Valentina Trozzi

A dynamic route choice model for public transport networks with boarding queues

Abstract The concepts of optimal strategy and hyperpath were born within the framework of static frequency-based public transport assignment, where it is assumed that travel times and frequencies do not change over time and no overcrowding occurs. However, the formation of queues at public transport stops can prevent passengers from boarding the first vehicle approaching and can thus lead to additional delays in their trip. Assuming that passengers know from previous experience that for certain stops/lines they will have to wait for the arrival of the 2nd, 3rd, …, k-th vehicle, they may alter their route choices, thus resulting in a different assignment of flows across the network. The aim of this paper is to investigate route choice behaviour changes as a result of the formation and dispersion of queues at stops within the framework of optimal travel strategies. A new model is developed, based on modifications of existing algorithms.

Dynamic User Equilibrium in Public Transport Networks with Passenger Congestion and Hyperpaths

This paper presents a Dynamic User Equilibrium for bus networks where recurrent overcrowding results in queues at stops. The route choice model embedded in the dynamic assignment explicitly considers common lines and strategies with alternative routes. As such, the shortest hyperpath problem is extended to a dynamic scenario with capacity constraints where the diversion probabilities depend on the time the stop is reached and on the expected congestion level at that time. In order to reproduce congestion for all the lines sharing a stop, the Bottleneck Queue model with time-varying exit capacity, introduced in Meschini et al. (2007), is extended. The above is applied to separate queues for each line in order to satisfy the First-In-First-Out principle within every attractive set, while allowing overtaking among passengers having different attractive sets but queuing single file.

Scheduled Hyperpath: A Strategy for Reliable Routing and Scheduling of Deliveries in Time-Dependent Networks with Random Delays

This paper presents a new method for improving the on-time arrival reliability of deliveries. A dispatcher wishes to minimize the total expected travel time and determines a set of attractive links before the trip. Drivers choose between them en route on the basis of the traffic conditions that they observe on immediate successor links. Such a set of attractive paths with associated departure time and decision rule collectively offers a better expected travel time than any single path on its own and is referred to as a “scheduled hyperpath.” The hyperpath concept was exploited by drawing of a parallel between the wait for randomly arriving public transport services and the wait for available capacity in traffic networks with random delays. Adaptation of those methods to the just-in-time delivery context follows from established assertions that consideration of multiple paths and adaptive path selection in networks with random travel times offers shorter travel times than selection of an a priori path with the least expected travel time. The HyperDOT algorithm presented identifies an optimal scheduled hyperpath sequentially in reverse topological and chronological order by use of the historical distributions of link travel times for discrete time intervals as inputs. Two areas of application are discussed: multiple simultaneous deliveries and repetitive shipments. Although the proposed strategy is advantageous in networks with multiple delays, it may lead to the discarding of routes that remain the shortest even when they are delayed because of the myopic character of information about network conditions.