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

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

On the spatial partitioning of urban transportation networks

It has been recently shown that a macroscopic fundamental diagram (MFD) linking space-mean network flow, density and speed exists in the urban transportation networks under some conditions. An MFD is further well defined if the network is homogeneous with links of similar properties. This collective behavior concept can also be utilized to introduce simple control strategies to improve mobility in homogeneous city centers without the need for details in individual links. However many real urban transportation networks are heterogeneous with different levels of congestion. In order to study the existence of MFD and the feasibility of simple control strategies to improve network performance in heterogeneously congested networks, this paper focuses on the clustering of transportation networks based on the spatial features of congestion during a specific time period. Insights are provided on how to extend this framework in the dynamic case. The objectives of partitioning are to obtain (i) small variance of link densities within a cluster which increases the network flow for the same average density and (ii) spatial compactness of each cluster which makes feasible the application of perimeter control strategies. Therefore, a partitioning mechanism which consists of three consecutive algorithms, is designed to minimize the variance of link densities while maintaining the spatial compactness of the clusters. Firstly, an over segmenting of the network is provided by a sophisticated algorithm (Normalized Cut). Secondly, a merging algorithm is developed based on initial segmenting and a rough partitioning of the network is obtained. Finally, a boundary adjustment algorithm is designed to further improve the quality of partitioning by decreasing the variance of link densities while keeping the spatial compactness of the clusters. In addition, both density variance and shape smoothness metrics are introduced to identify the desired number of clusters and evaluate the partitioning results. These results show that both the objectives of small variance and spatial compactness can be achieved with this partitioning mechanism. A simulation in a real urban transportation network further demonstrates the superiority of the proposed method in effectiveness and robustness compared with other clustering algorithms. (C) 2012 Elsevier Ltd. All rights reserved

City size, network structure and traffic congestion

This paper presents an alternative approach for analyzing the relationship between land use and traffic congestion by employing the Macroscopic Fundamental Diagram (MFD). The MFD is an empirically observed relationship between traffic flow and traffic density at the level of an urban region, including hypercongestion, where flow decreases as density increases. This approach is consistent with the physics of traffic and allows the parsimonious modeling of intra-day traffic dynamics and their connection with city size, land use and network characteristics. The MFD can accurately measure the inefficiency of land and network resource allocation due to hypercongestion, in contrast with existing models of congestion. The findings reinforce the 'compact city' hypothesis, by favoring a larger mixed-use core area with greater zone width, block density and number of lanes, compared to the peripheral area. They also suggest a new set of policies, including the optimization of perimeter controls and the fraction of land for transport, which constitute robust second-best optimal strategies that can further reduce congestion externalities. (C) 2013 Elsevier Inc. All rights reserved

On the stability of traffic perimeter control in two-region urban cities

In this paper, stability analysis of traffic control for two-region urban cities is treated. It is known in control theory that optimality does not imply stability. If the optimal control is applied in a heavily congested system with high demand, traffic conditions might not change or the network might still lead to gridlock. A city partitioned in two regions with a Macroscopic Fundamental Diagram (MFD) for each of the regions is considered. Under the assumption of triangular MFDs, the two-region MFDs system is modeled as a piecewise second-order system. Necessary and sufficient conditions are derived for stable equilibrium accumulations in the undersaturated regimes for both MFDs. Moreover, the traffic perimeter control problem for the two-region MFDs system is formulated. Phase portraits and stability analysis are conducted, and a new algorithm is proposed to derive the boundaries of the stable and unstable regions. Based on these regions, a state-feedback control strategy is derived. Trapezoidal shape of MFDs are also addressed with numerical solutions. (C) 2012 Elsevier Ltd. All rights reserved

Perimeter and boundary flow control in multi-reservoir heterogeneous networks

In this paper, we macroscopically describe the traffic dynamics in heterogeneous transportation urban networks by utilizing the Macroscopic Fundamental Diagram (MFD), a widely observed relation between network-wide space-mean flow and density of vehicles. A generic mathematical model for multi-reservoir networks with well-defined MFDs for each reservoir is presented first. Then, two modeling variations lead to two alternative optimal control methodologies for the design of perimeter and boundary flow control strategies that aim at distributing the accumulation in each reservoir as homogeneously as possible, and maintaining the rate of vehicles that are allowed to enter each reservoir around a desired point, while the system's throughput is maximized. Based on the two control methodologies, perimeter and boundary control actions may be computed in real-time through a linear multivariable feedback regulator or a linear multivariable integral feedback regulator. Perimeter control occurs at the periphery of the network while boundary control occurs at the inter-transfers between neighborhood reservoirs. To this end, the heterogeneous network of San Francisco is partitioned into three homogeneous reservoirs and the proposed feedback regulators are compared with a pre-timed signal plan and a single-reservoir perimeter control strategy. Finally, the impact of the perimeter and boundary control actions is demonstrated via simulation by the use of the corresponding MFDs and other performance measures. A key advantage of the proposed approach is that it does not require high computational effort and future demand data if the current state of each reservoir can be observed with loop detector data. (C) 2013 Elsevier Ltd. All rights reserved

Estimating MFDs in simple networks with route choice

The concept of the Macroscopic Fundamental Diagram (MFD) is elegant and attractive because it provides a global view of traffic behavior and performance at a network level. However, recent research shows that the MFD shape can be influenced by local traffic heterogeneities. Notably, route choices and heterogeneous local capacities may drive uneven (in space) or inconsistent (in time) distributions of congestion and then affect the shape and the scatter of the MFD. We are far from having a global understanding of the connections between local phenomena and the resulting MFD. This paper first aims to improve existing MFD estimation method for a succession of links with traffic signals. The new method overcomes previous limitations, notably regarding to the topology and signal settings regularities, by fully utilizing the receipts of the variational theory. Then, a single network with several parallel routes is investigated. MFDs on different routes are estimated with the variational method and then aggregated in a unified MFD for stationary and dynamic conditions and different sorts of equilibria (user and system optimum). It appears that the flow distribution among routes smoothly varies with respect to the total flow either in free-flow or congestion situations. Such a distribution is much more rough for system optimum, where it presents some discontinuities and is far from equity. This means that a control strategy able to lead such a network to the perfect system optimum would be hard to tune, especially in the congested regime. However, being able to determine the MFD corresponding to the system optimum provides a valuable reference to estimate the current efficiency of the considered network. Case studies for different simple networks and insights for generalization at the city level are proposed. (C) 2013 Elsevier Ltd. All rights reserved

Identification and Analysis of Queue Spillovers in City Street Networks

We propose a methodology for identifying queue spillovers in city street networks with signalized intersections using data from conventional surveillance systems, such as counts and occupancy from loop detectors. The key idea of the proposed methodology is that when spillovers from a downstream link block vehicle departures from the upstream signal line, queues discharge at rates smaller than the saturation flow. The application of the methodology on an arterial site and the comparison with field data show that it consistently identifies spillovers in urban networks with signal-controlled intersections. The method is extended to account for the variations in vehicle lengths. We also investigate the significant effect of spillovers in congestion and show that a macroscopic diagram that connects spillovers with vehicle density exists in large-scale congested urban networks

Empirical observations of capacity drop in freeway merges with ramp control and integration in a first-order model

An accurate density monitoring along a stretch of a freeway, especially under congested time-variant conditions is necessary to evaluate congestion levels, understand complex traffic phenomena and develop efficient control strategies. In the first part of the paper (i) we show empirical evidence from freeway-ramp merges in Twin Cities freeway system, in favor of the capacity drop phenomenon, (ii) we provide a methodology based on phase diagrams to quantitatively estimate the level of the drop, (iii) we show that the level of the drop depends on the ratio of mainline vs. ramp flow and (iv) we investigate whether implementation of control strategies has an effect on the value of capacity drop. In the second part of the paper, we develop a methodology to estimate densities with space and time based on data from loop detectors, by integrating the capacity drop. The methodology is based on solving a flow conservation differential equation (using LWR theory) with intermediate (internal) freeway mainline boundaries, which is faster and more accurate from approaches using only external boundaries. To capture the capacity drop phenomenon into the first-order model we utilize a fundamental diagram with two values of capacity and we provide a memory-based methodology to choose the appropriate value in the numerical solution of the problem with a Godunov scheme. Results compared with real data and micro-simulation of a long freeway stretch show that this model produces more reliable and accurate results than previous theories. (C) 2013 Elsevier Ltd. All rights reserved

On the estimation of arterial route travel time distribution with Markov chains

Recent advances in the probe vehicle deployment offer an innovative prospect for research in arterial travel time estimation. Specifically, we focus on the estimation of probability distribution of arterial route travel time, which contains more information regarding arterial performance measurements and travel time reliability. One of the fundamental contributions of this work is the integration of travel time correlation of route's successive links within the methodology. In the proposed technique, given probe vehicles travel times of the traversing links, a two-dimensional (2D) diagram is established with data points representing travel times of a probe vehicle crossing two consecutive links. A heuristic grid clustering method is developed to cluster each 2D diagram to rectangular sub spaces (states) with regard to travel time homogeneity. By applying a Markov chain procedure, we integrate the correlation between states of 2D diagrams for successive links. We then compute the transition probabilities and link partial travel time distributions to obtain the arterial route travel time distribution. The procedure with various probe vehicle sample sizes is tested on two study sites with time dependent conditions, with field measurements and simulated data. The results are very close to the Markov chain procedure and more accurate once compared to the convolution of links travel time distributions for different levels of congestion, even for small penetration rates of probe vehicles. (C) 2012 Elsevier Ltd. All rights reserved