Analysis and Modeling of Two-Wheeler-Overtaking-LMV Maneuver in Heterogeneous Traffic Stream

Author(s):  
Ujjwal Sugandhi ◽  
Mallikarjuna Chunchu
Transport ◽  
2010 ◽  
Vol 25 (3) ◽  
pp. 262-268 ◽  
Author(s):  
Mallikarjuna Chunchu ◽  
Ramachandra Rao Kalaga ◽  
Naga Venkata Satish Kumar Seethepalli

Collecting microscopic data is difficult under heterogeneous traffic conditions. This data is essential when modelling heterogeneous traffic at a microscopic level. In this paper, microscopic data collected under heterogeneous traffic conditions using a video image processing technique is presented. Data related to heterogeneous traffic such as vehicle composition in the traffic stream, a lateral distribution of vehicles, lateral gaps and longitudinal gaps have been collected. The lateral distribution of vehicles on a ten‐meter wide road has been analyzed with a specific emphasis on motorized two‐wheeler movement. Using trajectory data, an attempt to examine the gap maintaining the behaviour of vehicles under different traffic conditions has been made. Empirical relationships between the lateral gap and area occupancy have been proposed for various vehicle combinations. The influence of difference in the lateral positions of leading and following vehicles on the longitudinal gap has been analyzed.


2021 ◽  
pp. 853-861
Author(s):  
Manisha Biswal ◽  
Kudururpaka Vamshikrishna ◽  
Sujeet Sahoo ◽  
Prasant Kumar Bhuyan

2003 ◽  
Vol 1852 (1) ◽  
pp. 175-182 ◽  
Author(s):  
V. Thamizh Arasan ◽  
Shiraj Hussain Kashani

The quality of progression of a road traffic stream is one of the critical characteristics that must be quantified for operational analysis of traffic signals, particularly on urban roads. The parameter that has been found to best describe this characteristic of traffic streams is the arrival type. Though precise quantification of arrival type has been found to be difficult, the platoon ratio is a useful measure for this purpose. Thus, the quality of arrival of a traffic stream can be assessed by knowing the corresponding value of the platoon ratio. Study of arrival type over a wide range of traffic characteristics warrants theoretical modeling of traffic flow. In the study reported, an attempt was made to model heterogeneous traffic flow using an innovative technique. The developed model was used to study the arrival type of traffic streams, queue accumulation, and queue dissipation on approaches to traffic signals. The dispersal pattern of traffic platoons after vehicles pass a traffic signal was studied in detail. The effect of variation in traffic composition on traffic platoons was also analyzed.


10.29007/fzq3 ◽  
2018 ◽  
Author(s):  
Quazi Mishkatul Alam ◽  
Bejon Sarker ◽  
Biplob Biswas ◽  
Kazi Hasan Zubaer ◽  
Tarik Reza Toha ◽  
...  

Microscopic traffic simulators have become efficient tools to conduct different analytic studies on roads, vehicles, behavior of drivers, and critical intersections, which lead to- wards a well-planned traffic solution. Devising a realistic and sustainable traffic solution requires replication of the real traffic scenario in a simulator. For example, to simulate the traffic streams of developing and under developed countries, we need to simulate non-lane based heterogeneous traffic stream, i.e., motorized and non-motorized vehicles, road traffic behaviors such as irregular pedestrian, illegal parking, violation of laws pertaining lanes, etc. However, most of the existing traffic simulators are unable to mimic the unstructured road traffic streams of less developed countries with their diversified behaviors. Therefore, in this work, we propose a new microscopic traffic simulator to handle non-lane based heterogeneous traffic stream and on road traffic behaviors that generally occurred in the road networks of cities in less developed countries. Our simulator receives network topology, traffic routes, and traffic demand flow rates as input, visualizes the traffic flows, and provides traffic statistics. To evaluate sustainability of our proposed simulator in real-life scenarios, we calibrate the simulator using real traffic data. Our evaluation reveals 99% accuracy in terms of travel time.


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