Modeling impacts of different data transmission delays on traffic jam, fuel consumption and emissions on curved road

Under the intelligent transportation system, the use of autonomous vehicles can ease traffic jam, and reduce fuel consumption and emissions. The effects of different data transmission delays on traffic jam, fuel consumption and emissions on curved road are studied by constructing an extended multi-vehicle curve following model considering different data transmission delays to describe the curve following behavior of multiple autonomous vehicles. Subsequently, the stability of the novel model is derived by using linear stability theory. And then, numerical simulation is executed. Finally, some influence factors including curvature radius, backward looking effect, position signal time delay, and velocity signal time delay are discussed. Numerical simulation results show that reducing curvature radius and increasing backward looking effect can reduce fuel consumption and emissions, decrease density fluctuations, thereby gradually eliminating traffic jam. In addition, as difference between position signal time delay and velocity signal time delay decreases, the improvement degree in fuel consumption and emissions is limited. Meanwhile, it also makes density fluctuation decreases gradually, enhances traffic stream stability, and alleviates traffic jam, which is keeping with theoretical analysis. The finding has theoretical implications for designing autonomous vehicle control algorithms to reduce the negative effects of data transmission delays in traffic flow.