Pareto-Optimal Sustainable Transportation Network Design under Spatial Queuing

Wei, Huang; Xu, Guangming; Lo, Hong Kam

doi:10.1007/s11067-020-09494-6

Cited by 6 publications

(2 citation statements)

References 59 publications

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“…To this end, it is critical to quantify the impact of road traffic on the environment when designing transportation networks, not only with the aim of minimizing the system travel time (or associated cost), but also seeking to minimize the negative impacts of traffic on the environment [3,4]. Some researchers have investigated transportation network design problems (NDPs) in the context of environmental considerations, such as minimizing emission and traffic noise from different perspectives, but to our knowledge not in a context involving a heterogeneous traffic stream consisting of connected and autonomous vehicles (CAVs) and human-driven vehicles (HVs) [5,6].…”

Section: Introductionmentioning

confidence: 99%

Multiobjective Environmentally Sustainable Optimal Design of Dedicated Connected Autonomous Vehicle Lanes

et al. 2021

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The emergence of connected autonomous vehicles (CAVs) is not only improving the efficiency of transportation, but also providing new opportunities for the sustainable development of transportation. Taking advantage of the energy consumption of CAVs to promote the sustainable development of transportation has attracted extensive public attention in recent years. This paper develops a mathematical approach to investigating the problem of the optimal implementation of dedicated CAV lanes while simultaneously considering economic and environmental sustainability. Specifically, the problem is described as a multi-objective bi-level programming model, in which the upper level is to minimize the system-level costs including travel time costs, CAV lane construction cost, and emission cost, whereas the lower level characterizes the multi-class network equilibrium with a heterogeneous traffic stream consisting of both human-driven vehicle (HVs) and CAVs. To address the multi-objective dedicated CAV lane implement problem, we propose an integrated solution framework that integrates a non-dominated sorting genetic algorithm II (NSGA-II) algorithm, diagonalized algorithm, and Frank–Wolfe algorithm. The NSGA-II was adopted to solve the upper-level model, i.e., hunting for the optimal CAV lanes implementation schemes. The diagonalized Frank–Wolfe (DFW) algorithm is used to cope with multi-class network equilibrium. Finally, numerical experiments were conducted to demonstrate the effectiveness of the proposed model and solution method. The experimental results show that the total travel time cost, total emission cost, and total energy consumption were decreased by about 12.03%, 10.42%, and 9.4%, respectively, in the Nguyen–Dupuis network as a result of implementing the dedicated CAV lanes.

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Section: Introductionmentioning

confidence: 99%

Multiobjective Environmentally Sustainable Optimal Design of Dedicated Connected Autonomous Vehicle Lanes

et al. 2021

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“…Vehicular emission has a direct impact on air quality, which becomes a major concern of many local authorities. There are three main pollutants from the vehicular emissions that have critical negative impacts on human health and the environment, i.e., carbon monoxide (CO), violate organic compounds (VOC), and nitrogen oxides (NOx) (Huang et al, 2020), which are considered in this paper to estimate the emission cost. The total emission cost is calculated by multiplying the traffic flow on each link by the link length (i.e., trip length on the link) and an emission factor.…”

Section: The Bi-level Model For Optimizing the Pandr Facility Locatio...mentioning

confidence: 99%

Joint optimisation of park-and-ride facility locations and alternate traffic restriction scheme under equilibrium flows

Chen

Liu

2022

Transportmetrica A: Transport Science

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Alternate traffic restriction (ATR) or road space rationing schemes manage traffic congestion by prohibiting a proportion of cars from entering a predetermined ATR area during designated time periods or days. Under the ATR scheme, Park-and-Ride (P&R) often becomes more popular as travelers are able to take advantage of driving on non-restricted roads while they can park their cars at P&R facilities and do not need to drive into the predetermined ATR area. This paper proposes a joint optimization model of P&R facility locations and the ATR scheme, which optimally designs the ATR areas, the proportion of private cars to be restricted, and the P&R facility locations. In particular, a multi-objective bi-level model is established. The upperlevel model minimizes the total travel cost, minimizes the total emission cost, and maximizes consumer surplus. The lower-level model characterizes the user equilibrium of travel mode choices (i.e., private car mode, public transport mode, and P&R mode) and the route choices.The non-dominated sorting genetic algorithm (NSGA-II) is adapted to solve the proposed multi-objective bi-level model, where a gradient project algorithm is proposed for solving the lower-level user equilibrium with both mode choices and route choices. Numerical studies are conducted to test and illustrate the applicability of the model and algorithms.

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Winner Determination with Sustainable-Flexible Considerations Under Demand Uncertainty in Transportation Service Procurement Auctions

Qian,

Yin,

Chan

et al. 2023

Netw Spat Econ

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Pareto-Optimal Sustainable Transportation Network Design under Spatial Queuing

Cited by 6 publications

References 59 publications

Multiobjective Environmentally Sustainable Optimal Design of Dedicated Connected Autonomous Vehicle Lanes

Multiobjective Environmentally Sustainable Optimal Design of Dedicated Connected Autonomous Vehicle Lanes

Joint optimisation of park-and-ride facility locations and alternate traffic restriction scheme under equilibrium flows

Winner Determination with Sustainable-Flexible Considerations Under Demand Uncertainty in Transportation Service Procurement Auctions

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