Safety is the cornerstone of autonomous driving vehicles. For autonomously controlled vehicles driving safely in complex and dynamic traffic scenarios, it is essential to predict the evolution of the current traffic situation in the near future and make an accurate situation risk assessment. The precise motion prediction of surrounding vehicles is an essential prerequisite for risk assessment and motion planning of autonomous vehicles. In this paper, we propose a risk assessment and motion planning method for autonomously controlled vehicles based on motion prediction of surrounding vehicles. Firstly, surrounding vehicles' trajectories are predicted based on fusing constant turn rate and acceleration-based motion prediction model and maneuver-based motion prediction model with interactive multiple models. Then, the collision risk assessment between autonomously controlled vehicle and surrounding vehicles is conducted with a collision risk index considering both the probability of collision event and collision severity. After that, the motion planning of autonomously controlled vehicle is formulated as a multiobjectives and multi-constraints optimization problem with model predictive control. Finally, the proposed method is applied to several traffic scenarios to validate its feasibility and effectiveness. INDEX TERMS Autonomous vehicles, motion prediction, risk assessment, motion planning, model predictive control.

<div class="section abstract"><div class="htmlview paragraph">Safety is the cornerstone for Advanced Driver Assistance Systems (ADAS) and Autonomous Driving Systems (ADS). To assess the safety of a traffic situation, it is essential to predict motion states of traffic participants in the future with mathematic models. Accurate vehicle trajectory prediction is an important prerequisite for reasonable traffic situation risk assessment and appropriate decision making. Vehicle trajectory prediction methods can be generally divided into motion model based methods and maneuver model based methods. Vehicle trajectory prediction based on motion models can be accurate and reliable only in the short term. While vehicle trajectory prediction based on maneuver models present more satisfactory performance in the long term, these maneuver models rely on machine learning methods. Abundant data should be collected to train the maneuver recognition model, which increases complexity and lowers real-time performance. In this paper, a vehicle trajectory prediction method based on motion model and maneuver model fusion with Interactive Multiple Model (IMM) is proposed. Firstly, Constant Turn Rate and Acceleration (CTRA) motion model and Unscented Kalman Filter (UKF) are used to predict vehicle trajectory with uncertainty in the future. Then, vehicle trajectory prediction based on simplified maneuver recognition model is conducted, using temporal and spatial relationship between vehicle historical trajectory and lane lines. After that, vehicle trajectory prediction by integrating motion model and maneuver model with IMM is conducted. Finally, the proposed method is compared with CTRA motion model based vehicle trajectory prediction and lane keeping model (LKM) based vehicle trajectory prediction in two simulation test scenarios. The simulation results indicates that the IMM-based method achieves both excellent prediction accuracy and appropriate prediction uncertainty in the whole prediction horizon. This research can be used to support decision making for Advanced Driver Assistance Systems (ADAS) and Autonomous Driving Systems and leads to improvement of traffic safety.</div></div>

With the coordinate data of community sports facilities in Fuzhou and the Geographic Information System platform, this paper developed a research framework of accessibility from three aspects of distribution, service coverage and access equality level. In addition, based on this, this paper analyzed the level and characteristics of the accessibility of community sports facilities within the third ring road of Fuzhou, China. The results showed that the community sports facilities within the third ring road of Fuzhou basically achieved the coverage of being within a ten-minute walking distance, but there were still some deficiencies regarding to the distribution of facilities and the equality level of accessibility. In addition, the results showed poor spatial matching between the number of facilities and population. A shortage of community sports facilities was found in the old central urban area, leading to poor accessibility. It is suggested in this paper that an overall improvement could be carried out through urban renewal.

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