Passengers, Information, and Disruptions

Passengers traveling in public transport generate a detailed digital track record of their journey through using automated fare collection systems and carrying mobile devices. This information on passenger behavior has only recently become available to public transport operators. This thesis addresses the question how this new information can be used to improve passenger service in case of disruptions in public transportation. Major disruptions cause the current logistical schedule of the operator to be infeasible. Adjusting this schedule to the disruption is a complicated planning problem. Passengers will adjust their journeys to the new schedule, and may need to adjust their route choice due to the route choice of other passengers in case of capacity shortages. Therefore the passenger service results from a complex interaction between passengers themselves, and between passengers and the schedule. This thesis proposes new models for improving passenger service in case of major disruptions by adjusting the schedule while anticipating passenger’s reactions, and also by supporting passengers during disruptions through the provision of route advice. This research is combined with a study on passenger behavior based on the new data sources. The models are evaluated using data and case studies of the passenger rail network of Netherlands Railways and the urban rail network of the Massachusetts Bay Transportation Authority. It was found that indeed this new information, together with the option to provide route advice to passengers, could significantly improve service during major disruptions

The Edge Investment Problem: Upgrading Transit Line Segments with Multiple Investing Parties

Bus Rapid Transit (BRT) systems can provide a fast and reliable service to passengers at lower costs compared to tram, metro and train systems. Therefore, they can be of great value to attract more passengers to use public transport, which is vital in reaching the Paris Agreement Targets. However, the main advantage of BRT systems, namely their flexible implementation, also leads to the risk that the system is only implemented partially to save costs. This paper focuses therefore on the Edge Investment Problem: Which edges (segments) of a bus line should be upgraded to full-level BRT? Motivated by the construction of a new BRT line around Copenhagen, we consider a setting in which multiple parties are responsible for different segments of the line. Each party has a limited budget and can adjust its investments according to the benefits provided to its passengers. We suggest two ways to determine the number of newly attracted passengers, prove that the corresponding problems are NP-hard and identify special cases that can be solved in polynomial time. In addition, problem relaxations are presented that yield dual bounds. Moreover, we perform an extensive numerical comparison in which we evaluate the extent to which these two ways of modeling demand impact the computational performance and the choice of edges to be upgraded

The Bus Rapid Transit Investment Problem

Bus Rapid Transit (BRT) systems can provide a fast and reliable service to passengers at low investment costs compared to tram, metro and train systems. Therefore, they can be of great value to attract more passengers to use public transport. This paper thus focuses on the BRT investment problem: Which segments of a single bus line should be upgraded such that the number of newly attracted passengers is maximized? Motivated by the construction of a new BRT line around Copenhagen, we consider a setting in which multiple parties are responsible for different segments of the line. As each party has a limited willingness to invest, we solve a bi-objective problem to quantify the trade-off between the number of attracted passengers and the investment budget. We model different problem variants: First, we consider two potential passenger responses to upgrades on the line. Second, to prevent scattered upgrades along the line, we consider different restrictions on the number of upgraded connected components on the line. We propose an epsilon-constraint-based algorithm to enumerate the complete set of non-dominated points and investigate the complexity of this problem. Moreover, we perform extensive numerical experiments on artificial instances and a case study based on the BRT line around Copenhagen. Our results show that we can generate the full Pareto front for real-life instances and that the resulting trade-off between investment budget and attracted passengers depends both on the origin-destination demand and on the passenger response to upgrades. Moreover, we illustrate how the generated Pareto plots can assist decision makers in selecting from a set of geographical route alternatives in our case study.Comment: 40 pages; updated links to supplemental materia

Shuttle Planning for Link Closures in Urban Public Transport Networks

Urban public transport systems must periodically close certain links for maintenance, which can have significant effects on the service provided to passengers. In practice, the effects of closures are mitigated by replacing the closed links with a simple shuttle service. However, alternative shuttle services could reduce inconvenience at a lower operating cost. This paper proposes a model to select shuttle lines and frequencies under budget constraints. We propose a new formulation that allows a minimal frequency restriction on any line that is operated and minimizes passenger inconvenience cost, which includes transfers and frequency-dependent waiting time costs. This model is applied to a shuttle design problem based on a real-world case study of the Massachusetts Bay Transportation Authority network of Boston, Massachusetts. The results show that additional shuttle routes can reduce passenger delay compared to the standard industry practice, while also distributing delay more equally over passengers, at the same operating budget. The results are robust under different assumptions about passenger route choice behavior. Computational experiments show that the proposed formulation, coupled with a preprocessing step, can be solved faster than prior formulations

Shuttle Planning for Link Closures in Urban Public Transport Networks

Urban Public Transport systems must periodically close certain links for main- tenance, which can have significant effects on the service provided to passengers. In practice, the effects of closures are mitigated by replacing the link with a simple shuttle service. However, alternative shuttle services could reduce inconvenience at lower op- erating cost. This paper proposes a model to select shuttle lines and frequencies under budget constraints. A new formulation is proposed that allows a minimal frequency restriction on any line that is operated, and minimizes passenger inconvenience cost, including transfers and frequency-dependent waiting time. This model is applied to a shuttle design problem based on a real world case study of the MBTA network of Boston (USA). The results show that additional shuttle routes can reduce passenger delay in comparison to the standard industry practice, while also distributing delay more equally over passengers, at the same operating budget. The results are robust under different assumptions about passenger route choice behavior. Computational experiments show that the proposed formulation, coupled with a preprocessing step, can be solved faster than prior formulations