Using Taxi GPS Trajectory Data to Optimize the Spatial Layout of Urban Taxi Stands

Wang, Xin; Qu, Zhaowei; Song, Xianmin; Li, Haitao; Pan, Zhaotian

doi:10.1177/0361198120970537

Cited by 4 publications

(2 citation statements)

References 35 publications

(51 reference statements)

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“…The LBS applications are used for tracking users ( Chen et al, 2020a ), routing prediction ( Wang et al, 2020 ), and to predict the revenue from ride-on-demand applications ( Guo et al, 2020 ) in outdoor applications. However, wireless sensing is mainly used for indoor localization ( Maghdid et al, 2019 ) and event detection ( Sharma & Singh, 2021 ) in indoor applications.…”

Section: Related Workmentioning

confidence: 99%

Novel integrated matching algorithm using a deep learning algorithm for Wi-Fi fingerprint-positioning technique in the indoors-IoT era

Asaad

Maghdid

2023

PeerJ Computer Science

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The Internet-of-Things (IoT) has been used with greater frequency to track peoples’ daily activities, particularly those conducted indoors. Wi-Fi technology has been also been used as an alternative to global navigation satellite system (GNSS) technologies to track indoor activities. The received signal strength indicator (RSSI) is widely used to assist in the positioning of Wi-Fi signals. However, the RSSI-based technique suffers from multipath, non-line-of-sight (NLOS) problems and the fluctuation of RSSI measurements via Wi-Fi chipsets. One of the most well-known RSSI-based approaches is to apply the fingerprinting method to do the positioning. However, the fingerprinting-based form has an additional problem due to the lack of RSSI data samples, specifically in harsh area with a huge number of classes or reference points (RPs) and an unstable matching process algorithm. To mitigate the problems of the RSSI-based fingerprinting approach, this research proposes a novel matching process algorithm called Norm_MSATE_LSTM. We first performed the augmentation process to increase the RSSI data records via the Mean Stander deviation Augmentation TEchnique (MSATE). The RSSI records were normalized (norm), and the long short-term memory (LSTM) technique was applied to estimate the correct positions. Finally, the proposed matching algorithm was compared with the stand-alone matching algorithms, including the weighted k-nearest neighbors (WkNN) and LSTM. The results obtained from the experiments and the simulated experiments using OMNeT++ show that the proposed matching algorithm may improve positioning accuracy by 33.1% and 57.5% when only augmentation and augmentation with normalization are applied, respectively.

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Section: Related Workmentioning

confidence: 99%

Novel integrated matching algorithm using a deep learning algorithm for Wi-Fi fingerprint-positioning technique in the indoors-IoT era

Asaad

Maghdid

2023

PeerJ Computer Science

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“…The method proposed in this article may be useful for traffic managers planning urban roads, reducing congestion levels, detecting hotspots, improving traffic flow, identifying anomalous traffic situations, and predicting future behaviors ( 17 ). Furthermore, better traffic flow management leads to environmental improvements.…”

mentioning

confidence: 99%

Proposal for a Pivot-Based Vehicle Trajectory Clustering Method

Reyes

Lanzarini

Hasperué

et al. 2021

Transportation Research Record: Journal of the Transportation R

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Given the large volume of georeferenced information generated and stored by many types of devices, the study and improvement of techniques capable of operating with these data is an area of great interest. The analysis of vehicular trajectories with the aim of forming clusters and identifying emerging patterns is very useful for characterizing and analyzing transportation flows in cities. This paper presents a new trajectory clustering method capable of identifying clusters of vehicular sub-trajectories in various sectors of a city. The proposed method is based on the use of an auxiliary structure to determine the correct location of the centroid of each group or set of sub-trajectories along the adaptive process. The proposed method was applied on three real databases, as well as being compared with other relevant methods, achieving satisfactory results and showing good cluster quality according to the Silhouette index.

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Subway Flow Prediction Based on Improved Support Vector Machine

Qin

et al. 2021

2021 8th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/2021 7th IEEE International Conference O

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Using Taxi GPS Trajectory Data to Optimize the Spatial Layout of Urban Taxi Stands

Cited by 4 publications

References 35 publications

Novel integrated matching algorithm using a deep learning algorithm for Wi-Fi fingerprint-positioning technique in the indoors-IoT era

Novel integrated matching algorithm using a deep learning algorithm for Wi-Fi fingerprint-positioning technique in the indoors-IoT era

Proposal for a Pivot-Based Vehicle Trajectory Clustering Method

Subway Flow Prediction Based on Improved Support Vector Machine

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