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Automotive safety is always the focus of consumers, the selling point of products, the focus of technology. In order to achieve automatic driving, interconnection with the outside world, human-automatic system interaction, the security connotation of intelligent and connected vehicles (ICV) changes: information security is the basis of its security. Functional safety ensures that the system is operating properly. Behavioral safety guarantees a secure interaction between people and vehicles. Passive security should not be weakened, but should be strengthened based on new constraints. In terms of information safety, the threshold for attacking cloud, pipe, and vehicle information should be raised to ensure that ICV system does not fail due to malicious attacks. The cloud is divided into three cloud platforms according to functions: ICVs private cloud, TSP cloud, public cloud.

Although energy harvesting systems are extensively used in different fields, studies on the application of energy harvesters embedded in tires for vehicle control are rare and mostly focus on solving power supply problems of tire pressure sensors. Sensors are traditionally powered by an embedded battery, which must be replaced periodically because of its limited energy storage. Heightened interest in vehicle safety is expected to drive increased design and manufacture of in-tire sensors, which in turn, translates to rising demand for power generation in tires. These challenges emphasize the need to investigate the substitution of batteries and in-tire energy harvesting systems. Current in-tire energy harvesting methods involve piezoelectric, electromagnetic, and electrostatic power generation, whose energy sources include tire vibrations, deformations, and rotations. Piezoelectric harvesters are generally compact but operate for short durations.

Due to the high cost of torque sensors, a calculation model of transient torque is required for real-time coordinating control purpose, especially in hybrid electric powertrains. This paper presents a feedforward calculation method based on mean value model of turbocharged non-EGR diesel engines. A fitting variable called fuel coefficient is defined in an affine relation between brake torque and fuel mass. The fitting of fuel coefficient is simplified to depend only on three variables (engine speed, boost pressure, injected fuel mass). And a two-layer feedforward neural network is utilized to fit the experimental data. The model is validated by load response test and ETC (European Transient Cycle) transient test. The RMSE (root mean square error) of the brake torque is less than 3%.

This paper proposed a path coordination strategy for autonomous parking based on independently designed parking lot topological map. The strategy merges two types of paths at the three stages of path planning, to determinate mode switching timing between low-speed automated driving and automated parking. Firstly, based on the principle that parking spaces should be parallel or vertical to a corresponding path, a topological parking lot map is designed by using the point cloud data collected by LiDAR sensor. This map is consist of road node coordinates, adjacent matrix and parking space information. Secondly, the direction and lateral distance of the parking space to the last node of global path are used to decide parking type and direction at parking planning stage. Finally, the parking space node is used to connect global path and parking path at path coordination stage.

Safety of buses is crucial because of the large proportion of the public transportation sector they constitute. To improve bus safety levels, especially to avoid driver error, which is a key factor in traffic accidents, we designed and implemented an intelligent bus called iBus. A robust system architecture is crucial to iBus. Thus, in this paper, a novel self-driving system architecture with improved robustness, such as to failure of hardware (including sensors and controllers), is proposed. Unlike other self-driving vehicles that operate either in manual driving mode or in self-driving mode, iBus offers a dual-control mode. More specifically, an online hot standby mechanism is incorporated to enhance the reliability of the control system, and a software monitor is implemented to ensure that all software modules function appropriately. The results of real-world road tests conducted to validate the feasibility of the overall system confirm that iBus is reliable and robust.

With the development of intelligent vehicle and active vehicle safety systems, the demand of sensors is increasing, especially in-tire sensors. Tire parameters are essential for vehicle dynamic control, including tire pressure, tire temperature, slip angle, longitudinal force, etc.. The diversification and growth of in-tire sensors require adequate power supply. Traditionally, embedded batteries are used to power sensors in tire, however, they must be replaced periodically because of the limited energy storage. The power limitation of the batteries would reduce the real-time data transmission frequency and deteriorate the vehicle safety. Heightened interest focuses on generating power through energy harvesting systems in replace of the batteries. Current in-tire energy harvesting devices include piezoelectric, electromagnetic, electrostatic and electromechanical mechanism, whose energy sources include tire deformations, vibrations and rotations.

The ability of actively adjusting attitude provides a great advantage for those vehicles used in special environments such as off-road environment with extreme terrains and obstacles. It can improve vehicles’ stability and performance. This paper proposes an attitude control system for realizing the active attitude adjustment and vehicle motion control in the same time. The study is based on a vehicle with six wheel independent drive and six independent suspensions (6WIDIS), which is a kind of unmanned vehicle with six in-wheel drives and six independent hydro pneumatic suspensions. With the hydro- pneumatic suspensions, the vehicle’s attitude can be actively adjusted. This paper develops a centralized- distributed control strategy with attitude information obtained by multi-sensor fusion, which can coordinate the complex relationship among the six wheels and suspensions. The attitude control system consists of three parts.

This paper presents an investigation of drivability issue of engine start-stop. Hybrid vehicles provide excellent benefits regarding fuel efficiency and emission. However, vibration results from constant engine start and stop events generate drivability issues, thus compromising driving comfort. This paper has designed a high speed torque sensor to capture instantaneous torque at the engine shaft. Its consequences help to find out the most suitable index of vibration severity. This paper is organized in four sections. The first section introduces the powertrain to be studied. The second section introduces development of a specially designed torque sensor. The torque sensor is installed between the engine and ISG (Integrated Starter Generator), alongside with an encoder. The torque sensor is utilized to collect the instantaneous shaft torque on occasion of engine start. In the third section, this paper has performed two experiments.