A Dynamic Cordon Pricing Scheme combining a Macroscopic and an Agent-based traffic Models

Pricing is considered an effective management policy to reduce traffic congestion in transportation networks. In this paper we combine a macroscopic model of traffic congestion in urban networks with an agent-based simulator to study congestion pricing schemes. The macroscopic model, which has been tested with real data in previous studies, represents an accurate and robust approach to model the dynamics of congestion. The agent-based simulator can reproduce the complexity of travel behavior in terms of travelers' choices and heterogeneity. This integrated approach is superior to traditional pricing schemes. On one hand, traffic simulators (including car-following, lane-changing and route choice models) consider travel behavior, i.e. departure time choice, inelastic to the level of congestion. On the other hand, most congestion pricing models utilize supply models insensitive to demand fluctuations and non-stationary conditions. This is not consistent with the physics of traffic and the dynamics of congestion. Furthermore, works that integrate the above features in pricing models are assuming deterministic and homogeneous population characteristics. In this paper, we first demonstrate by case studies in Zurich urban road network, that the output of a agent-based simulator is consistent with the physics of traffic flow dynamics, as defined by a Macroscopic Fundamental Diagram (MFD). We then develop and apply a dynamic cordon-based congestion pricing scheme, in which tolls are controlled by an MFD. And we investigate the effectiveness of the proposed pricing scheme. Results show that by applying such a congestion pricing, (i) the savings of travel time at both aggregated and disaggregated level outweigh the costs of tolling, (ii) the congestion inside the cordon area is eased while no extra congestion is generated in the neighbor area outside the cordon, (iii) tolling has stronger impact on leisure-related activities than on work-related activities, as fewer agents who perform work-related activities changed their time plans. Future work can apply the same methodology to other network-based pricing schemes, such as area-based or distance-traveled-based pricing. Equity issues can be investigated more carefully, if provided with data such as income of agents. Value-of-time-dependent pricing schemes then can also be determined. (C) 2012 Elsevier Ltd. All rights reserved.

Time-dependent area-based pricing for multimodal systems with heterogeneous users in an agent-based environment

Nikolaos Geroliminis, Guillaume Rérat, Nan Zheng

In this paper, we investigate an area-based pricing scheme for congested multimodal urban networks with the consideration of user heterogeneity. We propose a time-dependent pricing scheme where the tolls are iteratively adjusted through a Proportional-Integral type feedback controller, based on the level of vehicular traffic congestion and traveler's behavioral adaptation to the cost of pricing. The level of congestion is described at the network level by a Macroscopic Fundamental Diagram, which has been recently applied to develop network-level traffic management strategies. Within this dynamic congestion pricing scheme, we differentiate two groups of users with respect to their value-of-time (which related to income levels). We then integrate incentives, such as improving public transport services or return part of the toll to some users, to motivate mode shift and increase the efficiency of pricing and to attain equitable savings for all users. A case study of a medium size network is carried out using an agent-based simulator. The developed pricing scheme demonstrates high efficiency in congestion reduction. Comparing to pricing schemes that utilize similar control mechanisms in literature which do not treat the adaptivity of users, the proposed pricing scheme shows higher flexibility in toll adjustment and a smooth behavioral stabilization in long-term operation. Significant differences in behavioral responses are found between the two user groups, highlighting the importance of equity treatment in the design of congestion pricing schemes. By integrating incentive programs for public transport using the collected toll revenue, more efficient pricing strategies can be developed where savings in travel time outweigh the cost of pricing, achieving substantial welfare gain. (C) 2015 Elsevier Ltd. All rights reserved.

Elsevier2016

A complex networks approach to traffic flow theory: measures and models

Leonardo Bellocchi

In this thesis, we developed a research direction that combines the theoretical concepts of complex networks with practical needs and applications in the field of transportation engineering. As a first objective we analyzed the phenomenon of congestion propagation in a city trying to synthesize - hence reproduce - dynamical systems of complex nature in a well-established and elegant mathematical-physical structure. With this perspective, we identified in the reaction-diffusion-like system the most natural way to describe how congestion spreads in the road networks according to elementary diffusion mechanics (linear) and self-enhancement of traffic jam (non-linear). This analysis showed that models with a small number of parameters can reproduce dynamic network patterns without the need for very detailed and accurate input data. Another topic we dealt with was to indicate centrality measures expressively defined for congested road networks. Inspired by classical complex networks theory, we defined more suitable and exploitable indices in the field of transport and urban mobility that consider in a dynamic framework both the network topology and the spatial distribution and magnitude of congestion. For this scope, we proposed the definition of dynamical efficiency for single and multi-layer networks. Dynamical efficiency responds adequately to the need for classification of urban areas based on their accessibility and on the influence that traffic has, region-par-region, on the average travel time of passengers. This measure combines and exploits local information (average road speeds, functional type) with the complex structure of the road network and the opportunity for convenient alternative routes. Furthermore, by generalizing the dynamical efficiency definition in a multimodal environment, we are able to identify the most attractive intermodal exchange stations (for example, bus-metro, private car-public transport) and estimate their optimal capacity service. This opens up the workspace for innumerable engineering applications and accurate evaluations of the impact of high traffic demand in each transport system. Among the same lines, another chapter of this thesis concerns a measure of simplicity for paths and allows us to study an extended database of real trajectories and classify the drivers according to their priority path choice factors. Finally, we studied the congestion propagation under a topological perspective as an aggregation of connected components of congested links. By analyzing the distribution of their sizes and the average merging rate we are be able to (i) point out important premonitory signals that anticipate imminent traffic jam (namely morning and evening peak-hours), (ii) to visualize the most critical bottlenecks and (iii) to better understand the causal inference between components of congestion and the average network speed.

EPFL2020

Modeling and optimization of multimodal urban networks with limited parking and dynamic pricing

Nikolaos Geroliminis, Nan Zheng

Cruising-for-parking constraints mobility in urban networks. Car-users may have to cruise for on-street parking before reaching their destinations. The accessibility and the cost of parking significantly influence people's travel behavior (such as mode choice, or parking facility choice between on-street and garage). The cruising flow causes delays eventually to everyone, even users with destinations outside limited parking areas. It is therefore important to understand the impact of parking limitation on mobility, and to identify efficient parking policies for travel cost reduction. Most existing studies on parking fall short in reproducing the dynamic spatiotemporal features of traffic congestion in general, lack the treatment of dynamics of the cruising-for-parking phenomenon, or require detailed input data that are typically costly and difficult to collect. In this paper, we propose an aggregated and dynamic approach for modeling multimodal traffic with the treatment on parking, and utilize the approach to design dynamic parking pricing strategies. The proposed approach is based on the Macroscopic Fundamental Diagram (MFD), which can capture congestion dynamics at network-level for single-mode and bi-modal (car and bus) systems. A parsimonious parking model is integrated into the MFD-based multimodal modeling framework, where the dynamics of vehicular and passenger flows are considered with a change in the aggregated behavior (e.g. mode choice and parking facility choice) caused by cruising and congestion. Pricing strategies are developed with the objective of reducing congestion, as well as lowering the total travel cost of all users. A case study is carried out for a bi-modal city network with a congested downtown region. An elegant feedback dynamic parking pricing strategy can effectively reduce travel delay of cruising and the generic congestion. Remarkably, such strategy, which is applicable in real-time management with limited available data, is fairly as efficient as a dynamic pricing scheme obtained from system optimum conditions and a global optimization with full information about the future states of the system. Stackelberg equilibrium is also investigated in a competitive behavior between different parking facility operators. Policy indications on on-street storage capacity management and pricing are provided.

Elsevier2016

Modeling and optimization of multimodal urban networks with limited parking and dynamic pricing

Nikolaos Geroliminis, Nan Zheng

Elsevier2016

Time-dependent area-based pricing for multimodal systems with heterogeneous users in an agent-based environment

Nikolaos Geroliminis, Guillaume Rérat, Nan Zheng

Elsevier2016

A complex networks approach to traffic flow theory: measures and models

Leonardo Bellocchi

EPFL2020