Archives of Transport

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 3-20km, 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.

Qiang Xiao

Ruichun He

Changxi Ma

The analysis of urban taxi carpooling impact from taxi GPS data

出租车GPS数据的城市拼车影响分析

Analysis of works in the field of artificial intelligence allows to make an assumption that today there is a sufficiently developed theoretical basis for the development of intelligent control systems for locomotive control. This will minimize the risks associated with the human factor on the railways. The paper presents the theoretical rationale for the development of a knowledge base for intelligent locomotive control systems. The approach and structure of the self-learning system of intelligent DSS is proposed, the advantage of which is the presence of a fuzzy classifier that works according to the set criteria and determines a fuzzy image of the current train situation. Learning a fuzzy classifier consists in finding a vector K that minimizes the distance between the results of logical inference and experimental data from the sample. The knowledge base is implemented using linguistic variables formalized by methods of fuzzy logic. The use of linguistic values makes it possible to design the base using the usual language of communication, which greatly simplifies both the design process itself and the analysis of the system's performance. Also, the knowledge base has the possibility of constant self-improvement. This happens in two ways. The first is by adding new rules to the knowledge base in case the current situation does not match the existing ones in the base, in which case an additional rule is created and checked for adequacy. The second way is a mechanism for ranking rules in the knowledge base. If the control action of the locomotive driver coincided with the recommendation of DSS in the current situation, then the rating of this recommendation (rule) increases, and in the future the rule selection algorithm will choose one or another control action for the current situation that has the highest rating (that is, it has already been verified several times person). The experiment has shown that the use of intelligent DSS has positive results. On average, the DSS made the correct train control decisions faster than the locomotive driver.

Oleksandr Gorobchenko

Halyna Holub

Denys Zaika

Theoretical basics of the self-learning system of intelligent locomotive decision support systems

智能机车决策支持系统自学习系统的理论基础

The gathering effect of trucks at freight terminals and the high emission characteristics of trucks themselves lead to long-term truck queues and serious environmental pollution problems at freight terminals. Repeated stopping and following trucks aggravate the environmental pollution in the terminal. This paper proposes a scheme to plan truck parking spaces during waiting for trucks to enter the freight terminal in order to reduce the repeated stopping of trucks and to quantify the environmental benefits of truck parking spaces in the process. The truck admission process was simulated using the Visual Simulator (VISSIM). The simulation output provided vehicle operating data that was converted into operating mode distribution data using the Python calculation module. Then, the model parameters, including the operating mode distribution, were entered into the Motor Vehicle Emission Simulator (MOVES) to calculate the simulation scenario. Gangchen Logistics Park, for example, statistics of the park's 10 months of freight data, the design of freight volume gradually increased by 11 groups of admission simulation experiments, the simulation learned that the park queuing significant, more than 90% probability of queuing, queuing up to a maximum of 203 vehicles, the average queue of 61 vehicles. Then according to the actual road conditions in the park, add a parking lot in the VISSIM simulation. Signal sensing is realized by calling the COM interface of VISSIM through Python to guide the vehicles to park in order and enter the park. Eleven sets of simulation control experiments after designing and planning parking spaces are designed to calculate the pollutant emissions for each simulation scenario separately. The analysis of the emission measurement results shows that the emissions of CO, HC, NOX, and PM10 can be reduced by 1.90%, 7.90%, 9.42%, and 10.55% at the average level of the park's cargo volume. At the park's maximum cargo volume, it is possible to reduce HC, NOX, and PM10 emissions by about one-third. Truck parking space in the truck waiting to drive into the freight terminal process has obvious environmental benefits, queuing significant freight terminals should be reasonably planned truck parking spaces to reduce the freight terminal exhaust emissions pollution.

Yunzhu Yan

Zhongning Fu

Jintian Yue

Study on the environmental benefits of truck parking space for trucks waiting to enter freight terminal - A case study of Gangchen Logistics Park

货车等待进入货运终端的停车空间环境效益研究——以港城物流园为例

The wheel-rail wear was predicted for modern trams with independently rotating wheelset running on a groove-shaped rail. The tram vehicle-track coupled dynamics model, considering the wheel-rail multi-point contact, was developed using software UM to evaluate the dynamic responses of the vehicle and track. Hertz contact theory, the FastSim algorithm, and Archard material wear model were used to solve the normal contact stress, tangential contact stress, and wheel-ail wear, respectively. The wheel and rail profiles were updated when the wear depth reached to 0.1 mm. In calculation, the wheel and rail wear was calculated and analyzed separately. The results of groove rail and independently rotating wheelset wear predicted by this model coincided with relevant literature, which proved the effectiveness of this model. The wheel and rail wear characteristics of modern trams passing through curved tracks with small radii and the influence of wheel-rail friction coefficient on wheel and rail wear were calculated and analyzed using this model. The results show that the wheel and rail wear on the circular curve and the rear transition curve is more intense. The wheel wear is the most intense on circular curve while the rail wear is on the rear transition curve. The wear of inner and outer rails and wheels of wheelset one increases with the increase of wheel-rail friction coefficient while the wear of inner and outer wheels of wheelset three have no obvious change. The wear of the inner and outer rails is the most intense at the gauge corner position while is the lightest at the guard rail. The wear of wheelset one is more intense than that of wheelset three and the inner wheel wear is more intense than that of the outer wheel. The present analysis contributes to improve the life of tram wheel and rail and reduce the frequency of wheel-rail maintenance during operation.

Zhongjie Zhang

Xinwen Yang

Yanyan Zhang

Caixia Miao

Yipeng Cui

Jiqiang Shen

Wheel-rail wear characteristics of a modern tram passing curves with small radius

现代有轨电车通过小半径曲线时的轮轨磨耗特性

Macroscopic Fundamental Diagram (MFD) is widely used in traffic state evaluation due to its description of the macro level of urban road network. This study focuses on the discrimination and short-term prediction of macro traffic states in urban road networks, using MFD combined with FCM clustering for state partitioning to characterize different macro states of the road network. To predict the MFD state, this paper builds two LSTMs to perform short-term predictions on two important parameters in MFD: road network weighted flow qw and road network weighted density kw. The parameters of the first three statistical intervals and the predicted time period are used as inputs to output the MFD parameters for the predicted time period. To ensure that the two LSTM structures and hyper-parameters settings can achieve the best prediction performance for MFD, the parameter optimization process of both should be included in the same search framework for hyper-parameters search. Therefore, this paper uses GA algorithm combined with multi-objective particle swarm optimization algorithm as the solving algorithm, with the accuracy of solving two MFD parameters and the accuracy of MFD point positioning as the hyper-parameters solving objectives. The study was validated using actual road network data from Hong Kong, and the results showed that the method proposed in this paper has an MRE prediction error of less than 7.8% for the two parameters of MFD, and can predict the future temporal trend of the two parameters, demonstrating the feasibility of MFD related predictions. The model's prediction of the overall shape and change trajectory trend of MFD is consistent with reality, and some test sets in MFD state prediction show high accuracy, the overall accuracy is 81.45%. To verify the effectiveness of the multi-objective search algorithm, typical LSTM models and RNN models were used for comparison. The experiment proved that the model used in this study performed better in error control and state prediction. This study explores and practices a short-term prediction method for road network MFD parameters, MFD status, and their changing trends. Provided path reference for urban road network prediction, traffic control status, and MFD related research.

None Xuanhua Lin

None Chaojian TAN

None Xiaohui LIN

Short term road network Macroscopic Fundamental Diagram parameters and traffic state prediction based on LSTM

基于LSTM的短期路网宏观基本图参数与交通状态预测

Global Navigation Satellite Systems (GNSS) are increasingly being used in various modes of transport, including rail transport. When this technology is applied to railway traffic control, it is essential to ensure a high level of safety and reliability. The approval of a railway traffic control system requires a safety analysis, which includes hazard analysis and risk analysis. This also includes GNSS-based solutions in terms of their compliance with safety integrity requirements, i.e. THR (Tolerable Hazard Rate) and SIL (Safety Integrity Level) parameters, as defined in normative documents. In the case of railway traffic control systems, the level of dependability of the determined train position, referred to as position integrity, is very important in ensuring safety. Position integrity is affected by many factors, including: errors due to SIS (Signal-In-Space) propagation, multipath errors, signal interference or GNSS receiver errors. In order to improve position integrity, among other things, new data processing methods can be used to improve the accuracy and reliability of measurements. The paper presents the concept of satellite signal processing for precise determination of the position of objects in selected railway systems. The Kalman filter based model of satellite signal filtration and its selected applications, which were tested in the real condition, was presented. The application of Kalman filtration indicated in the paper is a universal method that improves the estimated measurement parameters and can be used in many applications of satellite systems for railway tasks. The applicability of satellite systems to automatic train operation, defect positioning in automatic and manual flaw detection tests, determining track spatial orientation and train integrity control have been considered. The conducted tests confirmed the correctness of the adopted concept and the model of satellite signals filtration developed for this purpose. According to the authors, the described methods can also be used in many other tasks related to rail transport.

ISSN	0866-9546, 2300-8830
h-index	18

Publication Information	Publisher: Warsaw University of Technology，Publishing cycle: ，Journal Type: journal，Open Access Journals: Yes
Basic data	Year of publication: 2010，Proportion of original research papers: 0.00%，Self Citation Rate:N.A.， Gold OA Rate: 0.00%
Journal Fees	$Details
Average review cycle	网友分享经验：24 Weeks

Archives of Transport

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Share Submission Experience

The analysis of urban taxi carpooling impact from taxi GPS data

Theoretical basics of the self-learning system of intelligent locomotive decision support systems

Study on the environmental benefits of truck parking space for trucks waiting to enter freight terminal - A case study of Gangchen Logistics Park

Wheel-rail wear characteristics of a modern tram passing curves with small radius

Short term road network Macroscopic Fundamental Diagram parameters and traffic state prediction based on LSTM

Theoretical basics of the self-learning system of intelligent locomotive decision support systems

Study on the environmental benefits of truck parking space for trucks waiting to enter freight terminal - A case study of Gangchen Logistics Park

Wheel-rail wear characteristics of a modern tram passing curves with small radius

Short term road network Macroscopic Fundamental Diagram parameters and traffic state prediction based on LSTM

Selected applications of satellite technologies in rail transport