Traffic Dynamics: Studies in Car Following

Chandler, Robert E.; Herman, Robert K; Montroll, Elliott W.

doi:10.1287/opre.6.2.165

Cited by 1,227 publications

(600 citation statements)

References 2 publications

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“…It shows the following vehicle speeds up or down, or just keeps an even speed under the influence of the leading vehicle. Gazis et al believed following stimulation sensitivity of different vehicles always changes and is not only concerned with space headway but also with instantaneous speed and speed difference [4]. They improved the original car-following model and derived…”

Section: Model Buildingmentioning

confidence: 99%

“…Since Pipes et al firstly put forward the carfollowing model based on safety distance in 1953 [3], many researchers have studied the car-following model from different perspectives. In 1958, Gazis et al pointed out that the sensibility of vehicle acceleration variation in car-following behavior was related not only to the spacing between the vehicles, but also to the speed of the following vehicle [4]. They proposed a stimulationreaction car-following model on the basis of Chandler Model.…”

Section: Introductionmentioning

confidence: 99%

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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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Section: Model Buildingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An extended car-following model considering the influence of bus

Shen

Qiu

et al. 2017

Teh. vjesn.

View full text Add to dashboard Cite

show abstract

“…From the time series of the measured vehicle positions one can determine the vehicle velocities and accelerations. These are all the data that have to be used in (1) to verify the dynamic traffic flow model [4]. It should be mentioned at this point, however, that the interrupted traffic flow (dynamic interaction between two vehicles and obstacles) was empirically investigated in uninterrupted conditions.…”

Section: Fundamentals Of Microscopic Traffic Modelsmentioning

confidence: 99%

Validation of Microscopic Traffic Models Based on GPS Precise Measurement of Vehicle Dynamics

Apeltauer¹,

Macur²,

Holcner³

et al. 1970

PROMET

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“…In principle, traffic flow modelling can be categorized into three types: microscopic models, mesoscopic models and macroscopic models. The microscopic approach describes traffic flow at a high level of detail such as the movement of individual vehicles (Chadler, Herman, and Montroll 1958;Helly 1959;Bando et al 1995Bando et al , 1998Treiber, Hennecke, and Helbing 2000;Jiang, Wu, and Zhu 2001;Helbing 2007, 2010;Laval, Toth, and Zhou 2014), whereas the macroscopic approach represents traffic flow at a low level of detail via aggregate traffic variables such as flow, mean speed and density (Treiber, Hennecke, and Helbing 1999;Katiyar 2005, 2006a;Zhang and Wong 2006;Boel and Mihaylova 2006;Laval and Leclercq 2010;Zhang, Wong, and Dai 2011;Helbing et al 2001;Ngoduy 2012a;Bogdanova et al 2015). The mesoscopic approach, on the other hand, describes traffic flow at a level of detail between microscopic and macroscopic approach through probabilistic terms.…”

Section: Introductionmentioning

confidence: 99%

Multi anticipative bidirectional macroscopic traffic model considering cooperative driving strategy

Ngoduy

Jia

2016

Transportmetrica B: Transport Dynamics

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Recent development of information and communication technologies (ICT) has enabled vehicles to timely communicate with others through wireless technologies, which will form future (intelligent) traffic systems (ITS) consisting of so-called connected vehicles. Cooperative driving with the connected vehicles is regarded as a promising driving pattern to significantly improve transportation efficiency and traffic safety. Such cooperative driving has motivated many studies to model the dynamics of traffic flow under multi anticipative driving strategy (i.e. drivers react to many leading vehicles) or bidirectional strategy (i.e. drivers react to both (single) leading and following vehicles). In the vast literature of traffic flow theory, there are continuum models considering multiple forward anticipative strategy, where the driver reacts to many leaders. To the best of our knowledge, few study effort has been undertaken to include bidirectional driving strategy, where the driver reacts to both direct leader and direct follower, in the continuum traffic flow models. Moreover, the current bidirectional continuum traffic flow model still suffers some drawbacks: considers the behaviour of only a single leading vehicle in the forward looking strategy and neglects the impact of the forward space headway (e.g. the distance between two consecutive vehicles) sensitivity parameter on the (linear) stability of the model. This paper aims to derive a continuum traffic model considering both multiple forward and backward driving strategy. It is shown that the derived model is a generalized version of a current continuum model for ITS and can improve important properties of such bidirectional (continuum) model.

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Traffic Dynamics: Studies in Car Following

Cited by 1,227 publications

References 2 publications

An extended car-following model considering the influence of bus

An extended car-following model considering the influence of bus

Validation of Microscopic Traffic Models Based on GPS Precise Measurement of Vehicle Dynamics

Multi anticipative bidirectional macroscopic traffic model considering cooperative driving strategy

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