Analysis of traffic congestion induced by the work zone

Fei, L.; Zhu, Huibing; Han, Xianglin

doi:10.1016/j.physa.2016.01.036

Cited by 53 publications

(19 citation statements)

References 21 publications

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“…This is similar to what happens with the other vehicles. Therefore, 95% of drivers can only choose to change lanes if the rear spacing on the target lane is greater than the safe distance or if their speed is higher than that of the corresponding vehicles on the target lane [64,65]. Figure 2 represents the lane-changing behavior pattern of a simple case in which a standard manual car is willing to change lane.…”

Section: Aggressive Lane Change Policymentioning

confidence: 99%

An Assessment of Age and Gender Characteristics of Mixed Traffic with Autonomous and Manual Vehicles: A Cellular Automata Approach

Tanveer

Kashmiri

Naeem³

et al. 2020

Sustainability

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Traffic congestion has become increasingly prevalent in many urban areas, and researchers are continuously looking into new ways to resolve this pertinent issue. Autonomous vehicles are one of the technologies expected to revolutionize transportation systems. To this very day, there are limited studies focused on the impact of autonomous vehicles in heterogeneous traffic flow in terms of different driving modes (manual and self-driving). Autonomous vehicles in the near future will be running parallel with manual vehicles, and drivers will have different characteristics and attributes. Previous studies that have focused on the impact of autonomous vehicles in these conditions are scarce. This paper proposes a new cellular automata model to address this issue, where different autonomous vehicles (cars and buses) and manual vehicles (cars and buses) are compared in terms of fundamental traffic parameters. Manual cars are further divided into subcategories on the basis of age groups and gender. Each category has its own distinct attributes, which make it different from the others. This is done in order to obtain a simulation as close as possible to a real-world scenario. Furthermore, different lane-changing behavior patterns have been modeled for autonomous and manual vehicles. Subsequently, different scenarios with different compositions are simulated to investigate the impact of autonomous vehicles on traffic flow in heterogeneous conditions. The results suggest that autonomous vehicles can raise the flow rate of any network considerably despite the running heterogeneous traffic flow.

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Section: Aggressive Lane Change Policymentioning

confidence: 99%

An Assessment of Age and Gender Characteristics of Mixed Traffic with Autonomous and Manual Vehicles: A Cellular Automata Approach

Tanveer

Kashmiri

Naeem³

et al. 2020

Sustainability

View full text Add to dashboard Cite

show abstract

“…Research on the lane-changing behavior of RVs [35,36] indicates that slower preceding vehicles would in many situations tempt the following drivers to consider overtaking. In addition, 95% of drivers would choose to do lane changing only if the rear spacing on the target lane is bigger than a 3-cell length (15 meters) and their speeds are higher than the following vehicles on the target lane [37,38]. As inspired by these findings, we have designed the ALC rules to supplement the PLC rules:…”

Section: Lane-changingmentioning

confidence: 99%

Characteristic Analysis of Mixed Traffic Flow of Regular and Autonomous Vehicles Using Cellular Automata

Liu

Guo

Taplin

et al. 2017

Journal of Advanced Transportation

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The technology of autonomous vehicles is expected to revolutionize the operation of road transport systems. The penetration rate of autonomous vehicles will be low at the early stage of their deployment. It is a challenge to explore the effects of autonomous vehicles and their penetration on heterogeneous traffic flow dynamics. This paper aims to investigate this issue. An improved cellular automaton was employed as the modeling platform for our study. In particular, two sets of rules for lane changing were designed to address mild and aggressive lane changing behavior. With extensive simulation studies, we obtained some promising results. First, the introduction of autonomous vehicles to road traffic could considerably improve traffic flow, particularly the road capacity and free-flow speed. And the level of improvement increases with the penetration rate. Second, the lane-changing frequency between neighboring lanes evolves with traffic density along a fundamental-diagram-like curve. Third, the impacts of autonomous vehicles on the collective traffic flow characteristics are mainly related to their smart maneuvers in lane changing and car following, and it seems that the car-following impact is more pronounced.

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“…A bilevel optimization model was proposed for the purpose of minimizing the total travel time of the affected network, involving a link closure and a proposed alternate route for travelers [30]. With a cellular automata model, a highway was divided into the normal area, merging area, and work zone, and the suitable merging length and the appropriate speed limit value were found to be key factors for managing work zone traffic operation [31]. A dynamic control model was used to optimize the signal operations of a new merging system, the lane-based signal merge (LBSM), which uses lane-based signals or variable signs to give drivers in different lanes the right-of-way to proceed through the open lane(s) in a work zone area [32].…”

Section: Predict and Evaluate Methods Of Highway Work Zone Impactmentioning

confidence: 99%

Evaluation of Two Improved Schemes at Non-Aligned Intersections Affected by a Work Zone with an Entropy Method

Shao

Luo

et al. 2020

Sustainability

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The impact of work zones on traffic is a common problem encountered in traffic management. The reconstruction of roads is inevitable, and it is necessary and urgent to reduce the impact of the work zone on the operation of traffic. There are many existing research results on the influence of highway work zones, including management strategies, traffic flow control strategies, and various corresponding model theories. There are also many research results on the impacts of urban road and subway construction on traffic operation, including construction efficiency, economic impact, and travel matrix. However, there are few studies concerning the choice of work zone location, and most previous studies have assumed that the work zone choice was scientific and reasonable. Therefore, it is reasonable to choose the location of the work zone and to assess whether there is room for improvement in the road form of the work zone, but this remains a research gap. Therefore, we studied a seven-lane main road T-intersection in Xi’an, China, and investigated a work zone located at this intersection that caused a road offset, leading to the non-aligned flow of main traffic. We designed two road improvement schemes and multiple transition schemes, used VISSIM software to evaluate the traffic operation of the two schemes, and used the entropy method to choose the suitability of the two schemes under different conditions. According to the results, in the best case, the driving time, delay, and number of stops are reduced by 44%, 66%, and 92%.

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Analysis of traffic congestion induced by the work zone

Cited by 53 publications

References 21 publications

An Assessment of Age and Gender Characteristics of Mixed Traffic with Autonomous and Manual Vehicles: A Cellular Automata Approach

An Assessment of Age and Gender Characteristics of Mixed Traffic with Autonomous and Manual Vehicles: A Cellular Automata Approach

Characteristic Analysis of Mixed Traffic Flow of Regular and Autonomous Vehicles Using Cellular Automata

Evaluation of Two Improved Schemes at Non-Aligned Intersections Affected by a Work Zone with an Entropy Method

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