Bi-directional Control Characteristics of General Motors (GM) and Optimal Velocity Car- Following Models: Implications for Coordinated Driving in Connected Vehicle Environment

1 In natural traffic flow, the information from preceding vehicles determines driver behavior predominantly. 2 With the availability of connected vehicle technologies (CVT), drivers can receive information from both 3 preceding and following vehicles. This creates new opportunities for vehicle coordination and control at 4 the microscopic level based on bi-directional information. Although the bi-directional car following 5 models have been studied since the 1960s, most existing car-following models, especially those used by 6 adaptive cruise control (ACC) technologies, are still forward-only car-following models. This paper 7 serves as a first step towards the use of bi-directional car-following models for microscopic vehicle 8 coordination and control. The focus is on studying their general control characteristics and their impact on 9 traffic flow stability. A general bi-directional control framework is proposed to convert any car-following 10 model into bi-directional forms. Four representative GM (General Motors) and optimal velocity car11 following models are reformulated and calibrated against field vehicle trajectory data collected in the 12 NGSIM (Next Generation SIMulation) project. The bi-directional control characteristics of the selected 13 models are evaluated by tuning the percentage of the consideration of backward information in the final 14 car-following decision. The evaluation uses forward versus backward acceleration diagrams and a ring 15 road stability analysis with respect to equilibrium states obtained from the NGSIM data. The increase of 16 backward information contribution may help alleviate traffic congestion and stabilize traffic flow. 17 Meanwhile, an operating range of backward information contribution between 5-20% is recommended so 18 that the resulting model can produce reasonable results for both free flow and congestion situation. 19 20 21