Abstract:

This study proposes a secondary speed guidance strategy that incorporates driver acceptance levels to enhance the traffic efficiency address and reduce fuel consumption and emissions in the upstream areas of signalized intersections. The strategy addresses the inadequate execution of guidance strategies by drivers in manual driving environments. Focusing on connected human-driven vehicles, it introduces the parameter of driver acceptance degree to refine three primary guidance models: acceleration guidance through, deceleration guidance through, and deceleration guidance to stop. To mitigate the impact of low driver acceptance, secondary acceleration guidance through and secondary deceleration guidance through models are constructed. Using the Matlab simulation platform, this study established a simulation environment that considers vehicle trajectory, speed, acceleration, fuel consumption, and emissions. Comparative analyses of no guidance, primary guidance under varying driver acceptance levels, and secondary guidance were conducted. The simulation results show that strictly following the primary guidance strategy can enable more vehicles to pass through the intersection without stopping, improving traffic efficiency by approximately 14.3%, and reducing fuel consumption and emissions by 10% to 15%. Low driver acceptance has a significant negative impact on primary speed guidance, rendering the primary guidance strategy ineffective and causing additional fuel consumption and emissions. The secondary guidance strategy can effectively alleviate the impact of low driver acceptance, restoring traffic efficiency to over 95% of that of primary guidance and reducing fuel consumption and emissions by approximately 8% to 12%.

Key words: signalized intersection, connected human-driven vehicles, speed secondary guidance, driver acceptance level, speed guidance strategy