scholarly journals Modelling the road network capacity considering residual queues and connected automated vehicles

2021 ◽  
Author(s):  
Peng Zhang ◽  
Hao Yue ◽  
Chunfu Shao ◽  
Xu Zhang ◽  
Bin Ran
Keyword(s):  
Road Network ◽  
Network Capacity ◽  
Automated Vehicles ◽  
The Road ◽  
Connected Automated Vehicles

A Combined Land-Use and Transportation Model for Work Trips

10.1068/b2608 ◽  
2000 ◽  
Vol 27 (1) ◽  
pp. 93-103 ◽  
Author(s):  
Qiang Meng ◽  
Hai Yang ◽  
Sze-Chun Wong
Keyword(s):  
Land Use ◽  
Road Network ◽  
Network Capacity ◽  
Programming Approach ◽  
Round Trip ◽  
Transportation Model ◽  
The Road ◽  
Land Use Model ◽  
On The Road ◽  
The Given

In this paper we propose a combined land-use and transportation model for work trips with constraints on the road network capacity. A Lowry-type land-use model is used to distribute all the given activities into various residential and employment zones. Trip distributions are based on the equilibrium round-trip cost, which is obtained from a network equilibrium model. A bilevel programming approach is used to determine the maximum number of trips that can be accommodated by the road network subject to the network-capacity constraints.

scholarly journals Macro-level road network evaluation by fuzzy signature rule bases

2021 ◽  
Vol 4 (1) ◽  
pp. 3-16
Author(s):  
Gergely Cs. Mikulai ◽  
László T. Kóczy
Keyword(s):  
Road Network ◽  
Network Capacity ◽  
Macro Level ◽  
Rule Base ◽  
The Road ◽  
Weak Points ◽  
Typical Part ◽  
Rule Bases ◽  
Available Information

In our fast-growing world, we need to create increasingly efficient systems to ensure further growth and sustainability. This also applies to transportation, where a key limitation is the bottle-necks of road network capacity. To eliminate, or at least, to moderate these bottlenecks, they must first be localised. In this case study, a model is proposed to objectively identify the weak points of the road infrastructure in the Western Hungarian region, a typical part of the Hungarian road net-work, based on automated data input. This way, there is no need to visually analyse the road net-work on site, but it is possible to evaluate the available information and suggest efficient measures from the distance. The model is suitable for general application, meaning it can serve other regions or countries as well, and enables macro-level decision-makers to take steps to eliminate those weak points. A fuzzy signature rule base is applied by the authors, which systematically maps and models the various attributes of the road network. The model currently contains more than 20 independent variables as inputs, but they can be easily expanded or replaced if further inputs need to be included.

scholarly journals The Impact of Automated Vehicles on Traffic Flow and Road Capacity on Urban Road Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Ji Eun Park ◽  
Wanhee Byun ◽  
Youngchan Kim ◽  
Hyeonjun Ahn ◽  
Doh Kyoum Shin
Keyword(s):  
Traffic Flow ◽  
Road Network ◽  
Traffic Volume ◽  
Transport Systems ◽  
Automated Vehicles ◽  
Average Delay ◽  
The Road ◽  
Capacity Increase ◽  
Road Capacity ◽  
The Impact

Automated vehicles (AVs) are believed to have great potential to improve the traffic capacity and efficiency of the current transport systems. Despite positive findings of the impact of AVs on traffic flow and potential road capacity increase for highways, few studies have been performed regarding the impact of AVs on urban roads. Moreover, studies considering traffic volume increase with a mixture of AVs and human-driven vehicles (HDVs) have rarely been conducted. Therefore, this study investigated the impact of gradual increments of AV penetration and traffic volume on urban roads. The study adopted a microsimulation approach using VISSIM with a Wiedmann 74 model for car-following behavior. Parameters for AVs were set at the SAE level 4 of automation. A real road network was chosen for the simulation having 13 intersections in a total distance of 4.5 km. The road network had various numbers of lanes from a single lane to five lanes in one direction. The network consists of a main arterial road and a parallel road serving nearby commercial and residential blocks. In total, 36 scenarios were investigated by a combination of AV penetrations and an increase in traffic volumes. The study found that, as AV penetration increased, traffic flow also improved, with a reduction of the average delay time of up to 31%. Also, as expected, links with three or four lanes had a more significant impact on the delay. In terms of road capacity increase, when the penetration of AVs was saturated at 100%, the road network could accommodate 40% more traffic.

scholarly journals Assessing Urban Road Network Capacity considering Parking Supply and Parking Pricing

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Xiaowei Jiang ◽  
Muqing Du ◽  
Haisheng Liu
Keyword(s):  
Road Network ◽  
Travel Demand ◽  
Management Strategies ◽  
Network Capacity ◽  
Assessment Model ◽  
Urban Road ◽  
The Road ◽  
Capacity Model ◽  
Congestion Effect ◽  
Parking Pricing

To enhance the assessment of the network capacity for a given urban road system, the effects of the parking management strategies at destination areas are supposed to be considered in the network capacity assessment model. This study provides an extended road network capacity model which takes into consideration both the parking supply and parking pricing at each traffic zone. The network capacity model is formulated as a bilevel programming problem, with the maximization of total trip generation in the upper level and the combined trip distribution and traffic assignment (CTDTA) problem in the lower level. To reasonably characterize the impacts of the parking pricing and parking delay due to the congestion effect, two classes of travel demand are involved in the CTDTA model. An efficient and practical algorithm is provided for the solution of the bilevel network capacity model. Numerical experiments show the advantages of the proposed model and also demonstrate the effect of the parking supply and parking pricing on the assessment results of the road network capacity.

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