Flow pattern and optimal capacity in a bi-modal traffic corridor with heterogeneous users

Liu, Peng; Liu, Jielun; Ong, G. B.; Qiu, Tian

doi:10.1016/j.tre.2019.101831

Cited by 17 publications

(3 citation statements)

References 59 publications

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“…This research delved into methods for effectively managing traffic patterns in areas where autonomous vehicles are prevalent, with an emphasis on trajectory-based approaches. Additionally, researchers have considered the effects of transportation mode choice and activities on travelers and studied travel choice behaviors based on bottleneck models [30,31].…”

Section: Traffic Bottleneck Modelmentioning

confidence: 99%

Travel Plan Sharing and Regulation for Managing Traffic Bottleneck Based on Blockchain Technology

Zhu,

Yu,

Fan

2024

Sustainability

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To alleviate traffic congestion, it is necessary to effectively manage traffic bottlenecks. In existing research, travel demand prediction for traffic bottlenecks is based on travel behavior assumptions, and prediction accuracy is low in practice. Thus, the effect of traffic bottleneck management strategies cannot be guaranteed. Management strategies are often mandatory, leading to problems such as unfairness and low social acceptance. To address such issues, this paper proposes managing traffic bottlenecks based on shared travel plans. To solve the information security and privacy problems caused by travel plan sharing and achieve information transparency, travel plans are shared and regulated by blockchain technology. To optimize the operation level of traffic bottlenecks, travel plan regulation models under scenarios where all/some travelers share travel plans are proposed and formulated as linear programming models, and these models are integrated into the blockchain with smart contract technology. Furthermore, travel plan regulation models are tested and verified using traffic flow data from the Su-Tong Yangtze River Highway Bridge, China. The results indicate that the proposed travel plan regulation models are effective for alleviating traffic congestion. The vehicle transfer rate and total delay rate increase as the degree of total demand increases; the vehicle transfer rate increases as the length of the time interval decreases; and the vehicle transfer rate and total delay rate increase as the number of vehicles not sharing their travel plans increases. By using the model and method proposed in this paper, the sustainability of urban economy, society, and environment can be promoted. However, there are many practical situations that have not been considered in this paper, such as multiple entry and exit bottlenecks, multiple travel modes, and other control strategies. In addition, this paper considers only one bottleneck rather than road networks because of the throughput limitations of blockchain technology.

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Section: Traffic Bottleneck Modelmentioning

confidence: 99%

Travel Plan Sharing and Regulation for Managing Traffic Bottleneck Based on Blockchain Technology

Zhu,

Yu,

Fan

2024

Sustainability

View full text Add to dashboard Cite

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“…Comparatively, in the transit corridor design, the route alignment is typically predetermined, and thus, the station location and the frequency need to be determined. ere are plenty of studies related to the transit corridor design with different travel modes, for example, regular bus, bus rapid transit, rail, and mixed [4,5,11,12], compositions of travel demand, for example, many-to-one, one-to-many, and many-to-many [13][14][15], and objectives, for example, coverage maximization, passenger cost minimization, and system cost minimization [15][16][17][18]. Typically, the discrete models are adopted in most of the above literature in transit service design.…”

Section: Literature Reviewmentioning

confidence: 99%

Continuum Approximation Model for Transit Service Design with Stochastic Demand

Xia

Fan

et al. 2022

Journal of Advanced Transportation

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Travel demand is commonly predefined as a constant during the planning period in transit service design, but it varies daily with many factors, for example, weather, vacation, and social activity. Under the uncertain demand, the transit system operates in two states, that is, unsaturation and saturation, distinguished by whether or not the capacity of transit vehicle satisfies the possible demand. Thus, we propose a continuum approximation (CA) model for transit service design, including headway and station location, to account for the effects of the stochastic demand via a penalty cost, a service-reliability constraint, and equilibrium. The penalty cost is utilized to describe the saturation state. The service-reliability constraint is applied to ensure the robustness of the transit system. The equilibrium is introduced to allocate the household location where trip demand is generated in a corridor. Furthermore, we build a bilevel framework to find the solutions to the proposed model. In the numerical experiment, the proposed model is applied in the impact analyses of the service-reliability constraint, as well as the sensitivity analyses of the household numbers and value of time. The impact analyses indicate that the transit service design integrated with the effect of housing location choice is necessary under the stochastic demand. The sensitivity analyses show that the number of households and the value of time play a significant role in the performance of transit systems accounting for service reliability. The proposed model and findings serve to improve the design of the transit system under stochastic demand.

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“…The model supposed that the travelers' behavioral adjustment of decision-making of travelers followed the principle of random utility maximization only when the perceived difference in utility between modes was greater than the indifference threshold; otherwise, travelers chose randomly. Liu et al [20] investigated modal split and departure time choices of heterogeneous travelers and two capacity design problems, i.e., total travel cost minimization with budget constraints and total system cost minimization with budget and equity constraints in a bi-modal traffic corridor with a highway and a transit line.…”

Section: B Bi-modal Transport Systemmentioning

confidence: 99%

Capacity Design and Pareto Improvement of Highway Toll Plaza in a Competitive Transport System

Gui

Zhang

et al. 2021

IEEE Access

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As the traffic infrastructure for collecting vehicle tolls, the capacity of the toll plaza determines the service level of the entire highway. The capacity of a toll plaza is highly correlated with its operating costs, especially in peak periods. In this paper, it is assumed that in a competitive transportation system, the residential area and the workplace are connected by a highway with a toll plaza which forms a bottleneck, parallel to a mass transit line; commuters can choose to travel by car or by public transport. By establishing an equilibrium model and two mathematical programming models, the capacity designs of the toll plaza were studied during the traffic service period to achieve three objectives, namely, the toll plaza breaking even, profit maximization, and total social cost minimization of the transportation system. The travel modal splits were analyzed under travel equilibrium in three situations, respectively. In addition, a biobjective optimization model was developed to optimize total profit and total social cost, and a Pareto optimization scheme was analyzed. Finally, the theoretical analyses were also verified by numerical examples.INDEX TERMS Bi-modal traffic, bi-objective optimization model, capacity design, highway toll plaza.

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Flow pattern and optimal capacity in a bi-modal traffic corridor with heterogeneous users

Cited by 17 publications

References 59 publications

Travel Plan Sharing and Regulation for Managing Traffic Bottleneck Based on Blockchain Technology

Travel Plan Sharing and Regulation for Managing Traffic Bottleneck Based on Blockchain Technology

Continuum Approximation Model for Transit Service Design with Stochastic Demand

Capacity Design and Pareto Improvement of Highway Toll Plaza in a Competitive Transport System

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