Safety impact of right-turn waiting area at signalised junctions conditioned on driver’s decision-making based on fuzzy cellular automata

Gao, Yidan; Zhou, Qingji; Chai, Chunlei; Wong, Yiik Diew

doi:10.1016/j.aap.2018.12.008

Cited by 11 publications

(4 citation statements)

References 26 publications

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“…CA models are used for urban growth and traffic analysis simulation due to their relative simplicity and intuitiveness, and particularly due to the provision to incorporate spatial and temporal dimensions in computer simulations. These models are popular, as they provide flexible traffic simulations for individual vehicle movement analysis [29]. The fast performance is due to their low accuracy on a microscopic scale.…”

Section: Cellular Automata Models For Traffic Flow Simulationmentioning

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: Cellular Automata Models For Traffic Flow Simulationmentioning

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

“…In the literature, many of the models developed so far have utilized homogenous one-lane-based traffic (7,12,21). The first basic grid block model of homogenous onelane traffic was developed by Biham et al (21).…”

Section: Heterogeneous Traffic Modelsmentioning

confidence: 99%

“…Most of the simulation models developed so far are based on homogenous traffic without considering seepage, heterogeneity, and non-lane-based behavior, and so forth (7)(8)(9)(10)(11)(12). The present study aims to address these gaps by employing a cellular automata (CA) simulation model to capture more realistic traffic behavior.…”

mentioning

confidence: 99%

Simulation of Signalized Intersection with Non-Lane-Based Heterogeneous Traffic Conditions Using Cellular Automata

Singh,

Ramachandra Rao

2023

Transportation Research Record: Journal of the Transportation R

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Intersections affect the maneuvering and driving behavior of vehicles. The present study attempts to simulate an isolated signalized intersection with the dimensions obtained through the influence zone of intersections. This model includes several unexplored traffic characteristics observed at the intersection, such as non-lane-based heterogeneity and seepage behavior. The model was calibrated and validated with the field data collected in New Delhi, India. Several measures of performance, such as GEH statistics, Theil’s coefficient, root mean square error, and so forth, were used to validate and benchmark the simulation model. After calibration and validation, the model was used to find delays. The delays obtained from the model, several manuals, and the field were compared and found to be close to the field delays. Further, delays obtained from Indonesian and Canadian manuals were comparatively closer to the delays obtained from the field, whereas delays obtained from the Indian Highway Capacity Manual (2017) and U.S. Highway Capacity Manual (2010) are overestimated. The model presented can be used to benchmark the performance of signalized intersections under a variety of traffic and environmental conditions.

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“…This suggest that bicycle behaviour should be controlled at the intersectionsno turning at intersection[74]1✗✗✗✗open✓A CA rule was formed by accounting the responses of speeds, brake light and the conflicts of traffic flow at the intersections of internet of vehicles (IoV) and this rule was named as CE‐NS. CA rules for acceleration, deceleration and conflicts were modifiedonly direction change[75]1✗✗✗✗open✓calibrated and validated with fields data, decision‐making of in driver was simulated…”

Section: Literature Review Of the Ca Model At The Intersectionmentioning

confidence: 99%

Cellular automata models for signalised and unsignalised intersections with special attention to mixed traffic flow: a review

Singh

Rao

2020

IET intell. transp. syst

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Safety impact of right-turn waiting area at signalised junctions conditioned on driver’s decision-making based on fuzzy cellular automata

Cited by 11 publications

References 26 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

Simulation of Signalized Intersection with Non-Lane-Based Heterogeneous Traffic Conditions Using Cellular Automata

Cellular automata models for signalised and unsignalised intersections with special attention to mixed traffic flow: a review

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