Estimation of the Network Capacity for Multimodal Urban Systems

Boyacı, Burak; Geroliminis, Nikolas

doi:10.1016/j.sbspro.2011.04.499

Cited by 39 publications

(22 citation statements)

References 14 publications

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“…The average trip length of buses can be easily estimated as buses have fixed routes. By using the above equations and variational theory Boyaci and Geroliminis, 2011) To validate all of the above assumptions, we performed a micro-simulation of San Francisco network taken from Geroliminis and Daganzo (2007), which provides a low scatter MFD and can be estimated with variational theory with small error. While in the previous version this was a car-only simulation, we performed additional simulations for shared-use bus-car lanes and for dedicated bus lanes with different bus frequencies and dwell times.…”

Section: Multimodal Travel Time Estimationmentioning

confidence: 99%

“…Recently, Gonzales et al (2011) observed through simulation an MFD for multimodal systems of cars and buses in the city center of Nairobi, Kenya. Boyaci and Geroliminis (2011) extended the VT theory for the multi-modal case and provided a semi-analytical approximation of the MFD, by considering that bus service related stops interact with traffic as hypothetical traffic signals with periodic characteristics. The operational characteristics of this hypothetical signal-bus stop depend on the dwell times and the frequencies of buses, while the capacity during service stops is smaller as buses might block traffic.…”

Section: Introductionmentioning

confidence: 99%

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On the distribution of urban road space for multimodal congested networks

Zheng

Geroliminis

2013

Transportation Research Part B: Methodological

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121

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a b s t r a c tTransport systems in real cities are complex with many modes of transport sharing and competing for limited road space. This work intends to understand how space distributions for modes and interactions among modes affect network traffic performance. While the connection between performance of transport systems and general land allocation is the subject of extensive research, space allocation for interacting modes of transport is an open research question. Quantifying the impact of road space distribution on the performance of a congested multimodal transport system with a dynamic aggregated model remains a challenge. In this paper, a multimodal macroscopic fundamental diagram (MFD) is developed to represent the traffic dynamics of a multimodal transport system. Optimization is performed with the objective of minimizing the total passenger hours traveled (PHT) to serve the total demand by redistributing road space among modes. Pricing strategies are also investigated to provide a higher demand shift to more efficient modes. We find by an application to a bi-modal two-region city that (i) the proposed model captures the operational characteristics of each mode, and (ii) optimal dynamic space distribution strategies can be developed. In practice, the approach can serve as a physical dynamic model to inform space distribution strategies for policy makers with different goals of mobility.

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Section: Multimodal Travel Time Estimationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

On the distribution of urban road space for multimodal congested networks

Zheng

Geroliminis

2013

Transportation Research Part B: Methodological

Self Cite

121

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“…Indeed, several studies have shown that MFD is a reliable tool for traffic agency to manage and evaluate solutions for improving mobility. Moreover, recent works (Daganzo and Laval 2005a;Boyaci and Geroliminis 2011;Leclercq and Geroliminis 2013;Xie, Chiabaut, and Leclercq 2013) propose accurate method to analytically estimate MFD for arterial based on its characteristics (number of lanes, traffic signal parameters, etc.). These existing methods will be extended to account for both buses and IBL strategies.…”

Section: Introductionmentioning

confidence: 99%

Performance analysis for different designs of a multimodal urban arterial

Chiabaut

Xie

Leclercq

2014

Transportmetrica B: Transport Dynamics

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This article aims to introduce an analysis framework to assess and compare different designs of an urban multimodal arterial before their implementation. Especially, the work focuses on dedicated bus lanes and intermittent bus lanes (IBLs), which are compared to the reference case where the buses and cars are mixed in the same flow. First, analytical considerations highlight the influence of buses and IBLs on traffic dynamics in free-flow conditions. Second, the article resorts to an aggregated and parsimonious model to account for both free-flow and congested traffic states. Such a model provides a better understanding and valuable insights on multimodal traffic dynamics on the arterial. To this end, the concept of passenger fundamental diagram is introduced. With this new relationship, efficiency of the global transport system, i.e. behaviours of cars and buses, is assessed and domains of applications of the different transit strategies are identified.

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“…Multi-modal MFDs are a powerful tool to investigate and understand the multimodal performance of entire urban road networks (Ampountolas et al, 2017;Zheng et al, 2017;Amirgholy et al, 2017). They can be estimated using both simulation and empirical observations (Geroliminis et al, 2014;Loder et al, 2017;Castrillon and Laval, 2018;Dakic and Menendez, 2018) or derived numerically (Boyaci and Geroliminis, 2011;Chiabaut, 2015;Dakic et al, 2019). So far, however, no particular functional form for multi-modal MFD exists, and no proposal has been made to link the physical properties of the road and bus network topology as well as the traffic operations to the shape of the 3D-MFD.…”

Section: Introductionmentioning

confidence: 99%

Capturing network properties with a functional form for the multi-modal macroscopic fundamental diagram

Loder

Dakic

Bressan

et al. 2019

Transportation Research Part B: Methodological

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In urban road networks, the interactions between different modes can clearly impact the overall travel production. Although those interactions can be quantified with the multi-modal macroscopic fundamental diagram; so far, no functional form exists for this diagram to explicitly capture operational and network properties. In this paper, we propose a methodology to generate such functional form, and we show its applicability to the specific case of a bi-modal network with buses and cars. The proposed functional form has two components. First, a three dimensional lower envelope limits travel production to the theoretical best-case situation for any given number of vehicles for the different modes. The lower envelopes parameters are derived from topology and operational features of the road network. Second, a smoothing parameter quantifies how interactions between all vehicle types reduce travel production from the theoretical best-case. The smoothing parameter is estimated with network topology and traffic data. In the case no traffic data is available, our functional form is still applicable. The lower envelope can be approximated assuming fundamental parameters of traffic operations. For the smoothing parameter, we show that it always hold similar values even for different networks, making its approximation also possible. This feature of the proposed functional form is an advantage compared to curve fitting, as it provides a reasonable shape for the multi-modal macroscopic fundamental diagram irrespective of traffic data availability. The methodology is illustrated and validated using simulation and empirical data sets from London and Zurich.

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Estimation of the Network Capacity for Multimodal Urban Systems

Cited by 39 publications

References 14 publications

On the distribution of urban road space for multimodal congested networks

On the distribution of urban road space for multimodal congested networks

Performance analysis for different designs of a multimodal urban arterial

Capturing network properties with a functional form for the multi-modal macroscopic fundamental diagram

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