A Lagrangian discretization multiagent approach for large-scale multimodal dynamic assignment

This paper develops a Lagrangian discretization multiagent model for large-scale multimodal simulation and assignment. For road traffic flow modeling, we describe the dynamics of vehicle packets based on a macroscopic model on the basis of a Lagrangian discretization. The metro/tram/train systems are modeled on constant speed on scheduled timetable/frequency over lines of operations. Congestion is modeled as waiting time at stations plus induced discomfort when the capacity of vehicle is achieved. For the bus system, it is modeled similar to cars with different speed settings, either competing for road capacity resources with other vehicles or moving on separated bus lines on the road network. For solving the large-scale multimodal dynamic traffic assignment problem, an effective-path-based cross entropy is proposed to approximate the dynamic user equilibrium. Some numerical simulations have been conducted to demonstrate its ability to describe traffic dynamics on road network.multimodal transportation systems; Lagrangian discretization; traffic assignment; multiagent systems

a cross-entropy based multiagent approach for multiclass activity chain modeling and simulation

This paper attempts to model complex destination-chain, departure time and route choices based on activity plan implementation and proposes an arc-based cross entropy method for solving approximately the dynamic user equilibrium in multiagent-based multiclass network context. A multiagent-based dynamic activity chain model is developed, combining travelers' day-to-day learning process in the presence of both traffic flow and activity supply dynamics. The learning process towards user equilibrium in multiagent systems is based on the framework of Bellman's principle of optimality, and iteratively solved by the cross entropy method. A numerical example is implemented to illustrate the performance of the proposed method on a multiclass queuing network.dynamic traffic assignment, cross entropy method, activity chain, multiagent, Bellman equation

A Comparative Study of the Cross Entropy Approach with the State–of-the-art Simulation-based Traffic Assignment Algorithms

AbstractThis paper presents a path-based cross entropy algorithm for solving simulation-based dynamic traffic assignment problem. The performance of the cross entropy algorithm is compared with two state-of-the-art algorithms: method of successive averages and gap function based projection algorithm. The dynamic network loading model is based on a mesoscopic queue model complying with generic first order macroscopic node model. The computational study implemented on four realistic networks shows the cross entropy method provides satisfactory convergence accuracy to user equilibrium

Dynamic charging management for electric vehicle demand responsive transport

With the climate change challenges, transport network companies started to electrify their fleet to reduce CO2 emissions. However, such an ecological transition brings new research challenges for dynamic electric fleet charging management under uncertainty. In this study, we address the dynamic charging scheduling management of shared ride-hailing services with public charging stations. A two-stage charging scheduling optimization approach under a rolling horizon framework is proposed to minimize the overall charging operational costs of the fleet, including vehicles' access times, charging times, and waiting times, by anticipating future public charging station availability. The charging station occupancy prediction is based on a hybrid LSTM (Long short-term memory) network approach and integrated into the proposed online vehicle-charger assignment. The proposed methodology is applied to a realistic simulation study in the city of Dundee, UK. The numerical studies show that the proposed approach can reduce the total charging waiting times of the fleet by 48.3% and the total charged the amount of energy of the fleet by 35.3% compared to a need-based charging reference policy

A shared frailty semi-parametric markov renewal model for travel and activity time-use pattern analysis

This study investigates the influence of observed explanatory factors and unobserved random effect (heterogeneity) on episode durations of travel-activity chain. A shared frailty semiparametric proportional hazard model is proposed to estimate the transition hazard of travel/activity states. The proposed model is applied on the travel and activity episode duration analysis during evening work-to-home commute using the household travel survey data collected in the city of Lyon in France in 2005-2006. The empirical results provide useful insights for the determinants of travel and activity episode durations for evening work-to-home commute.time-use; activity duration; Markov renewal model; shared frailty; heterogeneity

Variability versus stability in daily travel and activity behaviour. The case of a one week travel diary

Temporal rhythms in travel and activity patterns are analysed thanks to a seven-day travel diary collected on 707 individuals in the city of Ghent (Belgium) in 2008. Our analysis confirms the large level of intrapersonal variability whether for daily trips, home-based tours, time use and activity sequence. However our analysis goes further by studying this variability along various time periods within the week. Moreover, we show that the systematic day-to-day variability has an extremely low share in intrapersonal variability. The influence of socio-demographic characteristics on intrapersonal variability is weak, whether for daily trips, tours, time use and activity sequence. Repetitive activity-travel behaviour is then detected, through attributes of activity at trip destination, travel mode, trip arrival time and destination location. The picture is at the same time one of diversity and of specificity in activity-travel across the week. People tend to concentrate their weekly activity-travel patterns on few combinations of attributes, despite a large dispersion. Our results on core stops are somewhat encouraging by showing some kind of concentration of activity patterns on a few "anchor" points.travel behaviour ; daily travel ; activity behaviour

A stochastic user-operator assignment game for microtransit service evaluation: A case study of Kussbus in Luxembourg

This paper proposes a stochastic variant of the stable matching model from Rasulkhani and Chow [1] which allows microtransit operators to evaluate their operation policy and resource allocations. The proposed model takes into account the stochastic nature of users' travel utility perception, resulting in a probabilistic stable operation cost allocation outcome to design ticket price and ridership forecasting. We applied the model for the operation policy evaluation of a microtransit service in Luxembourg and its border area. The methodology for the model parameters estimation and calibration is developed. The results provide useful insights for the operator and the government to improve the ridership of the service.Comment: arXiv admin note: substantial text overlap with arXiv:1912.0198

multi-state non-homogeneous semi-markov model of daily activity type, timing and duration sequence

Understanding travelers' daily travel-activity pattern formation is an important issue for activity-based travel demand analysis. The activity pattern formation concerns not only complex interrelations between household members and individual's socio-demographic characteristics but also urban form and transport system settings. To investigate the effects of these attributes and the interrelationship between conducted activities, a multistate semi-Markov model is applied. The underlying assumption of the proposed model states that the state transition probability depends on its adjoining states. Based on the statistical tests of significance, it is affirmed that the duration of activity depends not only on its beginning time-of-day but also on the duration of travel/activity previously conducted. The empirical study based on Belgian Mobility survey is conducted to estimate individual's daily activity durations of different episodes and provides useful insight for the effects of socio-demographic characteristics, urban and transportation system settings on the activity pattern formation.travel-activity pattern, semi-Markov process, Cox regression model