A slack arrival strategy to promote flex-route transit services

Reliability Analysis of Bus Timetabling Strategy during the COVID-19 Epidemic: A Case Study of Yixing, China

“…Factors considered in the study Notes Gkiotsalitis et al [31][32][33][34] Rolling horizons bus fleet allocation, holding control, and transit rescheduling strategies e purpose is to increase the coordination among running buses, avoid vehicle bunching, and obtain the accurate evaluation of bus timetable Salicru et al [35]; Steiner and Irnich [36]; Zhang et al [37]; Ma et al [38] Passenger travel demands extracted from multisource traffic datasets Smarter computational methods were provided to reduce operational costs and improve the server level of bus timetable Domschke [39]; Ceder et al [40]; Eranki [41]; Liu et al [42]; Ibarra-Rojas et al [43][44][45] Bus line network, route choices of passengers, waiting time at nodes, and the operational costs ey developed a series of models to represent the route choice behaviours of various passengers and minimize the operational cost of bus timetables Wong et al [46]; Shafahi and Khani [47]; Kang et al [48]; Guo et al [49,50]; Chu et al [12]; Abdolmaleki et al [51] Trains' run times, station dwell times, interchange waiting times of all passengers, transfer redundant time, and the network accessibility A series of nonlinear programming models were provided to achieve the synchronize timetables in the transit network and improve the transfer efficiency of passengers factors, including the headway in a rolling horizon scheme, greenhouse gas emission policy, and bus line capacity, were also considered to integrate the vehicle procurement scheme and timetabling for urban transport [37,94,95]. In our previous work, we proposed a slack arrival strategy in which transit vehicles are allowed to reach checkpoints somewhat later than the scheduled departure time and delayed vehicles must leave the checkpoints immediately after serving the boarding and alighting passengers [96]. In this paper, we extended this strategy of time control points to the environment of the COVID-19 epidemic and proposed a reliability evaluation model to quickly acquire and identify which intervals in the bus network would have large arrival delays or transfer synchronization problems in the operational process.…”

A Methodology for Choosing between Route Deviation and Point Deviation Policies for Flexible Transit Services

“…Qiu et al [21] proposed a dynamic station strategy to accept more passengers when the actual travel demand is higher than demand. Zheng et al [22] proposed a slack arrival strategy to reduce the number of rejected passengers through redistributing the slack time among segments. In practice, the actual demand frequently deviates from the expected demand levels in low-demand service areas and the uncertain travel demand makes it hard to serve all curb-to-curb requests, which definitely degrade the service level of the systems.…”

Vehicle Routing and Scheduling of Flex-Route Transit under a Dynamic Operating Environment

“…We let MQ and MT be a sufficiently large number to ensure that constraints (9) and (10) are irrelevant when there is no connection between the two nodes. Constraint (11) makes sure that the departure time of every non-checkpoint stop is always equal to the arrival time plus the dwelling time. Since there may be some idle time at each checkpoint, constraint (12) guarantees that the departure time of the checkpoint is always later than the arrival time plus the dwelling time.…”

“…In our study, the service time fluctuation is not taken into account because it can be considered as part of the travel time between two stops. is line has been widely regarded as a benchmark and testbed of flex-route transit for comparing and evaluating different system settings, models, and solution methods [2,8,10,11,24,25]. e default parameter values are shown in Table 1.…”

“…In practice, the passengers who need deviation service are required to make reservations at least two hours ahead of time. erefore, most studies focus on fully static systems in which all the requests are known in advance and all the unforeseeable events that may happen during the flex-route transit operation are neglected [7][8][9][10][11]. However, real-life situations could be more complex, and the distributions of some accidents cannot be clearly identified.…”