Modeling Lane-Changing Behavior in a Connected Environment: A Game Theory Approach

AbstractVehicle-to-Vehicle communications provide the opportunity to create an internet of cars through the recent advances in communication technologies, processing power, and sensing technologies. Aconnected vehicle receives real-time information from surrounding vehicles; such information can improve drivers’ awareness about their surrounding traffic condition and lead to safer and more efficient driving maneuvers. Lane-changing behavior,as one of the most challenging driving maneuvers to understand and to predict, and a major source of congestion and collisions, can benefit from this additional information.This paper presents a lane-changing model based on a game-theoretical approach that endogenously accounts for the flow of information in a connected vehicular environment.A calibration approach based on the method of simulated moments is presented and a simplified version of the proposed framework is calibrated against NGSIM data. The prediction capability of the simplified model is validated. It is concluded the presented framework is capable of predicting lane-changing behavior with limitations that still need to be addressed.Finally, a simulation framework based on the fictitious play is proposed. The simulation results revealed that the presented lane-changing model provides a greater level of realism than a basic gap-acceptance model

Dynamic Coordinated Control System for Emergency Evacuation: Exploration and Assessment

In light of more frequent extreme events impacting larger and denser population centers, understanding evacuation processes and developing strategies to make evacuations more efficient has become essential. From a transportation standpoint, evacuation related problems involve multiple dimensions: (1) a demand dimension, (2) a routing dimension, and (3) a control dimension. Focusing on the routing and the control dimensions, the objective of this paper is to explore a dynamic coordination logic that involves different control strategies that result in adaptive route switching in response to prevailing traffic information during extreme events. The corresponding logic can be adopted within the current traffic management framework; the resulting adaptive coordination logic is implemented and tested on a portion of the Maryland Coordinated Highways Action Response Team (CHART) network in the United States. Through the use of the dominant path concept and transforming the transportation network into multiple evacuation corridors, improved evacuation performance measures are reached. The dynamic coordination of existing control tools (i.e., variable message signs, ramp meters, and traffic signals) is better realized on these dominant paths. The numerical results show improvements in travel times and delays experienced by the evacuating vehicles

Aggressiveness propensity index for driving behavior at signalized intersections. Accident Analysis and Prevention

Abstract The development of a quantitative intersection aggressiveness propensity index (API) is described in this paper. The index is intended to capture the overall propensity for aggressive driving to be experienced at a given signalized intersection. The index is a latent quantity that can be estimated from observed environmental, situational and driving behavior variables using structural equations modeling techniques. An empirical study of 10 major signalized intersections in the greater Washington DC metropolitan area was conducted to illustrate the approach. The API is shown to provide (a) an approach for capturing and quantifying aggressive driving behavior given certain measurements taken at a particular intersection, (b) understanding of the factors and intersection characteristics that may affect aggressiveness, and (c) an index for the cross comparison of different traffic areas with different features. This index has the potential to support safety policy analysis and decision-making

Pedestrian dynamics at transit stations: an integrated pedestrian flow modeling approach

This paper presents an integrated modelling framework to capture pedestrian walking behaviour in congested and uncongested conditions. The framework is built using a combination of concepts from the Social Force model (basic one-to-one interaction), behavioural heuristics (physiological and cognitive constraints), and materials science (multi-body potential concept). The approach is ultimately designed to capture pedestrian interactions in transit stations. Due to the lack of available trajectory data of pedestrians within transit stations, the model is calibrated using pedestrian trajectory data from narrow bottleneck and bidirectional flow experiments provided by the Delft University of Technology. These two scenarios were chosen due to the frequency with which they occur in transit stations. The integrated modelling framework reproduced similar trajectory patterns observed in the experiments which encouraged a transit station simulation in an environment similar to that at the Foggy-Bottom METRO station in Washington, D.C.Transport and Plannin

From structural equation modeling to macroscopic fundamental diagrams : investigating the impact of road segments safety on network level efficiency

The main objective of this research is to expand upon the link between network flow (mobility) and safety through the estimation of Macroscopic Fundamental Diagrams (MFD) and Structural Equation Models (SEM) with different levels of disruptions caused by different surrounding driving conditions. Analysis begins with the aggregation of microscopic level loop detector data and collision data provided by The Korea Expressway Corporation (KEC). The KEC operates highway tolls throughout South Korea and continues to expand upon the nearly 4000 km of high-speed motorways it provides. The rich, detailed collision and traffic flow data collected on these roadways makes the region an ideal candidate for the new analysis technique that is presented in this study. Three specific types of non-recurrent disruptions, as suggested by SEM results, (inclement weather conditions; increased holiday demand; increased number of collisions) are analyzed and compared in this study. By estimating and comparing MFDs for these specific cases, the differences in network level disruptions caused by these events are visualized, quantified and discussed. Additionally, by using SEM to quantify the impact of these disruptive events on safety and impedance at the link level, spatial and temporal analysis can be conducted – establishing a link between the microscopic event-based data (mainly collisions) and the macroscopic network performance measures of safety and traffic mobility