Rail Transit Travel Time Reliability and Estimation of Passenger Route Choice Behavior

Author(s):  
Yanshuo Sun ◽  
Ruihua Xu

Applications of automatic fare collection data were investigated, with a focus on analysis of travel time reliability and estimation of passenger route choice behavior. Beijing Metro was used as a case study. A rail journey was decomposed, and each component was studied with regard to the uncertainties involved. Methods were then designed and validated to infer platform elapsed time (PET) for through stations and platform elapsed time–transfer (PET-Trans) for transfer stations by using smart card transactional data, train schedules, and complementary manual surveys. With this information, the journey time distribution of any path can be established, and methods were proposed for inferring route choice proportions. After data preparation, the methods were applied to two typical origins and destinations from the Beijing Metro. Key values concerning travel time reliability, such as PET, PET-Trans, travelers left behind (unable to board), and path coefficients, were obtained and interpreted in detail. The outcome of this research could facilitate analysis of transit service reliability and passenger flow assignment in daily operations.

2019 ◽  
Vol 16 ◽  
pp. 13-22 ◽  
Author(s):  
Zohreh Rashidi Moghaddam ◽  
Mansoureh Jeihani ◽  
Srinivas Peeta ◽  
Snehanshu Banerjee

2011 ◽  
Vol 130-134 ◽  
pp. 3716-3720
Author(s):  
Yi Ran Cheng ◽  
Yin Han ◽  
Xin Kai Jiang ◽  
Jia Lei Gu

Considering the un-deterministic transportation networks, the paper proposes the change of the route choice decisions under the stochastic transportation networks. The route choice behavior is described as a choice for a time shortest route which is subject to a time-reliability level. The paper also considered this new route choice behavior in the stochastic user equilibrium model, and proposed stochastic user equilibrium model based on the optimized reliability travel time route choice behavior in the stochastic networks. The equivalence and uniqueness of the solution of the model are demonstrated. Numerical results of a small network show that the proposed model can reflect the real traveler’s route choice behavior in stochastic transportation networks.


2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Lei Zhao ◽  
Hongzhi Guan ◽  
Junze Zhu ◽  
Yunfeng Wei

In this paper, route free-flow travel time is taken as the lower bound of route travel time to examine its impacts on budget time and reliability for degradable transportation networks. A truncated probability density distribution with respect to route travel time is proposed and the corresponding travel time budget (TTB) model is derived. The budget time and reliability are compared between TTB models with and without truncated travel time distribution. Under truncated travel time distribution, the risk-averse levels of travelers are adaptive, which are affected by the characteristics of the used routes besides the confidence level of travelers. Then, a TTB-based stochastic user equilibrium (SUE) is developed to model travelers’ route choice behavior. Moreover, its equivalent variational inequality (VI) problem is formulated and a route-based algorithm is used to solve the proposed model. Numerical results indicate that route travel time boundary produces a great influence on decision cost and route choice behavior of travelers.


2011 ◽  
Vol 97-98 ◽  
pp. 925-930
Author(s):  
Shi Xu Liu ◽  
Hong Zhi Guan

The influence of different traffic information on drivers’ day-to-day route choice behavior based on microscopic simulation is investigated. Firstly, it is assumed that drivers select routes in terms of drivers’ perceived travel time on routes. Consequently, the route choice model is developed. Then, updating the drivers’ perceived travel time on routes is modeled in three kinds of traffic information conditions respectively, which no information, releasing historical information and releasing predictive information. Finally, by setting a simple road network with two parallel paths, the drivers’ day-to-day route choice is simulated. The statistical characteristics of drivers’ behavior are computed. Considering user equilibrium as a yardstick, the effects of three kinds of traffic information are compared. The results show that the impacts of traffic information on drivers are related to the random level of driver’s route choice and reliance on the information. In addition, the road network cannot reach user equilibrium in three kinds of information. This research results can provide a useful reference for the application of traffic information system.


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