Examining queue-jumping phenomenon in heterogeneous traffic stream at signalized intersection using UAV-based data

© 2020, Springer-Verlag London Ltd., part of Springer Nature. This research presents an in-depth microscopic analysis of heterogeneous and undisciplined traffic at the signalized intersection. Traffic data extracted from the video recorded using an unmanned aerial vehicle (UAV) at an approach of a signalized intersection is analyzed to study the within green time dynamics of traffic flow. Various parameters of Wiedemann 74, Wiedemann 99, and lateral behavior models used in microscopic traffic simulation package, Vissim, are calibrated for the local heterogeneous traffic. This research is aimed at exploring the queue-jumping phenomenon of motorbikes at signalized intersections and its impact on the saturation flow rate, travel time, and delay. The study of within green time flow dynamics shows that the flow of traffic within green time is not uniform. Surprisingly, the results indicate that the traffic flow for the first few seconds of the green time is significantly higher than the remaining period of green time, which shows a contradiction to the fact that traffic flow for the first few seconds is lower due to accelerating vehicles. Mode-wise traffic counted per second shows that this anomaly is attributed to the presence of motorbikes in front of the queue. Consequently, the outputs of simulation results obtained from calibrated Vissim show that the simulated travel time for motorbikes is significantly lower than the field-observed travel times even though the average simulated traffic flow matches accurately with the field-observed traffic flow. The findings of this research highlight the need to incorporate the queue-jumping behavior of motorbikes in the microsimulation packages to enhance their capability to model heterogeneous and undisciplined traffic

Basic Driving Dynamics of Cyclists

In this work we introduce the Necessary-Deceleration-Model (NDM) which is a car-following-model developed to investigate driving behavior of bicycles. For this purpose the derivation of the mathematical description of the NDM is investigated. For the sake of calibration and validation of the model, several experiments are performed. The results of the experiments are presented and examined. Finally, the limits and possibilities of the NDM are discussed

Comparative Evaluation of Density Estimation Methods on Different Uninterrupted Roadway Facilities: Few Case Studies in India

Traffic density is one of the fundamental macroscopic characteristics and it is of prime importance when assessment of a facility has to be done based on both users as well as planner’s perspective. According to the Highway Capacity Manual (HCM), USA, for expressways and multilane roads, the Level-of-Service (LoS) has been defined taking density as the governing factor. Density is treated as the fundamental macroscopic spatial parameter of traffic flow, as it directly indicates the quality of traffic and ease with which one can drive. The present research study focuses on applicability of density estimation methods on multi-class, heterogeneous, non-lane based Indian traffic condition. In this research study, mid-block road sections namely, on Delhi-Gurgaon Expressway, Ahmedabad-Vadodara Expressway, National Highway (NH)-8 and urban arterial road in Chennai are considered. The expressways are the highest class of roads in Indian road network with different roadway, traffic conditions and with access control facilities. Delhi–Gurgoan Expressway is eight-lane divided facility and Ahemdabad –Vadodara Expressway is four-lane divided with 2.6 m paved shoulder. On the other hand, selected section on National Highway (NH8) is four-lane divided road. Real traffic data was collected through video-graphic survey on all these roads with different traffic conditions. HCVs (Heavy Commercial Vehicles) and MCVs (Multi-axle Commercial Vehicles) were the major traffic composition in congested regime. Thus, the present study focuses on the comparison of density estimation methods on different roadway and traffic conditions. The three methods to be employed for the purpose of estimating traffic density on the study section are: (1) using traffic flow fundamental equation relating speed, flow and density, HCM definition (2) using Cumulative input–output Plots (Input–Output method) (3) Eddie’s (x, t) method. This paper aims to empirically quantify the difference in the density estimation based on the aforementioned methods. Assuming input–output provides theoretical density, the errors in the estimation of density using fundamental equation under different traffic flow conditions are also quantified. In spite of growing body of literature disputing about the effectiveness and applicability of various density estimation methods, the key finding from this research indicates that all three abovementioned methods works very well under uncongested traffic flow condition. However, for oversaturated traffic conditions the density estimation using fundamental relationship has errors, primarily due to errors in estimation of the space mean speed since the vehicles which persisted within trap length for period longer than time-interval under consideration are not incorporated in the calculation, which is not the case for other two methods. Moreover, the research study concludes that smaller trap length (<100 m) can have errors in estimation of density values as compared to actual density values. The findings are useful for condition assessment of traffic flow for design and operation purposes