A three-dimensional macroscopic fundamental diagram for mixed bi-modal urban networks

Recent research has studied the existence and the properties of a macroscopic fundamental diagram (MFD) for large urban networks. The MFD should not be universally expected as high scatter or hysteresis might appear for some type of networks, like heterogeneous networks or freeways. In this paper, we investigate if aggregated relationships can describe the performance of urban bi-modal networks with buses and cars sharing the same road infrastructure and identify how this performance is influenced by the interactions between modes and the effect of bus stops. Based on simulation data, we develop a three-dimensional vehicle MFD (3D-nu MFD) relating the accumulation of cars and buses, and the total circulating vehicle flow in the network. This relation experiences low scatter and can be approximated by an exponential-family function. We also propose a parsimonious model to estimate a three-dimensional passenger MFD (3D-pMFD), which provides a different perspective of the flow characteristics in hi-modal networks, by considering that buses carry more passengers. We also show that a constant Bus-Car Unit (BCU) equivalent value cannot describe the influence of buses in the system as congestion develops. We then integrate a partitioning algorithm to cluster the network into a small number of regions with similar mode composition and level of congestion. Our results show that partitioning unveils important traffic properties of flow heterogeneity in the studied network. Interactions between buses and cars are different in the partitioned regions due to higher density of buses. Building on these results, various traffic management strategies in hi-modal multi-region urban networks can then be integrated, such as redistribution of urban space among different modes, perimeter signal control with preferential treatment of buses and bus priority. (C) 2014 Elsevier Ltd. All rights reserved.

Economic Model Predictive Control of Large-Scale Urban Road Networks via Perimeter Control and Regional Route Guidance

Nikolaos Geroliminis, Isik Ilber Sirmatel

Local traffic control schemes fall short of achieving coordination with other parts of the urban road network, whereas a centralized controller based on the detailed traffic models would suffer from excessive computational burden. State estimation for detailed traffic models with limited observations and unpredictability of individual driver behavior create additional complications in the applicability of these models for large-scale traffic control. This point toward the need for designing network-level controllers building on aggregated traffic models, which have recently attracted attention through the macroscopic fundamental diagram (MFD) of urban traffic. Under some conditions, the MFD provides a unimodal, low-scatter, and demand-insensitive relationship between vehicle accumulation and travel production inside an urban region. In this paper, we propose MFD-based economic model predictive control (MPC) schemes to improve mobility in heterogeneously congested large-scale urban road networks. For more realistic simulations of urban networks with route guidance actuation-based control, a new model with cyclic behavior prohibition is developed. This paper extends upon earlier works on perimeter control-based MPC schemes with MFD modeling by integrating route guidance type actuation, which distributes flows exiting a region over its neighboring regions. Performance of the proposed schemes is evaluated via simulations of congested scenarios with noise in demand estimation and measurement errors. Results show the possibility of substantial improvements in urban network performance, in terms of network delays and traveled distance, even for low levels of driver compliance to route guidance.

2018

An optimization framework for exclusive bus lane allocation in large networks with dynamic congestion

Nikolaos Geroliminis, Anastasios Kouvelas, Dimitrios Tsitsokas

Road space distribution among multiple modes of transport in urban networks has attracted the interest of several researchers and policy planners. Traditionally, these problems are solved by ignoring operational and dynamic characteristics of multi-modal congestion due to the computational burden involved. Revealing the relation between road space share and global performance of the network can lead to more efficient transport system design. The introduction of dedicated bus lanes in some parts of the network has been proposed as a measure to allow high occupancy vehicles to travel through regions with high traffic load without long delays. In this way, the bus transit system operates more efficiently and is competitive to the private car option in terms of travel time. This effect can stimulate a significant mode shift from car to bus and help alleviate congestion by reducing the number of low occupancy vehicles. In this work we address the problem of optimal allocation of exclusive bus lanes in a multi-modal urban network of fixed total road infrastructure and passenger demand, with the aim of minimizing the total passenger hours travelled (PHT) for all travel modes, within a framework which is consistent with the dynamics of congestion. A queueing theory based traffic flow model with proper treatment of spillbacks and traffic signal settings, known as the Store-and-Forward (SaF) model, is extended to simulate the dynamics of congestion inside the network by keeping track of the queues inside all links over time. The SaF simulation model can be used to evaluate the performance of different allocation policies.

2019

A Dynamic Network Approach for Multimodal Urban Mobility

Nan Zheng

Recent advances in traffic flow theory at the network level, namely the Macroscopic Fundamental Diagram (MFD), reveals the existence of well-defined laws of congestion dynamics at aggregated levels. The same knowledge for multimodal networks however is limited. It is critical to understand how urban space can be allocated and managed for multimodality. The objective is to develop aggregated modeling and optimization approaches, which will contribute on the knowledge of congestion dynamics in cities of different structures and mode usages, and ultimately facilitate the design of efficient and equitable urban transport policies. Building on the knowledge of the single-mode MFD theory, a bi-modal MFD model considering the effect of mode conflict is proposed for mixed networks of buses and cars. A system-level model is developed for multiple-region city network. The flow dynamics among regions are described by a regional level flow conservation law. A non-linear optimization framework is performed to optimize space allocation, minimizing the total passenger cost, given certain demand, city structure and road facility. Then, parking limitation is integrated in the proposed multi-modal system model, where vehicles cruising for parking are also integrated. The extra delay of cruising is captured by a geometric distribution related to the time-dependent parking availability and estimated at the aggregated level. The delay cost to other users is also estimated via the bi-modal MFD, and it shows the effect of cruising on all travelers who do not require parking. Optimal parking pricing policies for on-street and garage parking are obtained through the optimization framework, as well. The existence of a three-dimensional MFD (3D-MFD) for mixed bi-modal networks is investigated and analyzed via micro-traffic simulation studies. A 3D-MFD relates vehicular production of a network (flow, travel distance) to the density of cars and buses, where the impact of each mode on network performance can be directly observed. To further compare the modal impact on performance, the Bus-Car Unit equivalent value is estimated, indicating that this value is state- and mode-composition dependent rather than deterministic. In addition to the conventional vehicle-flow-based analysis, a passenger 3D-MFD is derived which provides a different perspective of the flow characteristics in bi-modal networks. Simulation study on 3D-MFD based perimeter-control shows promising performance in real-time control. The final part of the thesis concerns the MFD-controlled congestion pricing. Feedback-type control mechanisms are proposed to determine and adjust the time-dependent tolls, based on congestion level as expressed by the MFD. One pricing scheme also considers userâs adaptation to the toll cost, allowing a great flexibility in toll adjustment, and deals with the promotion of public transport usage. The performance of the pricing schemes is investigated in an existing agent-based model where the complex travel behavior in real-life is reasonably reproduced. Results demonstrate that the pricing schemes are effective in congestion reduction. Remarkably, smooth behavioral equilibrium in long-term operation is found under such pricing schemes. Furthermore, user heterogeneity with respect to value-of-time is introduced in the agent-based model. By realizing and treating this heterogeneity, pricing strategies can achieve even higher efficiency and equitable benefit.

EPFL2014

A Dynamic Network Approach for Multimodal Urban Mobility

Nan Zheng

EPFL2014