Technical Analysis and Improvement of the Pedestrian Safety Protection of a Car Hood

The pedestrian protection technology must be used in automotive design if China-made automotives want to compete and grow strong in the world in the future. In this paper, a CAE simulation analysis is made for a domestic sedan car hood to check whether it meet the pedestrian safety protection laws and regulations. Results show that the original car cannot meet the demands of the rules. In order to meet the standards of the pedustrian protection rules, the car hood should undergo structural improvements. Tested again by CAE simulation analysis, the car after a series of improved design can reached the 3-star class EuroNCAP（ Euro New Car Assessment Program）standard of the car pedestrian safety protection laws and regulations.

Application of CAE technology for Geely car lightweight

In order to reduce energy consumption and protect the human survival environment, the lightweight has became the development trend of the world automobile industry. On the premise of ensuring the strength, safety and driving performance of the car, the major car enterprises try to reduce the curb weight of the ear, fuel consumption and emissions. Not only a lot of new technologies and new products have been generated, but also joint vehicle development process and computer aided engineering （CAE） analysis technology have been developed. Since the entry into the ＂Au- tomobile Lightweight Technology Innovation Strategic Alliance＂ in Dec. 2007, Geely Group has been focusing on light- weight construction of vehicle and key assemblies in every stage of the vehicle product development. Among vehicles ap- peared on the market and in research, it has presented continuously better performance. The paper describes application examples and successful experience of CAE simulation analysis and performance optimization during the lightweight de- sign and development of a self-developed model of Geely, and looks forward to the prospects for the development of lightweight of Geely vehicle.

Pedestrian trajectory prediction in crossing scenario using fuzzy logic and switching Kalman filter

Pedestrian trajectory prediction plays an important role in bothadvanced driving assistance system(ADAS) and autonomous vehicles. An algorithm for pedestrian trajectory prediction in crossing scenario is proposed. To obtain features of pedestrian motion, we develop a method for data labelling and pedestrian body orientation regression. Using the hierarchical features as domain of discourse, fuzzy logic rules are built to describe the transition between different pedestrian states and motion models. With derived probability of each type of motion model we further predict the pedestrian trajectory in the next 1.5 s using switching Kalman filter(KF). The proposed algorithm is further verified in our dataset, and the result indicates that the proposed algorithm successfully predicts pedestrian’s crossing behavior 0.4 s earlier before pedestrian moves. Meanwhile, the precision of predicted trajectory surpasses other methods including interacting multi-model KF and dynamic Bayesian network(DBN).