Linear Acceleration Car-Following Model Development and Validation

Aycin, Murat F; Benekohal, Rahim F.

doi:10.3141/1644-02

Cited by 41 publications

(16 citation statements)

References 3 publications

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“…It emerged from the data analysis that car-following conditions occur, in accordance with Aycin and Benekohal's theory [31], for distances of less than 75 metres: in fact, for distances greater than that critical value, user behaviour does not prove to be in any way influenced by preceding vehicles in the same lane.…”

Section: Data Gatheringsupporting

confidence: 68%

Analysis of user behaviour at a roundabout under car-following conditions

Guido¹,

Vitale²

2006

WIT Transactions on the Built Environment, Vol 89

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Roundabout intersection planning in urban areas has spread remarkably, especially in Europe. Compared with the conventional intersection layout, this system is suitable for improving road safety and the urban landscape. In the literature there are many studies regarding car-following models; the innovative characteristic of this research is the analysis of user behaviour at a roundabout. In fact, the main aim is to develop a car-following model allowing the definition of flow conditions under high vehicular densities at this type of intersection. The car-following model consists of a stimulus-response function; its calibration and validation has been made by the analysis of many parameters influencing traffic flow. These parameters have been observed with a video data acquirement technique in order to minimize the distance between the observed variables and the estimated one. Preliminary results show a strong correlation between the observed behavioural parameters and the output of the model, forecasting vehicular trajectories at a roundabout. The estimation of traffic parameters in car-following condition is useful to define the geometry of the intersection (length of weaving area, number of lanes, diameter, number of entries) and to forecast conditions that could lead to behavioural anomalies connected with a reduced safety level for users.

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Section: Data Gatheringsupporting

confidence: 68%

Analysis of user behaviour at a roundabout under car-following conditions

Guido¹,

Vitale²

2006

WIT Transactions on the Built Environment, Vol 89

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“…Bham argued that the follower accelerates in case when the space gap is greater than three times their current speed [21]. 1 s equivalent to time step and reaction time or "lag" for all the vehicles is suggested by Bham and Aycin [21,42]. In this study, the model parameter values are s min = 2 m, s safe = 3 × v t+1 (m), timestep = 1 s. The design speed is set to 60 km/h.…”

Section: Model Calibrationmentioning

confidence: 98%

Multi-agent systems for simulating traffic behaviors

Dai

2009

Chin. Sci. Bull.

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Multi-agent systems allow the simulation of complex phenomena that cannot be easily described analytically. As an efficient tool, the agent-oriented traffic models have emerged to investigate vehicular traffic behaviors. In this article, a new agent-based traffic simulation model is proposed for solving the traffic simulation problems. A vehicle with the driver is represented as a composite autonomous agent in this model. Different from the classical car-following principles, vehicle-agent moving approaches are proposed instead of particle-hopping techniques. This model defines reasonable acceleration and deceleration rates at any certain condition. In this simulation, this can offer a natural, even cognitive way to follow the leader and switch lane. The simulation results have verified that this model has achieved more realistic results without loss of accuracy than those obtained from the cellular automata traffic models. This model can provide better simulation performance than the traditional vehicle-following models which are used to investigate the nonequilibrium traffic flow. A comparison of the real flow with the simulated freeway flow and lane capacity highlights the validness of this model. microscopic traffic model, vehicle-following model, multi-agent, cellular automata, acceleration Citation:Dai J C, Li X. Multi-agent systems for simulating traffic behaviors.Microscopic vehicular traffic models focus on the study of the interaction between vehicles and investigate the synthesis characteristics of complex traffic phenomena. At present, there are several different types of traffic simulation models: vehicle-following (VF) models, Cellular Automata (CA) models and the multi-agent (MA) models. Vehicle-following models are based on Newtonian dynamics. In Newtonian mechanics, the acceleration may be regarded as the response of the particle to the stimulus it receives in the form of force which includes both the external force as well as those arising from its interaction with all the other particles in the system [1]. Pipes exploited the Follow-the-leader model in the 1950s [2]. After his heels, Gazis [3,4], Newell [5,6], Edie [7], Gipps [8], Bando [9], Treiber [10] proposed new VF models. Since the vehicular traffic is a nonequilibrium and complex system, classical vehicle-following models are not adequate to capture the essential features of lane changing, overtaking, speed limit and unanticipated parking. While particle hopping approaches usually formulated using CA are powerful techniques to investigate microscopic traffic. CA models have further been studied in recent decades [1,11-20], but CA models do not incorporate realistic driver and vehicular behavior. Vehicles are modeled as particles having unrealistic erratic acceleration and deceleration rates. And vehicles accelerate independent of their velocity and have speed jumps of about 27 km/h in 1 s [11]. Vehicles tend to change speed abruptly; they can come to a stop from a maximum speed of 135 km/h in 1 s [11]. In STCA (Stochastic Traffic Cellula...

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“…Some past researchers showed that a wide range of factors such as drivers' behavior, traffic condition, road condition, roadway design, state law and regulation, and even personality had effects on vehicle headway (Ayres et al 2001;Aycin and Benekohal 1998;Brackstone and McDonald 1999;Hogema 1999;Brackstone 2003;Rajalin, Hassel, and Summala 1997). Based on these factors, various car following models were developed to describe the interaction between individual vehicles or the whole traffic dynamic.…”

Section: Tailgating Issuesmentioning

confidence: 99%