Study of traffic flow characteristics using different vehicle-following models under mixed traffic conditions
04 Mar 2018-Transportation Letters: The International Journal of Transportation Research (Taylor & Francis)-Vol. 10, Iss: 2, pp 92-103
TL;DR: The performance of different vehicle-following models was evaluated based on different Measure of Effectiveness (MoE) using field data collected from a four-lane divided urban arterial road in Chennai city and the results showed the promise of some measures based on vehicle class.
Abstract: To understand the congestion problem and the occurrence of bottlenecks and to formulate solutions for it, a thorough study of vehicle-to-vehicle interactions is necessary. Car-following models replicate the behavior of a driver following another vehicle. These models are widely used in the development of traffic simulation models, and in analysis of safety and capacity. In India, traffic on roads is mixed in nature with wide variations in physical dimensions and other vehicular and traffic characteristics with loose lane discipline. In mixed traffic conditions, leader-follower vehicle types are not only car–car cases but also there are different combinations of vehicles (e.g. car-two wheeler, two wheeler-auto rickshaw, and heavy vehicle-two wheeler). The present study focuses on evaluation of different vehicle-following models under mixed traffic conditions. The car-following models such as Gipps, Intelligent Driver Model (IDM), Krauss Model and Das and Asundi were selected for this study. These m...
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TL;DR: Comparison of two-dimensional performance indicators with a baseline model and generative adversarial networks indicate the effectiveness and suitability of the developed motion planning algorithm in the mixed traffic environment.
Abstract: © The Institution of Engineering and Technology 2020. Classical artificial potential approach of motion planning is extended for emulating human driving behaviour in two dimensions. Different stimulus parameters including type of ego-vehicle, type of obstacles, relative velocity, relative acceleration, and lane offset are used. All the surrounding vehicles are considered to influence drivers' decisions. No emphasis is laid on vehicle control; instead, an ego vehicle is assumed to reach the desired state. The study is on human-like driving behaviour modelling. The developed motion planning algorithm formulates repulsive and attractive potentials in a data-driven way in contrast to the classical arbitrary formulation. Interaction between the stimulus parameters is explicitly considered by using multivariate cumulative distribution functions. Comparison of two-dimensional (lateral and longitudinal) performance indicators with a baseline model and generative adversarial networks indicate the effectiveness and suitability of the developed motion planning algorithm in the mixed traffic environment.
3 citations
06 Sep 2020
TL;DR: The results indicate the significant differences in PCU values due to the presence of curbside bus stop with varying traffic volume and composition.
Abstract: Representation of traffic in terms of Passenger Car Unit (PCU) is imperative to estimate capacity in disordered traffic. Many studies have been conducted on investigation of impacts of traffic and ...
2 citations
Cites background from "Study of traffic flow characteristi..."
...(3) Vehicle Movement: In disordered traffic, subject vehicle follows the leader closely and choose its speed and safe longitudinal gap to avoid rear-end collision (Asaithambi et al. 2018)....
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TL;DR: This article explains many scenarios and scenario construction techniques utilized in the process of self-driving car testing, with an emphasis on the map generating method and the dynamic scenario production method in the test scenarios.
Abstract: The advancement of autonomous driving technology has had a significant impact on both transportation networks and people’s lives. Connected and automated vehicles as well as the surrounding driving environment are increasingly exchanging information. The traditional open road test or closed field test, which has large costs, lengthy durations, and few diverse test scenarios, cannot satisfy the autonomous driving system’s need for reliable and safe testing. Functional testing is the emphasis of the test since features such as frontal collision and traffic sign warning influence driving safety. As a result, simulation testing will undoubtedly emerge as a new technique for unmanned vehicle testing. A crucial aspect of simulation testing is the creation of test scenarios. With an emphasis on the map generating method and the dynamic scenario production method in the test scenarios, this article explains many scenarios and scenario construction techniques utilized in the process of self-driving car testing. A thorough analysis of the state of relevant research is conducted, and approaches for creating common scenarios as well as brand-new methods based on machine learning are emphasized.
2 citations
TL;DR: In this article , a continuous wavelet transformation with oblique cumulative arrival and oblique occupancy time plots is proposed for estimating the fundamental relationships between traffic flow variables using empirical data. But, their relationships in mixed traffic are challenging to model due to the continuously changing vehicle composition.
Abstract: A thorough understanding of the fundamental relation of traffic flow variables is critical for the efficient operation of traffic systems. However, their relationships in mixed traffic are challenging to model due to the continuously changing vehicle composition. This paper proposes a composition-based approach for estimating the fundamental relationships between traffic flow variables using empirical data. The methodology seeks to eliminate the difficulties in class-specific ss identification by introducing a continuous wavelet transformation with oblique cumulative arrival and oblique occupancy time plots. We used machine learning (ML) algorithms to delineate regimes and showed the fundamental diagrams for a given location that has a composition-invariant free-flow branch but has distinct composition-specific branches in congestion. Also, it was observed that the congested regime (CR) has a wide scatter indicating possible stochastic inter-class interactions for varying vehicular composition. We proposed a distance optimization method to re-cluster the CR data and found that the proposed method improves the fit with the empirical observations. The inter-class interactions result illustrates that the heavy vehicles will dominate the high-speed vehicles with the increase of AO. It is found that beyond a critical level of AO in congestion, all vehicle class travel at the same speed. Finally, it is found that validation with different datasets shows that the proposed methodology is robust in estimating fundamental diagrams under mixed traffic conditions.
1 citations
TL;DR: This study uses microscopic simulation model, which contains abundant autonomous parameters to illustrate the features of traffic flow, behavior of drivers and traffic regulatory processes, to get a realistic capacity estimate of different multilane highways in Indian conditions.
Abstract: In case of a non-lane based heterogeneous traffic flow, the vehicle driver’s behavior becomes one of the major considering aspects for proper traffic maneuverability. In the present study, microscopic simulation model has been used, as it contains abundant autonomous parameters to illustrate the features of traffic flow, behavior of drivers and traffic regulatory processes. The present traffic simulation model follows two modified models based on vehicle following theories and behaviors as modified by Wiedemann. A driver in the micro-simulation model considers the preceding vehicle as well as neighboring lane vehicles in a traffic stream. The methodological description of a vehicle technically, behavior and interdependency of a driver and a vehicle as a unit is attributes of a driver and his or her vehicle in a traffic stream. Thus, hysteresis plots of relative speed against relative distance are made for aggregated leader and follower vehicles of each vehicle type based on follower vehicular category to get the calibrated coefficient of correlation parameters (CC). A new simulation model with calibrated CC parameters is made to get a realistic capacity estimate of different multilane highways in Indian conditions.
1 citations
References
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TL;DR: It is shown that the results of the microscopic model can be understood by formulating the theoretical phase diagram for bottlenecks in a more general way, and a local drop of the road capacity induced by parameter variations has essentially the same effect as an on-ramp.
Abstract: We present data from several German freeways showing different kinds of congested traffic forming near road inhomogeneities, specifically lane closings, intersections, or uphill gradients. The states are localized or extended, homogeneous or oscillating. Combined states are observed as well, like the coexistence of moving localized clusters and clusters pinned at road inhomogeneities, or regions of oscillating congested traffic upstream of nearly homogeneous congested traffic. The experimental findings are consistent with a recently proposed theoretical phase diagram for traffic near on-ramps [D. Helbing, A. Hennecke, and M. Treiber, Phys. Rev. Lett. 82, 4360 (1999)]. We simulate these situations with a continuous microscopic single-lane model, the ``intelligent driver model,'' using empirical boundary conditions. All observations, including the coexistence of states, are qualitatively reproduced by describing inhomogeneities with local variations of one model parameter. We show that the results of the microscopic model can be understood by formulating the theoretical phase diagram for bottlenecks in a more general way. In particular, a local drop of the road capacity induced by parameter variations has essentially the same effect as an on-ramp.
3,432 citations
"Study of traffic flow characteristi..." refers background in this paper
...In mixed traffic, when vehicles are progressing in urban networks with congested traffic, they follow the leader closely and select the following speed and following distance according to the principle of collision avoidance (Gipps 1981; Krauss 1997; Treiber, Hennecke, and Helbing 2000)....
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...The safety distance models (Gipps 1981; Krauss 1997; Treiber, Hennecke, and Helbing 2000) assume that the following vehicle will maintain a safe distance with the vehicle in front and will select its speed to ensure that the vehicle can stop safely to avoid a rear-end collision....
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TL;DR: In this model, the legal velocity function is introduced, which is a function of the headway of the preceding vehicle, and the evolution of traffic congestion is observed with the development of time.
Abstract: We present a dynamical model of traffic congestion based on the equation of motion of each vehicle. In this model, the legal velocity function is introduced, which is a function of the headway of the preceding vehicle. We investigate this model with both analytic and numerical methods. The stability of traffic flow is analyzed, and the evolution of traffic congestion is observed with the development of time.
2,505 citations
TL;DR: A new model is constructed for the response of the following vehicle based on the assumption that each driver sets limits to his desired braking and acceleration rates and it is shown that when realistic values are assigned to the parameters in a simulation, the model reproduces the characteristics of real traffic flow.
Abstract: The ability to predict the response of a vehicle in a stream of traffic to the behaviour of its predecessor is important in estimating what effect changes to the driving environment will have on traffic flow. Various proposed to explain this behaviour have different strengths and weaknesses. The paper constructs a new model for the response of the following vehicle based on the assumption that each driver sets limits to his desired braking and acceleration rates. The parameters in the model correspond directly to obvious characteristics of driver behaviour and the paper goes on to show that when realistic values are assigned to the parameters in a simulation, the model reproduces the characteristics of real traffic flow.
1,925 citations
"Study of traffic flow characteristi..." refers background in this paper
...In mixed traffic, when vehicles are progressing in urban networks with congested traffic, they follow the leader closely and select the following speed and following distance according to the principle of collision avoidance (Gipps 1981; Krauss 1997; Treiber, Hennecke, and Helbing 2000)....
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...The safety distance models (Gipps 1981; Krauss 1997; Treiber, Hennecke, and Helbing 2000) assume that the following vehicle will maintain a safe distance with the vehicle in front and will select its speed to ensure that the vehicle can stop safely to avoid a rear-end collision....
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TL;DR: A variety of nonlinear follow-the-leader models of traffic flow are discussed in this article in the light of available observational and experimental data, with emphasis placed on steady-state flow equations.
Abstract: A variety of nonlinear follow-the-leader models of traffic flow are discussed in the light of available observational and experimental data. Emphasis is placed on steady-state flow equations. Some trends regarding the advantages of certain follow-the-leader functionals over others are established. However, it is found from extensive correlation studies that more data are needed before one can establish the unequivocal superiority of one particular model. A discussion is given of some ideas concerning the possible reasons for the existence of a bimodal flow versus concentration curve especially for multilane highways.
1,429 citations
"Study of traffic flow characteristi..." refers background in this paper
...…as a stimulus-response concept based on the assumption that the driver of the following vehicle accurately perceives and reacts appropriately to the spacing and speed differential between the following and the lead vehicles (Chandler, Herman, and Montroll 1958; Gazis, Herman, and Rothery 1961)....
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TL;DR: In this paper, the acceleration at time t of a car attempting to follow a leader is proportional to the difference in velocity of the two cars at a time t-Δ, Δ being about 1.5 sec and the proportionality constant being about 0.37 sec-1.
Abstract: The manner in which vehicles follow each other on a highway without passing and the propagation disturbances down a line of vehicles has been investigated. Experimental data is presented which indicates that the acceleration at time t of a car which is attempting to follow a leader is proportional to the difference in velocity of the two cars at a time t-Δ, Δ being about 1.5 sec and the proportionality constant being about 0.37 sec-1. It is shown theoretically that the motion of a long line of vehicles becomes unstable when the product of the lag time and the proportionality constant exceeds one-half. The experimental data implies that driving is done on the verge of instability. A variety of other laws of following is analyzed theoretically.
1,351 citations
"Study of traffic flow characteristi..." refers background in this paper
...…as a stimulus-response concept based on the assumption that the driver of the following vehicle accurately perceives and reacts appropriately to the spacing and speed differential between the following and the lead vehicles (Chandler, Herman, and Montroll 1958; Gazis, Herman, and Rothery 1961)....
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