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1

The analysis of urban taxi carpooling impact from taxi GPS data

Xiao Q., He R., Ma C.

Archives of Transport

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2018

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Vol. 47, iss. 3

109--120

EN

Taxi is an important part of urban passenger transportation system. The research and analysis of taxi trip behavior is the key to meet the demand of urban passenger transport and solve the traffic congestion problem. Based on the GPS data of taxis in Nanjing, the statistical method is used to analyze the taxi characteristics of the average number of passengers, the average passenger time, the no-load distance and the passenger distance. By using the double logarithmic coordinate, the trip distance and trip time of taxi passengers are analyzed, it is found that the average trip distance of taxi passengers is mainly concentrated in 3-20 km, and the average trip time of taxi passengers is mainly concentrated in 10-30 minutes. Using the information entropy theory to construct the equilibrium model of taxi passenger-carrying point, and analyze the spatial distribution of taxi, it is found that the distribution of urban taxi is unbalanced. The peak clustering algorithm is used to determine the location of passenger gathering points, and the hot spot of taxi trip is analyzed, it is found that the hot spots of taxi trip are mainly concentrated in the central city of Nanjing. Combined with the results of urban taxi trip analysis, from the perspective of taxi and passenger, we found that the number of urban taxis, the passenger carrying rate of taxis, the duration period of passenger trip, the duration and distance of passenger trip and the location of passenger trip points will have an impact on the urban taxi carpooling in Nanjing. By using the probability model of urban taxi carpooling, this paper discusses and analyzes the influence of these factors on urban taxi carpooling. The research in this paper can provide a reference for the effective implementation of urban taxi carpooling policy.

2

Carpooling Scheme Selection for Taxi Carpooling Passengers: a Multi-Objective Model and Optimisation Algorithm

Xiao Q., He R.-C.

Archives of Transport

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2017

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Vol. 42, iss. 2

85--92

EN

Carpooling has been long deemed a promising approach to better utilizing existing transportation infrastructure, the carpooling system can alleviate the problems of traffic congestion and environmental pollution effectively in big cities. However, algorithmic and technical barriers inhibit the development of taxi carpooling, and it is still not the preferred mode of commute. In order to improve carpooling efficiency in urban, a taxi carpooling scheme based on multi-objective model and optimisation algorithm is presented. In this paper, urban traffic road network nodes were constructed from the perspective of passenger carpooling. A multi-objective taxi carpooling scheme selection model was built based on an analysis of the main influences of carpooling schemes on passengers. This model aimed to minimise get-on-and-get-off distance, carpooling waiting time and arriving at the destination. Furthermore, a two-phase algorithm was used to solve this model. A rapid searching algorithm for feasible routes was established, and the weight vector was assigned by introducing information entropy to obtain satisfying routes. The algorithm is applied to the urban road, the Simulation experimental result indicates that the optimisation method presented in this study is effective in taxi carpooling passengers.

3

Efficient coding of LSP parameters using Compressed Sensing on Approximate KLT Domain

Xiao Q., Chen L., Zhu T., Wang Y.

Przegląd Elektrotechniczny

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2011

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R. 87, nr 7

230-234

EN

An efficient LSP parameters quantization scheme is proposed using the compressed sensing (CS). The LSP parameters extracted from consecutive speech frames are compressed by CS on the approximate KLT domain to produce a measurement vector, which is quantized using the split vector quantizer. Then, from the quantized measurements, the original LSP parameters are reconstructed by the orthogonal matching pursuit method. Experiments show that the scheme can obtain "transparent quality" at 5 bits/frame with drastic bits reduction compared to other methods.

PL

Zaproponowano kwantyzację parametru LSP (Linear prediction coefficient) przy użyciu metody compressed sensing CS. Oryginalna wartośc LSP może być zrekonstruowana przy zastosowaniu metody ortogonalnego dopasowania. Uzyskano dobrą jakość ramki 5 bitów/ramka ze znacząca redukcją bitów w porównaniu z innymi metodami.

4

Analysis and evaluation for the Scalability Mechanisms of H.264/SVC

Zhang X., Zhu T., Shu X., Xiao Q.

Przegląd Elektrotechniczny

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2011

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R. 87, nr 7

235-239

EN

Compared with the scalable parts of previous video coding specifications, the Scalable Video Coding (SVC) extension of H.264 Advanced Video Coding (AVC) standard (short for H.264/SVC) has demonstrated significant improvement of video compression performance. In this paper, different coding methods for scalability are analyzed and their influence on the performance of H.264/SVC is investigated through extensive experiments. The conclusions derived from experimental results would serve as solid bases for the future improvement of encoder design.

PL

W porównaniu z wcześniejszymi metodami kodowania sygnału video rozszerzenie SVC (Scalable Video Coding) znane jako standard H.264/SVC wykazuje znaczą poprawę jakości kompresji. W artykule analizowano i porównano różne eksperymentalnie metody kodowania.