Development of Traffic Congestion Model to Evaluate the Level of Congestion and its Associative Cost for an Urban Arterial Road: a Case Study

Karthik, S; Loui, T. R.

doi:10.1007/s40030-021-00526-z

Cited by 6 publications

(2 citation statements)

References 8 publications

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“…ITH the gradual increase in the level of urbanization in China, traffic congestion is becoming more and more serious [1]. Safe driving models are the theoretical basis for achieving the development of intelligent transportation [2].…”

Section: Introductionmentioning

confidence: 99%

Safe Driving Model Based on V2V Vehicle Communication

Xie

Wang

et al. 2022

IEEE Open J. Intell. Transp. Syst.

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Along with the rapid development of connected vehicle communication technology, describing the vehicle following driving status becomes gradually complicated. Driver behavior, vehicle type, and road factors affect vehicle speed, and the following distance reflects variability. In this paper, a nonlinear following distance model is constructed to characterize this variability. The model is based on the full speed difference model (FVD), and introduces the headway time distance coefficient, the following vehicle type coefficient, the communication advance response parameter reflecting the driver's personal characteristics, and the slope coefficient and curve curvature coefficient reflecting the road conditions, etc., and analyzes to obtain the stability conditions of the model. MATLAB is applied to numerical simulation experiments of the model, and the results show that the model can better describe the variability of following headway due to driver attributes, vehicle type, slope and curve in the connected vehicle scenario, thus providing a reference for traffic flow control and management.

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Section: Introductionmentioning

confidence: 99%

Safe Driving Model Based on V2V Vehicle Communication

Xie

Wang

et al. 2022

IEEE Open J. Intell. Transp. Syst.

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“…The congestion can occur due to the frequent change in macro and micro level parameters looking to the present traffic demand [5]. The micro-level parameters are related to the traffic plying on a particular facility, while the macro-level parameter is related to the overall demand of the facility [6].…”

mentioning

confidence: 99%

A Simulation Approach for Evaluating Congestion and Its Mitigation Measures on Urban Arterials Operating with Mixed Traffic Conditions

Bari¹,

Gunjal²,

Dhamaniya³

2022

Communications

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Present study evaluates the various congestion indexes in terms of speed performance index, volume to capacity ratio and congestion index based on travel time on the urban roadway network of 5.7 km in length, operating with mixed traffic conditions (traffic with varying static and dynamic characteristics of vehicles). The mitigations measures have been proposed to cater to the present traffic demand by converting the uncontrolled intersection to a partially controlled or signal-controlled intersection. In order to check the effectiveness of such mitigation measures, various scenarios have been generated in the developed and a well calibrated simulation model. It has also been observed that the speed performance index has improved by 8.88 percent while providing channelized intersection at one of the point elements and 11.52 %when the two-point elements have converted to channelizing intersection.

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