Headway Optimisation for Metro Lines Based on Timetable Simulation and Simulated Annealing

Author:

Cui Yong12ORCID,Yu Qing3,Wang Chenyang4

Affiliation:

1. Hefei University, 99 Jinxiu Road, Hefei, Anhui 230601, China

2. Chinese-German Research and Development Centre for Railway and Transportation Technology Stuttgart (CDFEB e.V.), Torstraße 20, 70173 Stuttgart, Germany

3. Technical University of Darmstadt, Karolinenplatz 5, 64289 Darmstadt, Germany

4. Hefei Urban Rail Transit Co. Ltd., 17 Fuyang Road, Hefei, Anhui 230001, China

Abstract

To improve the capacity of metro systems, it is important to evaluate and minimise headway, which is defined as the time interval calculated from “head to head” between two successive trains in this paper. With existing approaches for headway optimisation, the headway for moving block systems is often calculated based on the safe braking distance. However, the blocking time at movable elements (e.g., switches and crossings) and stops has special characteristics. Since train separation is dominated by a signalling system, the distance between two successive trains at movable elements and stops exceeds the safe braking distance. In this work, the theory for building a blocking time model and calculating line headway for moving block systems is investigated. A workflow to minimise line headway is designed to derive an optimised velocity profile before the identified bottlenecks. Several different optimisation algorithms, including grid search, Monte Carlo, and simulated annealing, are developed and compared. Among them, simulated annealing shows the best optimisation capability with the least computational effort. The designed algorithm has been tested for Hefei-Metro Line 1, and the line headway can be reduced from 116.776 seconds to 105.806 seconds. If the acceptable rate of the increased transport is set at 1%, the line capacity will increase by 6.5%.

Funder

Anhui Provincial Key Research and Development Plan

Publisher

Hindawi Limited

Subject

Strategy and Management,Computer Science Applications,Mechanical Engineering,Economics and Econometrics,Automotive Engineering

Reference24 articles.

1. ERTMS Level 3: the game-changer;N. Furness;IRSE News,2017

2. Analysis of minimum train headway on a moving block system by genetic algorithm;H. Nakamura;WIT Transactions on The Built Environment,1998

3. Automatic train supervision for a CBTC suburban railway line using multiobjective optimization

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