometimes sequences of locations on trajectories are most important, while how objects move from location to location (the exact geometries of trajectories) is of less interest. For the abovementioned situations, the existing approaches cannot work anymore. In this paper, we propose a grid aware approach to convert trajectories into sequences of codes, so that shape details of trajectories are neglected while emphasizing locations where trajectories pass through. Experiments with Shanghai Float Car Data (FCD) show that the proposed method can calculate trajectories with high similarity if these pass through the same locations. In addition, the proposed methods are very efficient since the data volume is considerably reduced when trajectories are converted into grid-codes.

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Exploring Spatiotemporal Patterns of Long-Distance Taxi Rides in Shanghai

Cited by 11 publications

References 16 publications

Evaluating the Nonlinear Impacts of Built Environment on Online Car-Hailing: Focus on the Whole Day

Evaluating the Nonlinear Impacts of Built Environment on Online Car-Hailing: Focus on the Whole Day

A Big Data-Based Commuting Carbon Emissions Accounting Method—A Case of Hangzhou

A Grid-Based Approach for Measuring Similarities of Taxi Trajectories

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