Analysis of the Passenger Pick-Up Pattern for Taxi Location Recommendation

Lee, Junghoon; Shin, In-Hye; Park, Gyung-Leen

doi:10.1109/ncm.2008.24

Cited by 93 publications

(54 citation statements)

References 6 publications

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“…For example, Lee et al [11] performed a temporal analysis to create a time-dependent pick-up pattern within each area and recommended that empty taxis go to the nearest cluster locations derived by the k-means method to pick up customers. Wang et al [12] investigated the travel patterns to and from hotspots.…”

Section: Spatial Pattern Of Taxicabsmentioning

confidence: 99%

Understanding the Effect of an E-Hailing App Subsidy War on Taxicab Operation Zones

Fang

Lian³

2018

Journal of Advanced Transportation

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Understanding taxicab operation behaviors under various management or market policies (i.e., subsidies) is critical to making informed operating decisions for e-hailing companies and for government surveillance. This paper investigates the change of taxicab operation zones in context of an e-hailing app subsidy war in China, which is an important perspective that reflects changes in taxicab behavior, such as how the operation zones of taxicabs under the e-hailing app subsidy war change and how this change affects their trip distance and cruising time. To investigate this issue, this paper utilizes three indexes to elucidate the change of taxicab operation zones, namely, the repetition ratio of operation zone pairs, the area, and the degree of dispersion in the spatial distribution. A case study using taxicab trajectories during all of the important periods of the e-hailing app subsidy war in Shenzhen, China, was conducted and produced several valuable findings; for example, with respect to taxicabs as a whole, the proportion of habitual operation zone pairs among operation zone pairs in neighboring periods is relatively stable under any subsidy policy, and changes in the operation zones have little effect on changes in the average daily trip distance and average daily cruising time. Four groups of taxicabs divided according to initial change patterns in the operation zones present different change patterns during the subsidy war. By comparing these changes before and after the subsidy war, this paper finds that the subsidy war influences the taxicabs in groups I and II, while it has little influence on the taxicabs in groups III and IV, although all groups were affected during the subsidy war. For the taxicab groups in the period with the highest subsidy, the average daily trip distance and average daily cruising time decreased, whereas, in other periods, they presented different patterns.

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Section: Spatial Pattern Of Taxicabsmentioning

confidence: 99%

Understanding the Effect of an E-Hailing App Subsidy War on Taxicab Operation Zones

Fang

Lian³

2018

Journal of Advanced Transportation

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“…Literature [4] proposed a Hausdorff distance similarity measure based on line segments to detect anomalies in moving objects. The literature [5,6,7,8] detects and analyzes hotspots of on-road and off-road passengers in road network space. On the one hand, it improves people's perception of urban spatial dynamics, and on the other hand, it provides guidance for the vehicle to find passengers as soon as possible.…”

Section: Related Workmentioning

confidence: 99%

DBSCAN-Based No-Load Road Detection Algorithm

2018

2018 3rd International Conference on Materials Science, Machinery and Energy Engineering (MSMEE 2018)

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Abstract:Taxi plays an important role in the urban passenger transport system. Good taxi service quality will help increase the happiness of urban residents. However, the issue of no-load taxis has always been one of the most concerned issues for urban managers. This paper uses the improved DBSCAN method to carry on the cluster analysis to the taxi trajectory, prompts the taxi driver to avoid the no-load area, and achieves the purpose that to raise the taxi utilization factor. The improved DBSCAN method introduces two distance metrics, segment feature distance and dynamic space-time distortion distance. The feature distances of the segment include the vertical distance, horizontal distance, and angular distance, which can effectively measure the distance between trajectory segments. The dynamic space-time distortion distance introduces spatial factors on the basis of the dynamic distortion distance, and successfully overcomes the similarity error problem caused by different trajectory lengths. At the same time, using the GPS data set of Nanjing taxi to carry out experiments, the results show that the algorithm has higher accuracy and stability than the algorithms in the literature.

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“…However, taxi dispatching is not the only aspect that can be optimized. For example, Lee et al [LSP08] and Jia et al [Jia08] use real-time vehicle information to propose a model for taxi relocation recommendation based on demand forecasting and a probability model for the design of taxi stops, respectively.…”

Section: Elementary Relationsmentioning

confidence: 99%

Design and operation for an electric taxi fleet

Gacias

Meunier

2014

OR Spectrum

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Abstract. The deployment of electric taxi fleets is highly desirable from a sustainable point of view. Nevertheless, the weak autonomy of this kind of vehicles requires a careful operation. The way of managing such a fleet and the question of locating charging terminals for the vehicles are addressed in this paper. Methods for dealing with these tasks are proposed and their efficiency is proved through simulations.

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Analysis of the Passenger Pick-Up Pattern for Taxi Location Recommendation

Cited by 93 publications

References 6 publications

Understanding the Effect of an E-Hailing App Subsidy War on Taxicab Operation Zones

Understanding the Effect of an E-Hailing App Subsidy War on Taxicab Operation Zones

DBSCAN-Based No-Load Road Detection Algorithm

Design and operation for an electric taxi fleet

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