Macroscopic Approach for Optimizing Road Space Allocation of Bus Lanes in Multimodal Urban Networks Through Simulation Analysis

Zheng, Nan; Dantsuji, Takao; Wang, Pengfei; Geroliminis, Nikolas

doi:10.3141/2651-05

Cited by 26 publications

(4 citation statements)

References 18 publications

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“…Based on numerical examples, the authors revealed that road degradation level, travellers' risk-aversion level, and the uncertainty of the bus waiting time affected the user equilibrium results. Zheng et al [37] employed a simulation approach to determine the optimal space share between the modes in service. The impact of a bus lane on mode usage was taken into account to aggregated mode shift phenomena under changes in the layout of dedicated bus lanes.…”

Section: Literature Reviewmentioning

confidence: 99%

Modelling the Modal Shift Effects of Converting a General Traffic Lane into a Dedicated Bus Lane

Yang

Wang

Mao

2020

PROMET

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This paper presents an analytical framework for evaluating the performance of dedicated bus lanes. It assumes that under a designated travel demand, the traffic volume on a corridor changes with the modal shifts. The modal shift affects the operations of both bus traffic and car traffic and eventually, an equilibrium bus share ratio that maximizes the performance of the corridor will be reached. Microsimulation modelling is employed to assess the traffic operations under various demand levels and bus share ratios. The results show that converting a general lane into a bus lane significantly reduces bus delay. For car traffic, the overall trend is that delay increases after converting a general lane to a bus lane. In addition, delay decreases with the increase of bus share ratio. Nevertheless, when bus share ratio reaches 0.6 (demand less than 10,000 passengers per hour, pph; or 0.8 when demand increases up to 14,000 pph), there is no significant difference in delay between the two scenarios. The identified bus share ratios have the potential to direct the development of bus lane warrants. Finally, this research recommends that the Transportation Demand Management (TDM) strategies shall be developed to stimulate the modal shifts towards the identified optimal bus share ratio.

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Section: Literature Reviewmentioning

confidence: 99%

Modelling the Modal Shift Effects of Converting a General Traffic Lane into a Dedicated Bus Lane

Yang

Wang

Mao

2020

PROMET

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“…The latter indicator describes a set of bi-modal traffic states in the network for which high passenger production values can be achieved. A few studies apply the concept of the pMFD in the context of multi-modal transport system optimization (Zheng and Geroliminis, 2013;Amirgholy et al, 2017;Zheng et al, 2017;Zhang et al, 2018). The main focus lies on space allocation between buses and cars based on analytical formulations for the MFD.…”

Section: Introductionmentioning

confidence: 99%

“…Still, these studies mainly apply semi-analytical models to estimate the MFD. While Zheng et al (2017) aimed to assign bus lanes, their study represents an example where an optimization based on microscopic simulation is conducted. Their objective was to minimize the occurrence of congestion in the network.…”

Section: Introductionmentioning

confidence: 99%

Simulation-Based Design of Urban Bi-modal Transport Systems

Tilg¹,

Abedin²,

Amini³

et al. 2020

Front. Future Transp.

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The three-dimensional passenger macroscopic fundamental diagram (pMFD) describes the relation of the network accumulation of public transport and private vehicles, and the passenger production. It allows for modeling the multi-modal traffic dynamics in urban networks and deriving innovative performance indicators. This paper integrates this concept into a multi-modal transport system design framework formulated as a simulation-based optimization problem. In doing so, we consider the competition for limited road space and the operational characteristics, such as congestion occurrences, at the strategic design level. We evaluate the proposed framework in a case study for the Sioux Falls network. Thereby, we deliver a proof of concept, and show that the proposed methodology indeed designs a transport system which benefits the overall system's performance. This paper further advances the integration of sequential model-based optimization techniques, macroscopic traffic flow concepts, and traffic simulation to design multi-modal transport systems. This supports transport planners and local authorities in composing efficient and robust transport networks.

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“…With additional information on (average) vehicle occupancy levels, the 3D-MFD can then be expressed in terms of passenger travel production (in passenger-kilometers per unit time) (Geroliminis et al, 2014;Loder et al, 2017;Chiabaut, 2015). 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).…”

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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Macroscopic Approach for Optimizing Road Space Allocation of Bus Lanes in Multimodal Urban Networks Through Simulation Analysis

Cited by 26 publications

References 18 publications

Modelling the Modal Shift Effects of Converting a General Traffic Lane into a Dedicated Bus Lane

Modelling the Modal Shift Effects of Converting a General Traffic Lane into a Dedicated Bus Lane

Simulation-Based Design of Urban Bi-modal Transport Systems

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

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