Train Service Plan Design under the Condition of Multimodal Rail Transit Systems Integration and Interconnection

Abstract

Multimodal rail transit systems integration and interconnection can solve frequent transfer problems and better adapt to disequilibrium passenger flow and space. It is an inevitable choice in the development of various rail transit systems. Firstly, this paper proposes a novel train service plan design model in the scenario of multimodal rail transit systems integration and interconnection. Our model takes into account the costs of both passengers and enterprises, and passengers travel time is converted into cost using passengers’ nonworking time value coefficient. The model contains some conventional constraints such as passenger flow, station capacity, and line carrying capacity. It also considers whether the transportation capacity of different lines is matched, that is, the constraint of capacity matching degree. Secondly, an improved harmonic search algorithm (IHSA) is designed to solve the problem, and a numerical experiment is used to prove the performance of the proposed method. Our research result shows that the model and algorithm proposed in this paper is effective, which can help overcome the drawbacks of the existing independent operation mode of different rail transit systems. This study is also applicable to the scenario of other kinds of rail transit systems integration and interconnection.

Line Planning under the Operation Mode of Line Sharing between Metro and Suburban Railway

“…Constraint of Train Service Frequency. According to the relevant specifcations, service frequency of diferent kinds of trains shall not be lower than the minimum departure frequency [36]:…”

“…Otherwise, we jump to Step3. Most parameter values are given based on the practical experience or referring to the data in the existing studies [9,10,36,40,41]. Te parameters of the model are shown in Table 3.…”

Optimization of urban rail transit timetables for metropolitan commuter train cross-track operations

“…Liu [7] explored the train scheduling issue pertinent to peak times with oversaturated passenger demand. Based on passenger flow control, they established a bidirectional cooperative optimization model that jointly considers operational timetables, train schedules, and passenger flow control policies.Wang [8] analyzing different operating modes of offline trains under interconnectivity, proposed methods to mitigate the impact of transport and operational plans on capacity, thus providing invaluable support for drafting train schedules.Lin Li [9] focused on optimizing both operational costs for the company and travel time costs for passengers, researching train operation plans under the conditions of integrated and interconnected multi-modal rail transit systems.…”