Urban-scale Network Research Articles

Chain reaction of traffic breakdowns in coupled-cycle networks

We present a dynamic model for major traffic jams in urban-scale networks. We investigate the traffic breakdown in the directed network consisted of cycle graphs when an intersection is closed to vehicles. We show how the traffic breakdown propagates from cycle graph to cycle graph. The deadlock (jam) of vehicles is induced by the closed intersection, a local breakdown occurs at an early stage, and the breakdown propagates toward the whole network. The macroscopic dynamic equations of vehicular densities are derived by using the speed-matching model. The densities and currents (flows) on all roads are obtained numerically. We show that the chain reaction of traffic breakdowns occurs when a density is higher than a critical value, while it does not propagate over the network at lower density than the critical value. The chain reaction of traffic breakdowns induces the major traffic jam. The jamming transition between free traffic and major traffic jam is found in the traffic network.

Modeling and solving the optimal allocation-pricing of public parking resources problem in urban-scale network

This paper models and solves the optimal allocation-pricing of reservable parking resources and the pricing of unreservable parking resources, respectively. For reservable parking facility, a MP-DGS (modified proxy Demange-Gale-Sotomayor) mechanism and combinatorial system (integration of direct and evolutionary methods) are adopted to maximize the social surplus through optimizing the allocation-pricing of parking permits. As a result, it is found that: (i) the proposed approaches not only simplify the users’ bidding procedures but also ensure the users express their preference truthfully even under the situation of non-optimal parking permits allocation; (ii) in homogeneous case (parking periods for all users are the same), it is theoretically demonstrated that the MP-DGS mechanism is more efficient than the traditional mechanisms in the worst-case scenario; (iii) in heterogeneous case (users are heterogeneous in desired parking timing and duration), time-dependent parking permits are taken into account. The ranking of the algorithm time complexity in the worst-case scenario is that direct method = evolutionary method < Leonard mechanism = VCG (Vickrey-Clarke-Groves) mechanism, and the combinatorial system not only solves out the optimal allocation-pricing results effectively but also ensures the optimal results can be obtained in a shorter time. In addition, for unreservable parking facility, we formulate a dynamic social optimum as a stochastic control problem and then obtain a region-based optimal dynamic parking pricing. Through theoretical analysis, it is revealed that depending on the realization of the queue length due to the cruising-for-parking, the region-based optimal dynamic parking pricing can be divided into two patterns, furthermore, each pattern results in a “bang-bang” control.

A Global Sensitivity Analysis of Dynamic Loading and Route Selection Parameters on Network Performances

We conduct a Global Sensitivity Analysis (GSA) of urban-scale network performances to parameters representing a wide range of realistic dynamic loadings, decomposed in a choice of OD matrix, routing alternatives, and paths flow distribution. A special attention is given to the route alternatives generation, where overlapping metrics and selection methods are introduced to reproduce a wide variety of paths sets configuration. Paths flow distributions are calculated based on different equilibrium criteria. Several sets of simulations are conducted and analyzed graphically and then with a variance-based GSA method so as to get insights on how much and in which conditions each network loading parameter influences network performances by itself or by interaction. Results notably reveal that the demand level is the most decisive parameter since low values simply lead to free-flow conditions with no influence of the other parameters, whereas higher values lead to a wide diversity of network states going from close to capacity but stable to gridlocked. While a nonnegligible amount of this disparity is explained by the demand pattern parameter, the number of paths per OD, their overlapping, and the equilibrium criterion of the paths flow distribution are still influential enough to maintain the network close to its optimal capacity or to prevent the network from fast collapse (gridlock). The highlighted connection between spatial and temporal heterogeneities of the network states explains the gridlocking phenomena. These extracted insights are very encouraging for operational implementations.

Dynamic Modeling of Failure Events in Preventative Pipe Maintenance

Urban water supply network is ubiquitous and indispensable to city dwellers, especially in the era of global urbanization. Preventative maintenance of water pipes, especially in urban-scale networks, thus becomes a vital importance. To achieve this goal, failure prediction that aims to pro-actively pinpoint those “most-risky-to-fail” pipes becomes critical and has been attracting wide attention from government, academia, and industry. Different from classification-, regression-, or ranking-based methods, this paper adopts a point process-based framework that incorporates both the past failure event data and individual pipe-specific profile including physical, environmental, and operational covariants. In particular, based on a common wisdom of previous work that the failure event sequences typically exhibit temporal clustering distribution, we use mutual-exciting point process to model such triggering effects for different failure types. Our system is deployed as a platform commissioned by the water agency in a metropolitan city in Asia, and achieves state-of-the-art performance on an urban-scale pipe network. Our model is generic and thus can be applied to other industrial scenarios for event prediction.

Evaluating link criticality of road network based on the concept of macroscopic fundamental diagram

ABSTRACTA measure related to resilience and vulnerability can be useful in supporting decision-making process for maintenance and repair strategies. The existing measures have been focusing on large-scale road networks like highways between cities, although urban-scale networks are equally important. This study proposes a new methodology for evaluating link criticality of urban road network based on the concept of macroscopic fundamental diagram (MFD). Such operational measure is derived by comparing the MFD behaviour in normal condition and the behaviour in event condition, in which a link of a road network is disabled by an extreme event. A simulation study for testing the proposed measure is practiced on the road network of Gangnam district, Seoul, South Korea. The results show that the measure can help us observe the different patterns of network flow reduction by different traffic states. This work provides a new perspective of investigating link criticality of road networks.

Real-Time Dynamic Origin-Destination Matrix Adjustment with Simulated and Actual Link Flows in Urban Networks

The efficiency and robustness of different real-time dynamic origin–destination (O-D) matrix adjustment algorithms were investigated when implemented in large-scale transportation networks. The proposed algorithms produce time-dependent O-D trip matrices based on the maximum-entropy trip departure times with simulated and actual observed link flows. Implementation of the algorithms, which are coupled with a quasi-dynamic traffic assignment model, indicated their convergent behavior and their potential for handling realistic urban-scale network problems in terms of both accuracy and computational time. The main factors influencing the numerical performance of each algorithm were identified and analyzed. Their relative efficiency was found to be particularly dependent on the level at which the assigned flows approximate the observed link flows. These results may provide insights into the suitability of each algorithm for diverse application domains, including freeways, small networks, and large-scale urban networks, where a different quality of O-D information is usually available.