Public Norms in the Operation Scheme of Urban Rail Transit Express Trains: The Case of the Beijing Changping Line

Abstract

The development of urban rail transit is of great significance to the sustainable development of cities. However, the formulation of public norms of the urban rail transit train operation scheme lacks the corresponding theoretical support, rationality and scientificity. Therefore, based on the research on passenger flow conditions, this paper establishes an optimization model of express train operation and uses a heuristic genetic algorithm to solve it. In addition, this paper takes the Beijing Changping Line as an example to conduct empirical research. Results show that the optimization model established reduces the operation cost of operating enterprises, improves the capacity of urban rail transit, reduces travel time and maintains the full load rate of trains at a more comfortable level. This will improve the attractiveness of urban rail transit and promote benign interaction between operators and passengers. It will also provide a theoretical basis for formulating public norms of transit train operation, make it more scientific and reasonable and promote the development of urban rail transit.

A Comprehensive Survey and Future Directions on Optimising Sustainable Urban Mobility

“…From the Asian applications, China was the country with more studies (comprising 48 articles [38,40,41,46,), from which Beijing stands out with 17 studies [62, 63, 65, 74, 80, 81, 83-85, 87, 88, 92-94, 96, 98, 102]. Real networks or case study applications may include universities' campi [36,[103][104][105][106][107][108], neighbourhoods and districts [46,80,95,98,102,109], or studies that only consider some transport lines/stations within a city or transport network [71,81,86,93,96,[110][111][112].…”

“…Some authors modelled more than one aspect, for example routes and frequencies setting [194], routes and vehicle scheduling of a customised bus service [89], routes and timetabling [187], frequencies setting and timetable development [193], and service area, frequencies, and vehicle scheduling [164]; Nesheli et al [127] focused on real-time operation aspects of bus systems, as vehicle holding time and boarding limit at stops, and also deciding if the vehicle could skip certain stops. Finally, for rail systems, studies focused on determining train timetables and rolling stock schedule [63], a conflict-free timetable for all trains running on a railway, considering multiplatform stations [172], frequencies setting and operational aspects (stop scheme and operation time) [93], rail scheduling and fleet management [100], and a transit-based evacuation plan for rail transit line emergencies [71].…”

“…At last, for a multimodal network to integrate buses to the rail system, Almasi et al [196] focused on network design (routes), frequencies setting, and operational aspects (dwell time). 168, 170, 171, 173-177, 180, 181, 183-186, 188, 190, 192-199] Considering the perspective of passengers alone, studies sought to minimise uncovered demand [174], distances in the network [156], and passengers' travel time [68,93,127,190], and maximise accessibility [147] and direct transfers without waiting [127]. For the operators perspective alone, studies aimed at minimising costs or maximising revenue [84,98,100,101,152,154,160,182,185,192], minimising travelled distance or vehicle mileage [72-74, 92, 175, 187, 191], minimising workload [73] and rebalancing amount [192], maximising covered demand [73,176], rebalancing utility [191], the total social net benefit [47], and the average passenger flow [173].…”

Optimal Design of Subway Train Cross-Line Operation Scheme Based on Passenger Smart Card Data

“…Existing research on the optimization of subway train operation mostly focuses on a single subway line [6,7], including the optimization of departure frequency and running intervals, optimization of the train stop plan, optimization of train routing plan, etc. For the optimization of the departure frequency and running interval, Niu and Zhou proposed a genetic algorithm to solve the integer programming models to optimize the timetables of metro lines [8].…”