Towards Behavioral Modeling of Drivers in Mixed Traffic Conditions

Abstract

Mixed traffic conditions characterized by the presence of different vehicle types and weak lane discipline are common in the developing world. Different maneuvering capabilities of different vehicle types lead to vehicle-type dependent longitudinal and lateral movement driving behaviors. Weak lane discipline allows drivers to simultaneously look for possible lateral movements while progressing longitudinally. This integrated driving behavior gives rise to various driving phenomena like tailgating, multiple-leader following, swerving and filtering. However, very few studies exist in the literature that attempt to model these typical driving behaviors of mixed traffic streams. Moreover, most of these studies are not often readily available. Thus, a comprehensive review of the studies that consider modeling driver behavior in mixed traffic conditions is presented in this paper. Often, models developed for mixed traffic conditions stemmed out of the basic principles employed in the development of homogeneous traffic models. Hence, this paper first reviews the lane-based macro-, micro-and meso-scopic models in tandem and identifies their strengths and weaknesses in describing the mixed traffic system. A thorough understanding and conceptualization of any system is possible by analyzing large sets of empirical data. Therefore, a brief review on traffic data requirements to understand and model the driver behavior and, data extraction tools to obtain the trajectories of vehicles is presented next. Driver behavioral models form the core of any microscopic traffic simulation model. Core behavioral models such as carfollowing and lane-changing models which describe the longitudinal and lateral movements of drivers respectively are reviewed next. However, these two behavioral models may not be able to describe the integrated driving behavior independently. Therefore, various integrated driver behavioral models are briefed next. A simulation framework is essential to implement the driver behavioral models and evaluate their capabilities in representing larger scale traffic systems. Hence, a brief review of various simulation frameworks is presented subsequently. Finally, the challenges that are involved in modeling driver behavior in mixed traffic conditions are discussed and some useful research directions are proposed.

Network-risk: an open GIS toolbox for estimating the implications of transportation network damage due to natural hazards, tested for Bucharest, Romania

“…CC BY 4.0 License. behavior simulations or decision patterns (as described in Asaithambi & Basheer, 2017or Munigety & Mathew, 2016) can be implemented.…”

Simulation Strategies for Mixed Traffic Conditions: A Review of Car-Following Models and Simulation Frameworks

“…So, whenever there is a possibility for collision or overtaking instead of decelerating, drivers swerve off. is weaving action of these drivers gives rise to integrated lateral and longitudinal motions [124]. is driving behaviour in mixed traffic stream can be analysed by empirical data collection from real-time traffic data.…”

“…For the microscopic simulation of urban traffic, CARSIM and NETSIM came into existence [131]. Another famous microscopic simulation framework is SUMO, which is a time-discrete and space-continuous based model used to simulate the mixed transportation in urban areas such as pedestrians and public and private transport [89,137,138].…”

“…e modification of the car-following model in the PARAMICS framework to incorporate acceleration and deceleration rates was performed by Munigety et al [138] by introducing the threshold parameters into the model. In the same way, VISSIM a microscopic time-based simulation framework is used to simulate the urban traffic flow along with public transit.…”

“…e long-lasting problem in a psychophysical model is the consideration and distribution of parameters related to threshold values. To calibrate the real-world traffic accurately, continuous traffic measurement of different vehicle flow situations is of utmost importance [138,139]. Various researches have carried out and simulated the mixed traffic flow with the help of VISSIM framework to determine the heterogeneous vehicle behaviour [140][141][142][143].…”