Urban Rail Transport Coordination Based on Travel Time Cost

ICTE 2015 ◽  
2015 ◽  
Author(s):  
Haochuan Yu ◽  
Zhongyi Zuo ◽  
Yi Cao
2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Qin Luo ◽  
Yufei Hou ◽  
Wei Li ◽  
Xiongfei Zhang

The urban rail transit line operating in the express and local train mode can solve the problem of disequilibrium passenger flow and space and meet the rapid arrival demand of long-distance passengers. In this paper, the Logit model is used to analyze the behavior of passengers choosing trains by considering the sensitivity of travel time and travel distance. Then, based on the composition of passenger travel time, an integer programming model for train stop scheme, aimed at minimizing the total passenger travel time, is proposed. Finally, combined with a certain regional rail line in Shenzhen, the plan is solved by genetic algorithm and evaluated through the time benefit, carrying capacity, and energy consumption efficiency. The simulation result shows that although the capacity is reduced by 6 trains, the optimized travel time per person is 10.34 min, and the energy consumption is saved by about 16%, which proves that the proposed model is efficient and feasible.


Author(s):  
Hanyuan Zhang ◽  
Hao Wu ◽  
Weiwei Sun ◽  
Baihua Zheng

Estimating the travel time of a path is of great importance to smart urban mobility. Existing approaches are either based on estimating the time cost of each road segment which are not able to capture many cross-segment complex factors, or designed heuristically in a non-learning-based way which fail to leverage the natural abundant temporal labels of the data, i.e., the time stamp of each trajectory point. In this paper, we leverage on new development of deep neural networks and propose a novel auxiliary supervision model, namely DeepTravel, that can automatically and effectively extract different features, as well as make full use of the temporal labels of the trajectory data. We have conducted comprehensive experiments on real datasets to demonstrate the out-performance of DeepTravel over existing approaches. 


2017 ◽  
Vol 189 ◽  
pp. 829-835 ◽  
Author(s):  
E.P. Dudkin ◽  
L.A. Andreeva ◽  
N.N. Sultanov

2015 ◽  
Vol 744-746 ◽  
pp. 2049-2052
Author(s):  
Yao Wu ◽  
Jian Lu ◽  
Yue Chen

In order to study the factors influencing urban rail transit travel behavior, a questionnaire was conducted for residents’ selection of rail transit in Xi'an. Based on the collected data from 1105 valid questionnaires, a binary logistic regression model was established to analyze the influencing factors quantitatively. The results showed that seven factors have statistically significant for rail transit travel behavior including age, occupation, family income, average monthly household transportation costs (T-cost), travel purpose, travel distance, and travel time. Odds ratio analysis revealed that young people and staff were more likely to choose rail transit; the probability of selecting rail transit increased with the increase of family income and the T-cost. In addition, more and more people tend to rail travel with the increase of travel distance and travel time.


Author(s):  
Sonia Baee ◽  
Farshad Eshghi ◽  
S. Mehdi Hashemi ◽  
Rayehe Moienfar

Heavy traffic consequences in crowded cities can be extremely reduced by using mass transportation. Recent extensive studies on Tehran subway system, as a representative of crowded cities, show that ever increasing commutation demand results in rapid decline in service quality and satisfaction level, system capacity wastage, and poorer system performance. Since passenger boarding/alighting period is noticeable compared to the inter-station travel time, it seems that passenger boarding/alighting management would play a significant role in system performance improvement. Aiming at increasing satisfaction level and service success rate, while reducing travel time, different boarding/alighting strategies are proposed. Passengers behaviors are carefully simulated based on a microscopic model, through introducing an inclination function which governs a passengers movement in a two-dimensional queue. Simulation results, in terms of three aforementioned measures of performance, show that in less crowded stations, the first strategy, expectedly, outperforms the other two. However, in crowded stations (e.g. interchange stations) the third strategy outperforms the others significantly.


Sign in / Sign up

Export Citation Format

Share Document