1,175 research outputs found

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

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    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-vMFD) 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 bi-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 bi-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

    The application of variable speed limits to arterial roads for improved traffic flow

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    Traffic congestion problems continue to increase in large cities due to rapidly increasing travel demand and a lack of transport infrastructure. Congestion causes mobility and efficiency loss, safety reduction, increased fuel consumption and excessive air pollution. A number of traffic management strategies have been proposed and some are applied in cities, such as diverting traffic from peak periods to off-peak periods using congestion pricing, reduced speed limits, coordinated traffic signals along major arterial roads, or adding additional lanes where network expansion is feasible. Among the many solutions to traffic congestion, operational treatments for existing road networks provide more cost efficient traffic operation due to their relatively low cost. This research looks to improve efficiency through the application of Variable Speed Limits (VSLs). While VSLs have been used to improve traffic conditions on congested motorways in terms of mobility, safety and travel time, they are largely untested on signalized urban arterial roads. Griffith Arterial Road (GAR) U20 was selected as the case study for the research. GAR is part of the Brisbane Urban Corridor (BUC), and is approximately 11.5 km long and lies between the Gateway Motorway and the Ipswich Motorway. The average daily traffic volume (ADT) is between 18,000 vehicles to 24,000 vehicles. The number of lanes at approaches to signalised intersection varies from 1 to 4. In the context of this research, the study used STREAMS data and real world data collected using six high definition (HD) video cameras to develop a VISSIM model and to discern the effectiveness of applying VSL control. VISSIM is a time step and a psycho-physical car following model developed to model urban traffic and public transit operations. The VISSIM model was extensively calibrated and validated with the empirical data collected regarding measure of effectiveness such as traffic volumes, volume distribution, and saturated headway along the west bound (WB) and eastbound (EB) directions. The simulated model allowed the testing of different control strategies for VSL and Integrated Traffic Control System (ITCS) under different scenarios and circumstances. It helped to contrast the traffic flow parameters of invariant (no controlled speed) and VSL (controlled speed) conditions. Multiple simulation runs were considered in the calibration and evaluation process. The measures of effectiveness used to characterise the operational quality of signalized intersections were delay, queue length, and number of stops. In addition, flow, speed and density parameters were used to characterise the changes in traffic performance for the arterial road. This thesis investigates the application of VSLs for control of upstream traffic as a proposed traffic control strategy on the GAR. The objective was to investigate how dynamic VSL and signal control systems could be used in an integrated approach to traffic management to improve the traffic efficiency, safety, and mobility of a congested urban arterial road. The research indicates that the application of VSL could improve the traffic performance and safety during the peak period. It helped to maintain a planned continuous flow through coordinated intersections to avoid congestion. Integrating VSL with other traffic congestion management (changing the signal timings for the congested traffic) appeared effective in improving traffic conditions and reducing total travel time on the GAR. The research highlighted some important elements that could be used for the design and implementation of VSL systems using intelligent transport systems

    Heterogeneous perimeter flow distributions and MFD-based traffic simulation

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    This paper investigates how network and traffic heterogeneities influence the accuracy of a simulation based on the Macroscopic Fundamental Diagram (MFD). To this end, the MFD modeling of a simple grid network is compared to the outputs of a mesoscopic kinematic wave model simulating traffic in the same network. Heterogeneous distributions of demand and supply at the boundaries are set to the local entries and exits of the mesoscopic model to generate heterogeneous network loadings. These boundary conditions challenge the MFD simulation, as significant discrepancies are observed between both modeling approaches in steady state. While the accurate calibration of the MFD and the average trip length can reduce the discrepancies for heterogeneous demand settings, no simple solution exists for heterogeneous supply settings, because they may drive very different internal congestion patterns in the network. We propose a correction method to adjust the MFD model outputs in such a case

    Urban Network Gridlock: Theory, Characteristics, and Dynamics

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    AbstractThis study explores the limiting properties of network-wide traffic flow relations under heavily congested conditions in a large-scale complex urban street network; these limiting conditions are emulated in the context of dynamic traffic assignment (DTA) experiments on an actual large network. The primary objectives are to characterize gridlock and understand its dynamics. This study addresses a gap in the literature with regard to the existence of exit flow and recovery period. The one- dimensional theoretical Network Fundamental Diagram (NFD) only represents steady-state behavior and holds only when the inputs change slowly in time and traffic is distributed homogenously in space. Also, it does not describe the hysteretic behavior of the network traffic when a gridlock forms or when network recovers. Thus, a model is proposed to reproduce hysteresis and gridlock when homogeneity and steady-state conditions do not hold. It is conjectured that the network average flow can be approximated as a non-linear function of network average density and variation in link densities. The proposed model is calibrated for the Chicago Central Business District (CBD) network. We also show that complex urban networks with multiple route choices, similar to the idealized network tested previously in the literature, tend to jam at a range of densities that are smaller than the theoretical average network jam density. Also it is demonstrated that networks tend to gridlock in many different ways with different configurations. This study examines how mobility of urban street networks could be improved by managing vehicle accumulation and re-distributing network traffic via strategies such as demand management and disseminating real-time traveler information (adaptive driving). This study thus defines and explores some key characteristics and dynamics of urban street network gridlocks including gridlock formation, propagation, recovery, size, etc

    Compound Impact on Private and Public Transport Network Performance on Integration of New Forms of Mobility

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    Continued evolutions in autonomous drive technologies and pandemic leading to a boom in micro-mobility usage make these new forms of mobility an integral part of investigative research to assess their impacts on transportation networks. This research thesis examines their impacts in terms of: quantification of the penetration rate of autonomous vehicles (AVs), the influence of physical characteristics of the urban road network on macroscopic fundamental parameters in heterogeneous traffic stream, inequities in travel costs equilibrium, assessment of public transport (PuT) network vulnerability against random service disruptions and importance of topography for accurate provision of micro-mobility services. Some benefits for 25-35% inclusion of AVs include enhanced network capacity, improvement in travel time, decrement in travel equilibrium costs. Whereas, the integrated micro-mobility modes reduce the commuter’s dis-utility and perceived journey times by 7.14% in case of disruptions. However, the spill-over effects are to watch out for

    Understanding the costs of urban transportation using causal inference methods

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    With urbanisation on the rise, the need to transport the population within cities in an efficient, safe and sustainable manner has increased tremendously. In serving the growing demand for urban travel, one of the key policy question for decision makers is whether to invest more in road infrastructure or in public transportation. As both of these solutions require substantial spending of public money, understanding their costs continues to be a major area of research. This thesis aims to improve our understanding of the technology underlying costs of operation of public and private modes of urban travel and provide new empirical insights using large-scale datasets and application of causal econometric modelling techniques. The thesis provides empirical and theoretical contributions to three different strands in the transportation literature. Firstly, by assessing the relative costs of a group of twenty-four metro systems across the world over the period 2004 to 2016, this thesis models the cost structure of these metros and quantifies the important external sources of cost-efficiency. The main methodological development is to control for confounding from observed and unobserved characteristics of metro operations by application of dynamic panel data methods. Secondly, the thesis provides a quantification of the travel efficiency arising from increasing the provision of road-based urban travel. A crucial pre-condition of this analysis is a reliable characterisation of the technology describing congestion in a road network. In pursuit of this goal, this study develops novel causal econometric models describing vehicular flow-density relationship, both for a highway section and for an urban network, using large-scale traffic detector data and application of non-parametric instrumental variables estimation. Our model is unique as we control for bias from unobserved confounding, for instance, differences in driving behaviour. As an important intermediate research outcome, this thesis also provides a detailed association of the economic theory underlying the link between the flow-density relationship and the corresponding production function for travel in a highway section and in an urban road network. Finally, the influence of density economies in metros is investigated further using large-scale smart card and train location data from the Mass Transit Railway network in Hong Kong. This thesis delivers novel station-based causal econometric models to understand how passenger congestion delays arise in metro networks at higher passenger densities. The model is aimed at providing metro operators with a tool to predict the likely occurrences of a problem in the network well in advance and materialise appropriate control measures to minimise the impact of delays and improve the overall system reliability. The empirical results from this thesis have important implications for appraisal of transportation investment projects.Open Acces

    Establishment & Assessment of the Macroscopic Fundamental Diagrams for the City of Durban Freeway Network Using Empirical Data

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    The history of traffic flow studies dates to the years between the 1960s and 1970s. This paper reviews the history of traffic flow studies in the context of Macroscopic Fundamental Diagrams (MFD) to date. The recent findings have shown that understanding the Macroscopic Fundamental Diagrams (MFD) in cities can bring success in managing congestions. This study aimed to establish the Macroscopic Fundamental Diagrams (MFD) for the City of Durban Freeway network. Motivated the study was a failure seen in various transportation systems after the 2010 FIFA world cup in South African cities. This failure was associated with the adoption of the transportation system from first-world countries. The South African cities are not densified when compared to the first world countries' cities, of course, due to spatial urban planning and segregation of the past. The key lesson was that SA transportation systems problems are unique; solutions should be attributed to the existing travel demand conditions. This birthed the idea that the performance of a traffic system should uniquely serve the specific travel demands. The core aim of this study was to establish the MFD for the freeway network in the City of Durban, South Africa. Two major freeway corridors were evaluated, i,e. the National route 2 and 3. The study used loop detector data extracted from a total of 88 loop detector stations. The loop detector stations were dispersed 100-500 m apart over the network. The data was recorded in September 2019. The collected data was analysed in five minutes intervals. When the MFD was established on the network, aggregated detector loops produced a well defined MFD on the 2 nd,3rd ,16th, and the 23rd of September, whereas, on a separate day (30th of September), a scattered MFD forming a hysteresis loop was observed. The formation of the hysteresis was associated with the lack of alternative routes for drivers to avoid congestions in the network. These observations are discussed later in this paper. The study was a success as it did reveal that the MFD was an attribute of the City of Durban freeway network. The established MFD showed that the freeway network operates between the unsaturated and saturated state. This MFD does not reach the saturated flow. The highest recorded density was found at 10.11 veh/km while the highest recorded flow was found at 733.28 veh/hr. The network operates at an average speed of vav= 79.84 km/hr. The estimated average density for the network to reach the gridlocked state was calculated to be 75veh/km

    A Dynamic Network Approach for Multimodal Urban Mobility:Modeling, Pricing and Control

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    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
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