Traffic lights force vehicles to stop frequently at signalized intersections, which leads to excessive fuel consumption, higher emissions, and travel delays. To address these issues, this study develops a trajectory planning method for mixed vehicles at signalized intersections. First, we use the intelligent driver car-following model to analyze the string stability of traffic flow upstream of the intersection. Second, we propose a mixed-vehicle trajectory planning method based on a trigonometric model that considers prefixed traffic signals. The proposed method employs the proportional-integral-derivative (PID) model controller to simulate the trajectory when connected vehicles (equipped with internet access) follow the optimal advisory speed. Essentially, only connected vehicle trajectories need to be controlled because normal vehicles simply follow the connected vehicles according to the Intelligent Driver Model (IDM). The IDM model aims to minimize traffic oscillation and ensure that all vehicles pass the signalized intersection without stopping. The results of a MATLAB simulation indicate that the proposed method can reduce fuel consumption and NOx, HC, CO2, and CO concentrations by 17%, 22.8%, 17.8%, 17%, and 16.9% respectively when the connected vehicle market penetration is 50 percent.

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In order to track the research progress of AEB-related technologies, this paper makes a systematic analysis and research on the impact factors, key technologies, and effect evaluation of AEB. First, the paper deeply analyzes the three levels of factors affecting the performance of AEB, which are vehicle factors, driver factors, and environmental factors. Second, the paper deeply studies the technical status of the three subsystems of environment perception, decision-making, and control execution. Particularly, the performance of Mazda, Honda, NHTSA, Berkeley, and Seungwuk Moon are compared and analyzed based on MATLAB. Third, the paper summarizes the current AEB virtual test methods, closed field test methods, and its test sites. Three classic evaluation methods in the world, including the AEB test evaluation standards of ENCAP, IIHS, and i-Vista are analyzed. Finally, the paper prospects the specific research directions, including the protection of vulnerable road users, target detection method, collision avoidance strategy, complex scenarios application, and application of emerging technologies.

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