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

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.

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

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

Combinatorial optimization of Dedicated Bus Lane layout in urban networks with dynamic congestion

Nikolaos Geroliminis, Anastasios Kouvelas, Dimitrios Tsitsokas

Transit priority based in exclusive right-of-way is a low-cost way of improving transit service by minimizing delays caused by interaction with other vehicles. This effect can increase the share of public transit against private cars in the mode preferences of commuters and consequently alleviate heavy congestion resulting from the dominance of single-occupancy cars. In this work we propose a modeling and optimization framework for the problem of Dedicated Bus Lanes (DBL) location selection in bi-modal urban networks with time-varying traffic congestion. Traffic flow is replicated by dynamic macroscopic traffic model with queueing characteristics instead of steady state models, to capture potential spill-back effects caused by poor DBL planning. A combinatorial optimization problem is formulated aiming at minimizing total passenger delay. Optimization is performed by Local Search (LS) and Neighborhood Search (NS) algorithms, while a network decomposition technique is proposed for improved computational cost. The results show the proposed algorithms effective in significantly improving an initial DBL plan with reasonable computational cost.