Area-based equitable pricing strategies for multimodal urban networks with heterogeneous users

Equity issues among travellers are critical in congestion pricing. Failure to treat equity can lead to low acceptability towards pricing. In this paper, we develop congestion pricing schemes to improve both equity and traffic performance, for multimodal networks. We consider the equity issue by the existence of heterogeneous population, with respect to income level and value-of-time (VOT). An optimization framework is formulated for obtaining optimal toll schemes. We apply an aggregated network-level traffic flow model to reproduce congestion dynamics and mode choice behavior. The gain and loss for VOT-based user groups are investigated and discussed. We carry out simulation analysis over two pricing schemes: a unified toll and a VOT-based toll. In particular, we allow during the optimization process the VOT-based toll to obtain negative values for some users if it meets some system objectives. Our results confirm that significant differences in behavior and cost savings exist among groups, which justifies the need for a VOT-based pricing. It also demonstrates that properly-designed VOT-based tolls can improve the inequity in savings, e.g. users whose VOT values are lower may receive larger travel cost savings. Furthermore, a policy-oriented discussion on the design and implementation of the proposed equitable pricing schemes is provided.

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

Nikolaos Geroliminis, Nan Zheng

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.

2012

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

The spatial variability of vehicle densities as determinant of urban network capacity

Nikolaos Geroliminis, Seyyed Amin Mazloumian

Due to the complexity of the traffic flow dynamics in urban road networks, most quantitative descriptions of city traffic so far have been based on computer simulations. This contribution pursues a macroscopic (fluid-dynamic) simulation approach, which facilitates a simple simulation of congestion spreading in cities. First, we show that a quantization of the macroscopic turning flows into units of single vehicles is necessary to obtain realistic fluctuations in the traffic variables, and how this can be implemented in a fluid-dynamic model. Then, we propose a new method to simulate destination flows without the requirement of individual route assignments. Combining both methods allows us to study a variety of different simulation scenarios. These reveal fundamental relationships between the average flow, the average density and the variability of the vehicle densities. Considering the inhomogeneity of traffic as an independent variable can eliminate the scattering of congested flow measurements. The variability also turns out to be a key variable of urban traffic performance. Our results can be explained through the number of full links of the road network, and approximated by a simple analytical formula.