Flow dynamics of mixed traffic comprising connected autonomous vehicles and conventional vehicles - Yasushi Yokoya; Akito Yamasaki; Hitoshi Soma (Cogent Engineering)
Flow dynamics of mixed traffic, comprising connected autonomous vehicles (CAVs) and human-driven vehicles (HDVs) were elucidated by focusing on the CAV penetration rate and communication performance. The mixed traffic flow was modeled using a deterministic cellular automaton (CA). Each CAV utilized its communication functionality to acquire real-time information on the driving conditions, such as velocity, position, from the multiple CAVs traveling within the communication range. The mutual CAV behavior was synchronized by information transmitted in real time. In contrast, each HDV traveled by only referring to the single vehicle traveling immediately ahead. Simulation results indicated that when the critical density is exceeded, the time evolutions of the average velocity and flow do not reach a steady state, causing unstable traffic flow. As the CAV penetration rate increases, the flow increases, but the traffic flow instability intensifies above the critical density. Moreover, an increasing CAV penetration rate enhances the flow by expanding the communication range; however, a threshold penetration rate exists. The enhancement of the traffic flow was not appreciable below the threshold even if the CAV communication range expanded. These results provide useful knowledge for future attempts to increase flows for mixed traffic flows, while avoiding instability.