A car-following model accounting for the driver’s attribution

Tang, Tie-Qiao; He, Jia; Yang, Shichun; Shang, Hongyan

doi:10.1016/j.physa.2014.07.035

Cited by 127 publications

(40 citation statements)

References 41 publications

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“…In region II (Fig. 4(b)), the 18 traffic is congested on the upstream section of lane 2 but still free in downstream one, here the left turning vehicles works as 19 a bottleneck for the forward movement because it slows down when it approaches cell T 1 (i.e. the turning point).…”

Section: Not Allowed P Tr1mentioning

confidence: 99%

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Phase diagram of a non-signalized T-shaped intersection

Echab

Lakouari

Ez‐Zahraouy

et al. 2016

Physica A: Statistical Mechanics and its Applications

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Section: Not Allowed P Tr1mentioning

confidence: 99%

“…For Rule 17 1 the regions are ( Fig. 9(a)): (I) free-free-free, (II) free-congested-congested, (III) congested-congested-congested, (IV) 18 gridlock-gridlock-gridlock, (V) free-congested-free. However, for Rule 2 ( Fig.…”

mentioning

confidence: 99%

Phase diagram of a non-signalized T-shaped intersection

Echab

Lakouari

Ez‐Zahraouy

et al. 2016

Physica A: Statistical Mechanics and its Applications

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“…In recent years, car-following theory has been rapidly developed and many models have been proposed to describe traffic phenomena and driving behavior. These new models focused on many different factors that influence car-following behavior, like the effects of time delay [6][7][8][9], multiple-vehicle in front [10][11][12][13], lane changing [14][15][16][17][18][19], the heavy vehicles [20][21][22][23], driver's behaviors [24][25][26][27][28][29][30][31][32][33], and some other factors in the literatures [34][35][36][37][38][39][40][41][42][43][44]. Nagatani [12] found that the car interaction before the next car ahead can stabilize the traffic flow.…”

Section: Introductionmentioning

confidence: 99%

An Improved Car‐Following Model Accounting for Impact of Strong Wind

Liu

Shi

2017

Mathematical Problems in Engineering

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In order to investigate the effect of strong wind on dynamic characteristic of traffic flow, an improved car-following model based on the full velocity difference model is developed in this paper. Wind force is introduced as the influence factor of car-following behavior. Among three components of wind force, lift force and side force are taken into account. The linear stability analysis is carried out and the stability condition of the newly developed model is derived. Numerical analysis is made to explore the effect of strong wind on spatial-time evolution of a small perturbation. The results show that the strong wind can significantly affect the stability of traffic flow. Driving safety in strong wind is also studied by comparing the lateral force under different wind speeds with the side friction of vehicles. Finally, the fuel consumption of vehicle in strong wind condition is explored and the results show that the fuel consumption decreased with the increase of wind speed.

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“…The speed is faster of the following vehicle, the more sensitive the acceleration/deceleration is. On this basis, Sheu [7], Yu [8], Liu [9], Tang [10,11], Yu [12], Zhu [13], Zheng [14], Saifuzzaman [15], Davoodi [16] calibrated parameters in the basic stimulation-reaction model from different perspectives to optimize the model. The study of these researchers helps the model greatly reflect the characteristic of car-following in actual traffic stream.…”

Section: Introductionmentioning

confidence: 99%

An extended car-following model considering the influence of bus

Shen

Qiu

et al. 2017

Teh. vjesn.

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Original scientific paper In order to describe car-following behaviour of traffic flow which is composed of buses and passenger cars on freeway, an extended car-following model is proposed for single lane traffic in this paper. The proposed model discriminates four types of car-bus following combination, car-following-bus, busfollowing-bus, bus-following-car and car-following-car. The four combinations are considered in terms of following distance, following speed and following acceleration/deceleration. The proposed methodology is demonstrated using data collected from the combination of microwave radar detector and roadside laser detector on Xuanwu Avenue in the main urban area of Nanjing. Besides, the field data is divided into two data sets, one used for the training of the model, and the other for evaluation purpose. Gazis model and Edie model, the two most extensively used car-following models, are calibrated against the same training data sets and used as a reference benchmark. Finally, the performance of the model, proposed by this paper, was compared with the two classic models based on the evaluation data sets. The results show that buses have different characteristics and manoeuvrability compared with passenger cars. With the influence of buses in the car-following process, it could lead to uneven distribution of traffic flow on the lanes and become the main reason for traffic highway capacity decline. The model, proposed in this paper, is more accurate and stable when predicting acceleration/deceleration of different vehicles during car-following. It has better superiority to describe the car-following behaviours under the influence of bus on freeway. Keywords: bus; car-following model; model calibration; stimulus-response process; traffic flow Prošireni model kolone vozila koji uzima u obzir utjecaj autobusaIzvorni znanstveni članak Kako bi se opisalo ponašanje prometa kolone vozila, koja se sastoji od autobusa i osobnih automobila na autocesti, u ovom članku je predložen prošireni model kolone vozila za promet u jednoj traci. Predloženi model razlikuje četiri vrste kombinacija kolona automobil-autobus, automobil-nakon-autobusa, autobus-nakon-autobusa, autobus-nakon-automobila i automobil-nakon-automobila. Četiri kombinacije uzimaju u obzir udaljenost, brzinu i ubrzavanje/usporavanje kolone. Predložena metodologija je prikazana uporabom podataka prikupljenih kombinacijom mikrovalnog radarskog detektora i cestovnog laserskog detektora na aveniji Xuanwu u glavnom urbanom području Nanjinga. Osim toga, podaci o terenu podijeljeni su u dva seta podataka, jedan se koristi za uvježbavanje modela, a drugi je za ocjenu. Gazis model i Edie model, dva najčešće korištena modela kolone vozila, kalibrirani su prema istim skupovima podataka za vježbu, a koriste se kao referentna vrijednost. Konačno, izvedba modela, predložena ovim radom, uspoređena je s dva klasična modela na temelju evaluacijskih skupova podataka. Rezultati pokazuju da autobusi imaju različite karakteristike i manevriranost u usporedbi s osobnim ...

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A car-following model accounting for the driver’s attribution

Cited by 127 publications

References 41 publications

Phase diagram of a non-signalized T-shaped intersection

Phase diagram of a non-signalized T-shaped intersection

An Improved Car‐Following Model Accounting for Impact of Strong Wind

An extended car-following model considering the influence of bus

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