Article
Engineering, Civil
Yang Zhou, Yuantao Zhang, Quan Yuan, Chao Yang, Tangyi Guo, Yinhai Wang
Summary: Travel data is crucial for understanding individual travel behaviors and estimating travel demand. This study proposes a high-accuracy data collection system based on smartphones, and a hybrid random forest and merging algorithm is used to more accurately and efficiently identify travel modes in complex trips.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Zhenxing Yao, Fei Yang, Yudong Guo, Peter Jing Jin, Yan Li
Summary: This paper proposes a method for trip end identification using smartphone GNSS positioning data. It uses a spatial-temporal density-based clustering algorithm for initial identification and optimization models to further optimize the results. Field tests show that the method is feasible and effective.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Transportation
Abdhul Khadhir, B. Anil Kumar, Lelitha Devi Vanajakshi
Summary: The rapid advancements in sensor technologies have led to increased use of AVL systems for traffic data collection. This study analyzed travel time data from buses in Chennai, India to understand variation over time and space, finding critical points during peak hours. Analysis showed a significant increase in travel time and its variation from 2014 to 2016, primarily concentrated at six critical intersections.
JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS
(2021)
Article
Astronomy & Astrophysics
Christopher W. Johnson, Nicholas Lau, Adrian Borsa
Summary: The study found discrepancies in GPS station velocity estimates among different analysis centers, with vertical differences being more significant. Actual velocity uncertainties are often underestimated in the horizontal direction and may be over or underestimated in the vertical direction. Subsidence rates vary widely in different regions, with station density having a modest impact on uncertainties.
EARTH AND SPACE SCIENCE
(2021)
Article
Sport Sciences
Ross J. Brosnan, Greig Watson, Will Stuart, Craig Twentyman, Cecilia M. Kitic, Matthew Schmidt
Summary: This study investigates the validity, reliability, and agreement of three commonly used GPS units in applied and research settings. The results show good performance in distance and speed, but caution is needed in acceleration indices.
JOURNAL OF STRENGTH AND CONDITIONING RESEARCH
(2022)
Article
Engineering, Civil
Minh Hieu Nguyen, Jimmy Armoogum, Emeli Adell
Summary: This study introduces a method to enhance purpose imputation from global positioning system data by selecting relevant features, showing that the addition of actual or predicted travel modes improves imputation performance, with actual modes having a stronger effect. The newly adopted MFVP feature contributes to better prediction results, and the purpose-imputation models utilizing all features achieve high accuracy levels on both datasets.
TRANSPORTATION RESEARCH RECORD
(2021)
Article
Computer Science, Information Systems
Seunghyeon Lee, Hong-Woo Seok, Ki-rim Lee, Hoh Peter In
Summary: In this study, a prototype system was developed to improve the reliability and data integrity of national reference point surveys by using blockchain technology to record GPS data and correction data.
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
(2022)
Article
Engineering, Civil
Zeqian Jin, Yanyan Chen, Chen Li, Zexin Jin
Summary: Predicting trip destinations for individuals based on their travel patterns has significant research value. This paper utilizes a hidden Markov model (HMM) with multi-day GPS data and travel survey to predict weekday and weekend travel destinations. The results show that residence and workplace are the most frequent activities, and the method can be applied to real-time travel navigation and health and safety fields.
TRANSPORTATION RESEARCH RECORD
(2023)
Review
Transportation
Adham Badran, Ahmed El-Geneidy, Luis Miranda-Moreno
Summary: With the popularity of smartphones and mobile internet, GPS data from vehicles has become widely available. This data provides a unique opportunity to automatically extract road network features and generate detailed maps for transport network models, reducing the usual resource investment. However, current studies lack systematic exploration and evaluation of road network inference methods from a transport network modelling perspective. This research aims to address this gap by conducting a systematic and reproducible literature review on the use of GPS data in transport network modelling, highlighting limitations and future work for road network representation in transport models and autonomous vehicles navigation.
Article
Remote Sensing
Asmamaw Yehun, Tsegaye Gogie, Martin Vermeer, Addisu Hunegnaw
Summary: The study estimated the integrated precipitable water vapor in the atmosphere using GPS and LEO data, revealing significant variations in water vapor content across different regions in Ethiopia, with high correlation to other forecasting systems. Analyzing changes across different time scales, the study identified substantial variations in precipitable water vapor in the study area.
INTERNATIONAL JOURNAL OF REMOTE SENSING
(2021)
Article
Chemistry, Analytical
Abdulkadir Uzun, Firas Abdul Ghani, Amir Mohsen Ahmadi Najafabadi, Husnu Yenigun, Ibrahim Tekin
Summary: This paper presents an indoor positioning system using GPS signals in the 433 MHz ISM band, demonstrated experimentally under both line-of-sight and non-line-of-sight conditions on a building floor. The system utilizes down-converting repeaters and an up-converting receiver to transmit and receive GPS signals effectively for indoor positioning.
Article
Physics, Multidisciplinary
Tatsuro Mukai, Yuichi Ikeda
Summary: This study develops a method for evaluating the mobility of people in a city using GPS data, including evaluating human mobility using temporal networks and searching for the shortest path by solving the time-dependent traveling salesman problem. The results show that considering congestion leads to more realistic estimations.
FRONTIERS IN PHYSICS
(2022)
Article
Computer Science, Hardware & Architecture
Gabriela Ahmadi-Assalemi, Haider M. Al-Khateeb, Carsten Maple, Gregory Epiphaniou, Mohammad Hammoudeh, Hamid Jahankhani, Prashant Pillai
Summary: Connected cars with sensors and computational processing can model and differentiate drivers for enhanced security. Research data demonstrates that driving patterns can be used to distinguish between drivers of different genders.
COMPUTERS & ELECTRICAL ENGINEERING
(2021)
Article
Computer Science, Software Engineering
Chen Liang, Meixia Miao, Jianfeng Ma, Hongyang Yan, Qun Zhang, Xinghua Li
Summary: Most of the existing GPS spoofing detection schemes are vulnerable to generative GPS spoofing attacks or require additional equipment and extensive signal processing capabilities, which are not suitable for UAV systems. To address this, we propose a novel solution that combines GPS receiver and inertial measurement unit information fusion. Experimental results show that our method can accurately detect spoofing attacks in 8 seconds with a detection rate of 98.6%. Compared to existing schemes, our method improves real-time detection performance while maintaining a high detection rate. In the worst-case scenario, we can detect the spoofing attack within 28 seconds after the UAV system starts its mission.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2022)
Article
Chemistry, Analytical
Youssef Chebli, Samira El Otmani, Jean-Luc Hornick, Jerome Bindelle, Jean-Francois Cabaraux, Mouad Chentouf
Summary: This study utilized advanced electronic sensors to investigate the grazing activity and protein-energy requirements of dairy goats in a Mediterranean woodland, finding that grazing time was shorter in summer and protein-energy intake often insufficient. The combination of GPS collars and accelerometers provided valuable insights for goat-feeding strategies.
Article
Transportation Science & Technology
Yue Zhao, Liujiang Kang, Huijun Sun, Jianjun Wu, Nsabimana Buhigiro
Summary: This study proposes a 2-population 3-strategy evolutionary game model to address the issue of subway network operation extension. The analysis reveals that the rule of maximum total fitness ensures the priority of evolutionary equilibrium strategies, and proper adjustment minutes can enhance the effectiveness of operation extension.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
Article
Transportation Science & Technology
Hongtao Hu, Jiao Mob, Lu Zhen
Summary: This study investigates the challenges of daily storage yard management in marine container terminals considering delayed transshipment of containers. A mixed-integer linear programming model is proposed to minimize various costs associated with transportation and yard management. The improved Benders decomposition algorithm is applied to solve the problem effectively and efficiently.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
Article
Transportation Science & Technology
Zhandong Xu, Yiyang Peng, Guoyuan Li, Anthony Chen, Xiaobo Liu
Summary: This paper studied the impact of range anxiety among electric vehicle drivers on traffic assignment. Two types of range-constrained traffic assignment problems were defined based on discrete or continuous distributed range anxiety. Models and algorithms were proposed to solve the two types of problems. Experimental results showed the superiority of the proposed algorithm and revealed that drivers with heightened range anxiety may cause severe congestion.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
Article
Transportation Science & Technology
Chuanjia Li, Maosi Geng, Yong Chen, Zeen Cai, Zheng Zhu, Xiqun (Michael) Chen
Summary: Understanding spatial-temporal stochasticity in shared mobility is crucial, and this study introduces the Bi-STTNP prediction model that provides probabilistic predictions and uncertainty estimations for ride-sourcing demand, outperforming conventional deep learning methods. The model captures the multivariate spatial-temporal Gaussian distribution of demand and offers comprehensive uncertainty representations.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
Article
Transportation Science & Technology
Benjamin Coifman, Lizhe Li
Summary: This paper develops a partial trajectory method for aligning views from successive fixed cameras in order to ensure high fidelity with the actual vehicle movements. The method operates on the output of vehicle tracking to provide direct feedback and improve alignment quality. Experimental results show that this method can enhance accuracy and increase the number of vehicles in the dataset.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
Article
Transportation Science & Technology
Mohsen Dastpak, Fausto Errico, Ola Jabali, Federico Malucelli
Summary: This article discusses the problem of an Electric Vehicle (EV) finding the shortest route from an origin to a destination and proposes a problem model that considers the occupancy indicator information of charging stations. A Markov Decision Process formulation is presented to optimize the EV routing and charging policy. A reoptimization algorithm is developed to establish the sequence of charging station visits and charging amounts based on system updates. Results from a comprehensive computational study show that the proposed method significantly reduces waiting times and total trip duration.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)