Related papers: Fare Evasion in Transit Networks
The Traveling Thief Problem (TTP) is a multi-component optimization problem that captures the interplay between routing and packing decisions by combining the classical Traveling Salesperson Problem (TSP) and the Knapsack Problem (KP). The…
Airport public transport systems are plagued by passenger queue congestion, imposing a substandard travel experience and unexpected delays. To address this issue, this paper proposes a bi-level programming for optimizing queueing network in…
We study the problem of planning Pareto-optimal journeys in public transit networks. Most existing algorithms and speed-up techniques work by computing subjourneys to intermediary stops until the destination is reached. In contrast, the…
We study real-time routing policies in smart transit systems, where the platform has a combination of cars and high-capacity vehicles (e.g., buses or shuttles) and seeks to serve a set of incoming trip requests. The platform can use its…
We consider the price-optimal earliest arrival problem in public transit (POEAP) in which we aim to calculate the Pareto-set of journeys with respect to ticket price and arrival time in a public transportation network. Public transit fare…
Assigning passenger trips to specific network paths using automatic fare collection (AFC) data is a fundamental application in urban transit analysis. The task is a difficult inverse problem: the only available information consists of each…
Public transport administrators rely on efficient algorithms for various problems that arise in public transport networks. In particular, our study focused on designing linear-time algorithms for two fundamental path problems: the earliest…
Reorganizing bus frequency to cater for the actual travel demand can save the cost of the public transport system significantly. Many, if not all, existing studies formulate this as a bus frequency optimization problem which tries to…
Global infrastructure robustness and local transport efficiency are critical requirements for transportation networks. However, since passengers often travel greedily to maximize their own benefit and trigger traffic jams, overall…
Urban metro and tram networks are regularly subject to planned disruptions, including closures, resulting from the need to maintain and renew infrastructure. In this study, we first empirically analyse the passenger demand response to…
Urban rail transit is a fundamental component of public transportation, however, commonly station-based path search algorithms often overlook the impact of transfer times on search results, leading to decreased accuracy. To solve this…
Different passenger demand rates in transit stations underscore the importance of adopting operational strategies to provide a demand-responsive service. Aiming at improving passengers' travel time, the present study introduces an advanced…
The intelligent upgrading of metropolitan rail transit systems has made it feasible to implement demand-side management policies that integrate multiple operational strategies in practical operations. However, the tight interdependence…
In a ride-pooling system, travellers experience discomfort associated with a detour and a longer travel time, which is compensated with a sharing discount. Most studies assume travellers receive either a flat discount or, in rare cases, a…
Designing fare systems for public transportation networks is a challenging task. A popular approach is to partition the network into fare zones (``zoning'') and fix journey prices depending on the number of traversed zones (``pricing''). In…
We propose the first analytical stochastic model for optimizing the configuration and implementation policies of fare-free transit. The model focuses on a transportation corridor with two transportation modes: automobiles and buses. The…
Refined trajectory inference of urban rail transit is of great significance to the operation organization. In this paper, we develop a fully data-driven approach to inferring individual travel trajectories in urban rail transit systems. It…
Spurred by the growth of transportation network companies and increasing data capabilities, vehicle routing and ride-matching algorithms can improve the efficiency of private transportation services. However, existing routing solutions do…
The shift from private vehicles to public and shared transport is crucial to reducing emissions and meeting climate targets. Consequently, there is an urgent need to develop a multimodal transport trip planning approach that integrates…
This study investigates the network characteristics of high-frequency (HF) and low-frequency (LF) travelers in urban public transport systems by analyzing 20 million smart card records from Beijing's transit network. A novel methodology…