Traffic Simulation Research Papers - Academia.edu (original) (raw)

The primary objectives of this study are to develop two roundabout entry capacity models using a regression-based multiple non-linear regression model (MNLR) and artificial intelligence (AI)-based ANFIS (adaptive neuro-fuzzy inference system) model under heterogeneous traffic conditions. ANFIS is the latest technique in the field of AI that integrates both neural networks and fuzzy logic principles in a single framework. Required data have been collected from 27 roundabouts in eight states of India. To assess the significance of these models and select the best model among them, modified rank index is applied in this study. The coefficient of determination (R 2) and Nash-Sutcliffe model efficiency coefficient 'E' values are found to be 0.92, 0.91 and 0.98, 0.98 for the MNLR and ANFIS model, respectively. The ANFIS model is found to be the best model in this study. However, from a practical point of view, the MNLR model is recommended for determining roundabout entry capacity under heterogeneous traffic conditions. Sensitivity analysis reports that critical gap is the prime variable and shares 18.43% for the development of roundabout entry capacity. As compared with the Girabase formula (France), Brilon wu formula (Germany), and HCM 2010 models, the proposed MNLR model is quite reliable under low to medium ranges of traffic volumes. Roundabouts are a specialized form of an un-signalized intersection in which traffic moves in one direction around a central island. Direction of traffic, according to left-hand or right-hand driving rules, depends on the specific country. Roundabouts have been used as an effective intersection control measure to improve safety and operational performance under low to high circulating traffic flow conditions. As compared with other, signa-lized, intersections, roundabouts have several basic advantages, such as speed reduction of vehicles, less delay, pedestrian safety, aesthetics, and reduction of conflict points. A signalized intersection has 32 conflict points, whereas a roundabout with two circulating and entry lanes has 8 and 16 conflict points, respectively. Because of the increase in the use of roundabouts, an assessment regarding operational performance needs to be undertaken. Evaluation of capacity at roundabouts is an important aspect of operational performance that describes the present traffic scenario, level of service, delay, accidents, operational cost, and environmental issues. Under heterogeneous traffic conditions, vehicles of various kinds have varying physical and operational characteristics. In developing countries, driver behavior, vehicular characteristics (size, engine efficiency, and years of usage), and intersection geometric design vary significantly. The vehicle fleet is composed of heavy vehicles (HV), light motor vehicles (LMV), motor cycles/ scooters (MC/S), bicycles (BC) and human-drawn vehicles (HDV). These vehicles share the main carriageway without any physical or marked segregation. When there are vehicles of different types with varying static and dynamic characteristics, follow-the-lane discipline and the follow-the-leader concept become irrelevant. Under constraints of flow and space, small-sized vehicles try to move into the circulating area without following lane discipline. Also, HV forcibly merge into the circulating stream of traffic. These points reflect that the rule of priority is not respected under such a heterogeneous traffic condition. In these circumstances, the study of