scholarly journals Hybrid Random Regret Minimization and Random Utility Maximization in the Context of Schedule-Based Urban Rail Transit Assignment

2018 ◽  
Vol 2018 ◽  
pp. 1-28 ◽  
Author(s):  
Dewei Li ◽  
Yufang Gao ◽  
Ruoyi Li ◽  
Weiteng Zhou
Keyword(s):  
Utility Maximization ◽  
Choice Behavior ◽  
Route Choice ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Transit Assignment ◽  
Regret Minimization ◽  
Transit Network ◽  
Route Choice Behavior ◽  
Urban Rail

Route choice is one of the most critical passenger behaviors in public transit research. The utility maximization theory is generally used to model passengers’ route choice behavior in a public transit network in previous research. However, researchers have found that passenger behavior is far more complicated than a single utility maximization assumption. Some passengers tend to maximize their utility while others would minimize their regrets. In this paper, a schedule-based transit assignment model based on the hybrid of utility maximization and regret minimization is proposed to study the passenger route choice behavior in an urban rail transit network. Firstly, based on the smart card data, the space-time expanded network in an urban rail transit was constructed. Then, it adapts the utility maximization (RUM) and the regret minimization theory (RRM) to analyze and model the passenger route choice behavior independently. The utility values and the regret values are calculated with the utility and the regret functions. A transit assignment model is established based on a hybrid of the random utility maximization and the random regret minimization (RURM) with two kinds of hybrid rules, namely, attribute level hybrid and decision level hybrid. The models are solved by the method of successive algorithm. Finally, the hybrid assignment models are applied to Beijing urban rail transit network for validation. The result shows that RRM and RUM make no significant difference for OD pairs with only two alternative routes. For those with more than two alternative routes, the performance of RRM and RUM is different. RRM is slightly better than RUM in some of the OD pairs, while for the other OD pairs, the results are opposite. Moreover, it shows that the crowd would only influence the regret value of OD pair with more commuters. We conclude that compared with RUM and RRM, the hybrid model RURM is more general.

Study on Route Choice Behavior of Urban Rail Transit Passengers

2014 ◽  
Vol 587-589 ◽  
pp. 2252-2256
Author(s):  
Sha Sha Liu ◽  
En Jian Yao ◽  
Yong Sheng Zhang ◽  
Ling Lu
Keyword(s):  
Choice Behavior ◽  
Route Choice ◽  
Personal Characteristics ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Comfort Index ◽  
Route Choice Behavior ◽  
Urban Rail ◽  
New Variables ◽  
Vehicle Travel Time

In order to capture spatiotemporal distribution pattern of passenger flow under networked condition, it is necessary to analyze route choice behavior of urban rail transit passengers. First, angular cost value and comfort index are defined to reflect the influence of network structures, route directions and in-vehicle congestion on passengers’ route choice behavior respectively; Then, two route choice models are proposed respectively for peak and off-peak hours, in which new variables including angular cost value, comfort index and personal characteristics, as well as level of service variables (i.e. in-vehicle travel time, number of transfers and transfer time etc. , which are usually found in the base model) are considered. Finally, the models are calibrated with the surveyed data from Guangzhou Metro and compared with each other. The results show that the new variables significantly improve models’ explanatory and predictive abilities on route choice behavior of urban rail transit passengers.

Passenger Route Choice Behavior with Congestion Consideration

2013 ◽  
Vol 368-370 ◽  
pp. 1876-1880 ◽  
Author(s):  
Ying Zeng ◽  
Jun Li ◽  
Hui Zhu
Keyword(s):  
Choice Behavior ◽  
Route Choice ◽  
Transit Assignment ◽  
Transit System ◽  
Transit Network ◽  
Route Choice Behavior ◽  
Assignment Model ◽  
Proposed Model ◽  
Vehicle Capacity

Few studies have adequately focused on passenger route choice behavior with congestion consideration, or provided useful guidance on passenger route choice and hence the transit assignment model, which is the writing motivation of this paper. With congestion consideration, travel cost is assessed and and ways to reduce it also identified. Finally, an actual transit network of Chengdu is used as a case study to demonstrate the benefits of the proposed model. The result indicates that the vehicle capacity is an important factor that cant be ignored and a better understanding of passenger route behavior could significantly benefit public transit system.

scholarly journals CPT Model-Based Prediction of the Temporal and Spatial Distributions of Passenger Flow for Urban Rail Transit under Emergency Conditions

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Wei Li ◽  
Min Zhou ◽  
Hairong Dong
Keyword(s):  
Travel Behavior ◽  
Choice Behavior ◽  
Cumulative Prospect Theory ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Spatial Distributions ◽  
Passenger Flow ◽  
Route Choice Behavior ◽  
Urban Rail ◽  
Temporal And Spatial

Emergencies have a significant impact on the passenger flow of urban rail transit. It is of great practical significance to accurately predict the urban rail transit passenger flow and carry out research on its temporal and spatial distributions under emergency conditions. Urban rail transit operating units currently use video surveillance information mainly to process emergencies and rarely use computer vision technology to analyze passenger flow information collected. Accordingly, this paper proposes a passenger flow-based temporal and spatial distribution model for urban rail transit emergencies based on the CPT. First, this paper clarifies the categories and classification of urban rail transit emergencies, analyzes the factors affecting passenger route selection, and establishes a generalized travel cost model for passengers under emergencies. Second, this paper establishes a passenger route choice behavior model for urban rail transit based on the cumulative prospect theory. Finally, taking Beijing as an example, this paper analyzes passenger travel behavior under emergencies based on multiple logistic regression models and analyzes the impact of emergencies on rail transit travel behavior. The research results show that the cumulative prospect theory can better describe the route choice behavior of rail transit passengers under emergencies than the existing models, and this model is of great significance for handling urban rail transit emergencies. The model proposed in this paper can provide a theoretical basis for the government and relevant departments to formulate traffic management measures.

Study of Passengers’ Route Choice of Urban Rail Transit Network under the Emergency

2014 ◽  
Vol 587-589 ◽  
pp. 1940-1943 ◽  
Author(s):  
Qian Li ◽  
Yong Qin ◽  
Zi Yang Wang ◽  
Lin Qing Zhang
Keyword(s):  
Comparative Analysis ◽  
Choice Model ◽  
Route Choice ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Transit Network ◽  
Urban Rail ◽  
Urban Rail Transit Network ◽  
The Impact

In this paper, through the analysis of emergency’s impact on passengers’ route choice, a passengers’ route choice model was found of urban rail transit net and based on the model to analysis the instance. Through comparative analysis the impact of offering guidance by supplying information, the result showed that under the guidance by supplying information, the passengers is divided due to their own preferences on different paths property, comparing to no information to guide, the system has been optimized.

Sign in / Sign up

Export Citation Format

Share Document