7. Importance of Microscopic Parameters in Simulating No-Lane Based Heterogeneous
8.2. Summary of the Research Work
The important findings of this research work are divided in three parts and presented in the subsequent sub-sections.
8.2.1. Study of Dynamic Parameters of Vehicles
The longitudinal acceleration/deceleration (A/D), lateral acceleration and operating speed are three major dynamic parameters which can describe the driving behaviour in no-lane based
mixed traffic stream. All three dynamic parameters are evaluated for different type of vehicles on straight mid-block sections, and their best-fitted probability distributions are obtained. Also, their variation with operating speed of vehicles is studied. Significant findings obtainedfrom the study of all three parameters are listed below;
It is observed that road width does not have significant impact on longitudinal acceleration/deceleration behaviour of vehicles while it has a significant impact on lateral acceleration. It is observed that the lateral acceleration of 4-lane divided road (i.e. 2-lane each side)is higher than 6-lane roads (3 lanes each side).
From the cumulative percentile curve, it is found that the break point does not always lie exactly at 85th percentile value for both longitudinal acceleration/deceleration and lateral acceleration of vehicles. Hence, the 85th percentile design value concept should be reconsidered.
The 95th (85th) percentile of acceleration values are 1.38(0.94) m/s2, 1.45(0.95) m/s2 and 1.54 (1.04) m/s2 for SUV, Sedan and H-back cars respectively. However, the deceleration values for all three cars are 1.63 (1.03) m/s2, 1.77(1.06)m/s2 and 1.66 (1.04) m/s2 respectively.
The 95th (85th) percentile acceleration values for 2W and 3W are considerably higher than cars, i.e. 2.33 (1.45) m/s2 and 1.65 (1.07) m/s2 respectively with a higher deceleration of 1.82 (1.18) m/s2 and 2.43 (1.58) m/s2.
The 95th percentile values of lateral acceleration are <2 m/s2 for SUV and Sedan cars, and it increases for H-Back cars followed by motorized 3W and 2W (up to 2.54 m/s2).
The 85% of lateral acceleration data for all type of vehicles lies below the medium comfort level (<1.8 m/s2).
The 85th and 95th percentile A/D of different vehicles follow a linearly decreasing trend with the operating speed of vehicles during normal driving conditions on straight roads.
The relationship between 85th and 95th percentile lateral acceleration and operating speed of all five type of vehicles follow two-term exponential model for normal driving conditions on straight roads.
It is observed that the friction circle concept (g-g diagram) can determine the driving behaviour of different type of vehicles using all three dynamic parameters (longitudinal A/D, lateral acceleration and operating speed).
The proposed diagram for resultant acceleration and design speed (safety domain curve), can easily demonstrate the safe or unsafe driving behaviour. The defined safety
domain is an important tool for finding the points on the trajectory, where the driving behaviour is safe/unsafe to inform him about his driving behaviour and produce the threshold of attention to take preventive measures
This study also investigated the applicability of the copula based approach to model the joint distribution of longitudinal descriptors [operating speed, longitudinal (A/D)] and lateral descriptor [lateral acceleration] of five different type of vehicles (motorized 2W, 3W, H-back, Sedan and SUV cars) for no-lane based traffic streams.
The recommendation is to use trivariate Gaussian copula for the amelioration of the realistic representation of riders’ behaviour in lane-based as well as in non-lane based traffic streams, by suitably accommodating the dependent relationships between the longitudinal and lateral descriptors of different type of vehicles.
8.2.2. Study of Lateral Placement of Vehicles across the Road section:
The lateral placement of different type of vehicles on the entire cross-section is studied for roads with different width (i.e. 2-lane, 3-lane, 4-lane and 5-lane on each side). It is observed that the road width (number of the lane), flow condition and lateral placement of vehicles have a significant impact on operating speed of vehicles. The important findings from the study of the lateral placement of vehicles are presented below:
It is observed that in the case of 2-lane and 3-lane wide roads, 75% to 90% of cars travel near the median side of the roads.
55% to 80% trucks and light-commercial vehicles (LCVs) move mainly along the median-sided lane in case of 2-lane and 3-lane wide roads and shifts towards shoulder side in 4-lane and 5-lane wide roads.
50% of the road space towards shoulder side is covered by 70% of 2Ws present in the traffic stream. If one takes up 50% of the road on the shoulder side, it can be seen that nearly 60% of 2Ws move over this portion of the road for 4-lane, 6-lane and 10-lane divided roads and nearly 85% of them move in this portion of road for 8-lane divided road.
The operating speed of vehicles as a function of lateral placement and flow of the traffic stream follows a linearly decreasing trend from median to shoulder for all roads and all type of vehicles.
8.2.3. Impact of Median Type on Lateral Gap of Vehicles from Median:
The size of the median (width and height) and operating speed of vehicles have a significant
impact on the minimum lateral gap maintaining behaviour of vehicles.
The lateral gap maintained by cars decreases with the increase in width of the median (i.e. from 0.45m width to 1.2m width). However, the height of plantation has a significant impact on the lateral gap maintain behaviour of vehicles. Similarly, the width of median have a similar impact on lateral gap maintaining behaviour of trucks also.
The height of the median is highly correlated to the lateral gap maintained by vehicles from the median. The vehicles (both trucks and cars) shifts away from the median with the increase in height of the median due to their perception of risk to collision.
It is also observed that operating speed of vehicles have a higher impact on lateral gap maintaining behaviour of cars comparing to trucks.
8.2.4. Importance of Microscopic Parameters in Simulating Non-Lane Based Heterogeneous Traffic Stream
A simulation framework is essential to evaluate the detailed traffic performance at different roadway sections, development of the driver behaviour models and hence simulate the large- scale real-world traffic situations in great detail. Modelling driver behaviour requires a detailed understanding of the vehicular interactions with the surrounding traffic and roadway features from the real-world traffic stream. Unlike the lane based traffic, in case of no-lane-disciplined traffic, it is difficult to get the field data on vehicular movement such that a detailed understanding of the traffic stream behaviour can be obtained. The identified important microscopic parameters obtained from the field data are compared with the parameters obtained from the simulated stream using a commercially available micro-simulation framework, VISSIM. Before the comparison study, VISSIM is well calibrated and validation with microscopic and macroscopic parameters which are generally used in available literature.
The important observations of this study are listed below.
It is observed that the longitudinal manoeuvring behaviour related parameters (longitudinal speed, time headway and acceleration/deceleration behaviour of vehicles) obtained from VISSIM shows similar behaviour to the field data.
The lateral manoeuvring (i.e. the lateral acceleration, lateral speed and the lateral placement of vehicles on the entire road width) which impacts significantly the
manoeuvring behaviour in non-lane based heterogeneous traffic stream are not represented realistically by VISSIM.
In field traffic, it is observed that the minimum lateral gap maintained by vehicles from the median, depends on the median size (width and height) and the operating speed of vehicles. However, in case of VISSIM, vehicle maintain an uniform gap from median irrespective of their operating speed which is against the drivers’ perception of safety.
In case of field traffic, due to no-lane based heterogeneous traffic, the lateral manoeuvring of vehicles are very high. Hence, one should incorporate these microscopic parameters also in developing any simulation model for the no-lane based heterogeneous traffic stream.