Cunning and Curated: Window at the University of Auckland, New Zealand

Bennett, Lucinda; Woodward, Robin

doi:10.1080/21502552.2017.1288540

Cited by 1 publication

(1 citation statement)

References 5 publications

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“…After that, the time gap (in seconds) from the rear of the preceding vehicle to the front of the follower is utilized to detect \close following" behaviors from NGSIM data, and the smaller time gap means the closer car following behavior. Based on the characteristics of NGSIM data, a value of 3 s is chosen as the critical time gap for \close following" behaviors, which is also used by Bennett 29 and Sayer et al 30 Then, the extracted vehicle trajectory data with the characteristic of \close following" can be further separated into two di®erent groups according to the A new car following model from the perspective of visual imaging 1550090-5 vehicle type of the leader, i.e. the car or the truck.…”

Section: Field Data Preprocessingmentioning

confidence: 99%

A new car following model from the perspective of visual imaging

Zheng

2015

Int. J. Mod. Phys. C

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The paper proposes a car following model from the perspective of visual imaging (VIM), where the visual imaging size of the preceding vehicle on a driver's retina is considered as the stimuli and determines the driving behaviors. NGSIM trajectory data are applied to calibrate and validate the VIM under two scenarios, i.e. following the car and following the truck, whosē tting performance outperforms that of visual angle car following model (VAM). Through linear stability analyses for VIM, it can be drawn that the asymmetry in tra±c°ow is preserved; the larger vehicle width, vehicle length and vehicle apparent size all bene¯t enlarging the tra±c°ow stable region; the tra±c°ow unstable region when following the car tends to fall in the relatively small distance headway range compared with that when following the truck. After that, numerical experiments demonstrate that the visual imaging information applied in VIM is more contributive to the tra±c°ow stability than the visual angle information in VAM when following the truck in the relatively large distance headway or involving the driver's perception threshold, i.e. Weber ratio; introducing Weber ratio would break the originally stable tra±c°o w or deteriorate the tra±c°uctuation, which however can be alleviated by increasing drivers' sensitivity, e.g., decreasing Weber ratio. Finally, VIM is veri¯ed to be able to satisfy the consistency criteria well from the theoretical aspect.

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Section: Field Data Preprocessingmentioning

confidence: 99%

A new car following model from the perspective of visual imaging

Zheng

2015

Int. J. Mod. Phys. C

View full text Add to dashboard Cite

show abstract

Cunning and Curated: Window at the University of Auckland, New Zealand

Cited by 1 publication

References 5 publications

A new car following model from the perspective of visual imaging

A new car following model from the perspective of visual imaging

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