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: In this article, a review of commercially existing microscopic traffic simulation frameworks built to evaluate real-world traffic scenario is presented, where the significant contributions made by 2D models in evaluating the lateral and longitudinal vehicle behaviour simultaneously.
Abstract: The area of traffic flow modelling and analysis that bridges civil engineering, computer science, and mathematics has gained significant momentum in the urban areas due to increasing vehicular population causing traffic congestion and accidents. Notably, the existence of mixed traffic conditions has been proven to be a significant contributor to road accidents and congestion. The interaction of vehicles takes place in both lateral and longitudinal directions, giving rise to a two-dimensional (2D) traffic behaviour. This behaviour contradicts with the traditional car-following (CF) or one-dimensional (1D) lane-based traffic flow. Existing one-dimensional CF models did the inclusion of lane changing and overtaking behaviour of the mixed traffic stream with specific alterations. However, these parameters cannot describe the continuous lateral manoeuvre of mixed traffic flow. This review focuses on all the significant contributions made by 2D models in evaluating the lateral and longitudinal vehicle behaviour simultaneously. The accommodation of vehicle heterogeneity into the car-following models (homogeneous traffic models) is discussed in detail, along with their shortcomings and research gaps. Also, the review of commercially existing microscopic traffic simulation frameworks built to evaluate real-world traffic scenario are presented. This review identified various vehicle parameters adopted by existing CF models and whether the current 2D traffic models developed from CF models effectively captured the vehicle behaviour in mixed traffic conditions. Findings of this study are outlined at the end.
32 citations
Cites methods from "Study of traffic flow characteristi..."
...[84] evaluated the performance of carfollowing models such as Gipps, IDM, Krauss Model, Das, and Asundi based on the measure of effectiveness (MoE), which utilises field data obtained from heterogeneous traffic conditions....
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TL;DR: In this paper, the authors investigated the performances of two emission models for estimating emissions from passenger cars and auto-rickshaws of different mileages, moving with a traffic fleet during these events.
29 citations
TL;DR: To test the car-following model’s efficacy in replicating the following behavior, simulation runs were performed using VISSIM 9.0 and it was well-established that psychophysical models (Wiedemann), multi-regime (Gipps), and IDM car- following models resemble Indian traffic behavior reasonably well, whereas single- Regime car- Following model, optimal velocity model fails in replicates the actual following-behavior.
22 citations
TL;DR: It is verified that the proposed model, in addition to macroscopic patterns, can also accurately predict complex maneuvers, such as overtaking, sideways movements and avoiding collisions with slower moving vehicles.
Abstract: In this paper, a new model is introduced for traffic on broad roads, where the drivers do not follow lane-discipline. For both longitudinal and lateral motions, the driver reactions are assumed to be influenced by possibly a number of vehicles, obstacles, and unmodeled entities in visibility cones to the front and to the sides of each vehicle. The network of influences and the resultant interaction is modeled by “influence graphs.” In congested traffic situations, it is assumed that the influence structure is time invariant and all drivers are forced to behave homogeneously. Then, the collection converges to a layered formation with fixed intervehicle distances. In sparse and heterogeneous traffic, the velocity and intervehicle separations in the set of modeled vehicles, though can oscillate continuously, are uniformly bounded. These model-based predictions are verified experimentally. Videos of typical traffic on a sample road in Mumbai city, India, are recorded. Detailed motion information of groups of cars is extracted through image processing techniques. The proposed model is initialized with the extracted data and the computed trajectories are compared with the actual ones calculated from the images. It is verified that the proposed model, in addition to macroscopic patterns, can also accurately predict complex maneuvers, such as overtaking, sideways movements and avoiding collisions with slower moving vehicles.
21 citations
Cites result from "Study of traffic flow characteristi..."
...Similar models, in the absence of more realistic theory, have been used to model Indian traffic [32], [33] which, however, does not obey lane discipline....
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01 Jun 2018
TL;DR: This paper aims to investigate the behavior of the immediate follower during the lane-change of its leader vehicle with a novel and adaptive neuro-fuzzy model that considers human driving factors and reveals that the proposed model can describe anticipation and evaluation behavior with smaller errors.
Abstract: Nowadays, vehicles are the most important means of transportation in our daily lifes. During the last few decades, many studies have been carried out in the field of intelligent vehicles and signif...
19 citations
References
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TL;DR: The preliminary analysis indicated that factors such as composition, intraclass variability, and lane discipline had a statistically significant effect on stream speed, and the results showed the promise of some measures based on vehicle class, namely, the exclusion of autorickshaws or autorickhaws and heavy vehicles.
Abstract: Mixed traffic in the cities of many developing countries is characterized by a lack of lane discipline, varying compositions of constituent vehicle types, and significant intraclass variability in static and dynamic characteristics. However, the influence of these factors on traffic flow parameters is not well understood. This study addressed the influence of lane discipline, intraclass variability, and composition on traffic flow characteristics under heterogeneous traffic conditions in Chennai, India. A microscopic traffic simulation model was calibrated and validated with field data from a four-lane divided urban arterial road in Chennai. The preliminary analysis indicated that factors such as composition, intraclass variability, and lane discipline had a statistically significant effect on stream speed. Speed-flow and speed-density relationships were developed on the basis of simulation results. These results showed a clear influence of lack of lane discipline, variability, and composition on stream s...
24 citations
"Study of traffic flow characteristi..." refers methods in this paper
...Asaithambi et al. (2012) studied the influence of lane discipline, intra-class variability, and composition on traffic flow characteristics under heterogeneous traffic conditions using simulation model and evaluated a range of traffic control measures based on vehicle type and lane....
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...For this purpose, a microscopic traffic simulation model for mixed traffic conditions developed by Asaithambi et al. (2012) is adapted by incorporating various types of vehicle-following models under mixed traffic conditions....
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TL;DR: In this article, the performance of major car-following models is evaluated using microscopic vehicle trajectory when the lead and the following vehicle types are different, and it is shown that the following behavior of small sized vehicles is easily reproduced by the models, compared to large vehicle types.
Abstract: Car-following models replicate the behavior of a driver following another vehicle and are widely used in the development of traffic simulation tools. In this study, the performance of major car-following models is evaluated using microscopic vehicle trajectory when the lead and the following vehicle-types are different. Vehicles equipped with Global Positioning System (GPS) receivers were used to collect car-following data from two urban arterials of India. Analysis of car-following data indicates the existence of distinct behavior for each vehicle-type combination. Among the vehicle-type combinations studied, the following behavior of small sized vehicles is easily reproduced by the models, compared to large vehicle-types. Similarly, among the models, the Gipps and Krauss models are able to predict following behavior better than the rest followed by the MITSIM model.
18 citations
"Study of traffic flow characteristi..." refers background in this paper
...Mathew and Ravishankar (2011) studied different car-following models (General Motors, Gipps, Krauss, IDM, Wiedmann, optimum velocity) in mixed traffic conditions....
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01 Nov 2006
TL;DR: An alternative measure of density, termed as area occupancy, as a measure of impedance to estimate the passenger car equivalents (PCE) values is presented, which will be helpful in analyzing traffic flow patterns and in capacity analysis.
Abstract: The purpose of this paper is to present an alternative measure of density, termed as area occupancy, as a measure of impedance to estimate the passenger car equivalents (PCE) values A simulation technique is used to estimate PCE values under different traffic regimes These values will be helpful in analyzing traffic flow patterns and in capacity analysis In studying heterogeneous traffic, PCE play a significant role in converting the mixed traffic flow into equivalent hypothetical homogeneous traffic that consists of passenger cars only As can be seen in the literature there are different measures of impedance (speed, density, vehicle-hours etc) based on which PCE values are calculated for different types of vehicles Since vehicle-hours and speed are functions of vehicle density, PCE values invariably depend on density Measuring these values is difficult under heterogeneous traffic conditions Due to these reasons using the density value as a measure of impedance in calculating PCE values under mixed traffic conditions may lead to erroneous results
18 citations
"Study of traffic flow characteristi..." refers methods in this paper
...Mallikarjuna and Rao (2006) developed a Cellular Automata (CA) based simulation model for mixed traffic is used to estimate the PCE values....
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01 Jan 2011
TL;DR: Comparison of headway distributions across two facility types is made and it is observed that most of the pairs, particularly two wheeler, Auto rickshaw, pairs fit in same distribution irrespective of facility types.
Abstract: Time headway between vehicles is an important traffic flow characteristic affecting safety, level of service, driver behavior, and capacity of a transportation system. However, almost all the reported research on headway is focused on mixed vehicular flow without considering the difference in headway with respect to different lead and lag vehicle types. In this paper, different pairs of time headway based on different combinations of leading vehicle and following vehicle (Ex: Two wheeler-Two wheeler, Two wheeler-car, Two wheeler-Auto Rickshaw , etc.) are studied under heterogeneous traffic conditions. Monte-Carlo simulation procedure to simulate traffic stream headways based on the classwise distributions is discussed. The study of effect of lane and non lane discipline on headways shows that non-lane based discipline is appropriate for heterogeneous traffic conditions. Comparison of headway distributions across two facility types (two and three lane) is made and observed that most of the pairs, particularly two wheeler, Auto rickshaw, pairs fit in same distribution irrespective of facility types. The results of the paper identify difference of the vehicle-type-specific headway distribution, which can be used as a reference for practical applications, especially for improving microscopic traffic simulation models. They can also give insight on devising better planning and management of traffic and there by lead to better tools for traffic engineers and managers.
9 citations
"Study of traffic flow characteristi..." refers background in this paper
...Vehicles are generated at the starting point of the simulation road stretch based on time gap distribution for different categories based on lead-lag vehicle types (Kanagaraj et al. 2011)....
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TL;DR: A simple, explicit model, which uses two parameters derived from simple measurements of real-time traffic data, allows for a prediction of the approximate relationship for congested as well as uncongested vehicular traffic flow.
Abstract: With the increase in simulation of urban environments for the purpose of planning, modelling vehicular traffic has become important. Since empirical evidence on traffic flow is relatively sparse, models are being increasingly used for planning urban roads and environments. In this paper, a simple, explicit model is proposed to approximate the speed versus density of vehicular traffic flow. The model, which uses two parameters derived from simple measurements of real-time traffic data, allows for a prediction of the approximate relationship for congested as well as uncongested vehicular traffic flow. The proposed model is especially useful in conditions where available data is sparse and can be invaluable for the modelling and simulation of urban environments.
3 citations
"Study of traffic flow characteristi..." refers result in this paper
...The models such as Gipps, IDM, and Das-Asundi (Das and Asundi 2011) following models seems to be reasonable under steady state and mixed traffic conditions; Krauss model also gives reasonable results in non-steady state conditions (Naveen Kumar 2012)....
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