Development of a Behavior-Based Passenger Flow Assignment Model for Urban Rail Transit in Section Interruption Circumstance

Abstract

At present, the urban rail transit (URT) system has achieved network operation in many major cities of China. But, little attention has been given to the vulnerability of the URT system. The purpose of this study is to assign the passenger flow under the condition of section interruption in URT system. Two surveys (a passenger behavior survey and a stated preference survey) were conducted and a multinomial logit model was developed. The results show that although the first choice of passengers in emergency situation is to stay in URT system by a circuitous way, more than half of the respondents express interest in the temporary shuttle bus. For the temporary shuttle bus, the sensitivity analysis show that the relative speed is more important than crowding degree for passengers. The significant variables mostly fall in the personal attributes such as income, gender, age, etc. The impacts of trip feature factors are similar to the previous research in normal situations. These results provide basic support for passenger flow assignment at the shuttle bus level and reducing the risk of crowding at some special stations. Moreover, it is also good for reducing passenger delay and recovering the trip.

A Passenger-Oriented Optimization Model for Implementing Energy-Saving Strategies in Railway Contexts

“…This work, instead, is focused on strategies involving the design of suitable speed profiles and the optimization of operational parameters within the timetable by taking into account effects on user perspectives. Indeed, recently, numerous studies have been developed for analyzing user behaviors and related quality perceptions (see, for instance, [23][24][25][26][27][28][29][30][31][32][33][34][35]) in the case of transportation systems, including rail and metro systems.…”

“…The upper level (i.e., Equation (15)) consists in determining the optimal value of α TLT which minimizes the objective function Z(•), having fixed the headway (H), the number of rail convoys (NC) and having determined the corresponding speed limits (v lim ot andv lim rt ) by means of the lower level problem (i.e., Equations (24) and (25)).…”

“…The lower level (i.e., Equations (24) and (25)) consists in determining, for any fixed α TLT value, the maximum values of speed limits (v lim ot andv lim rt ) which maximize the use of layover times (lt TO ot and lt TO rt ). Indeed, constraints (26) and (27) impose driving speed profiles (v ESS ot and v ESS rt ) which respect the speed limits (v lim ot and v lim rt ).…”

Updating origin–destination matrices with aggregated data of GPS traces

“…Traffic and transit assignment map (e.g. Teng and Liu (2015)) can be incorporated in the objective function. But due to the limitation of datasets such as link cost and transit fare, link count and number of transit users, we consider the OD estimation problem as a fitting problem here.…”

Traffic Management Plan Evaluation Outside the Station in Emergent Events of Urban Rail Transit

“…The number of passengers can be calculated by passenger flow OD and arriving and departing time of trains; the calculation of the proportion that passengers choose bridging bus can refer to our previous research [20], this research is based on passenger travel behavior characteristics in emergent events of URT, which used the result of passenger travel behavior survey and Stated Preference survey as basic data and proposed passenger behavior distribution Logit model. We chose cost, SDB, and MRSQ as influencing factors, and calculate the utility value of three modes (URT, bus, and other modes).…”