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Lane detection is an important component in automatic pilot system and advanced driving assistance system (ADAS). The stability and precision of lane detection will directly determine precision of control and lane plan of vehicles. Traditional mechanical vision lane detection approaches in complicated environment have the deficiencies of low precision and feature semantic description disabilities. But the lane detection depending on deep learning, e.g. SCNN network, LaneNet network, ENet-SAD network have imbalance problems of splitting precision and storage usage. This paper proposes an approach of high-efficiency deep learning Segnet-LSTM semantic segmentation network. This network structure is composed with encoding network and corresponding decoding networks. First, convolution and maximum pooling. The proposal extracts texture details of five images and stores searching position of maximum pooling. Meanwhile, it will implement interpolate processing to the lost points.

In the passenger cabin of the parking under the summer sun, the air’s average temperature will reach about 60°C. Such temperature can cause discomfort to the person who has just entered the passenger cabin, also can damage components of the passenger cabin. The reason for this phenomenon is because it is not convective with the outside air. Some vehicles use the electric power to drive the blower in order to ventilate, but the air’s temperature of cabin is so high that the blower’s effect of ventilation is limited. The system proposes to use solar energy to drive the automobile blower and the thermoelectric cooler(TEC) in order to cool the cabin’s air, and use the air-conditioning condensate water collected during the driving process to cool the TEC’s hot end to improve the cooling efficiency.

It’s not easy to start the engine in winter, especially in frigid highlands, because the low temperature increases the fuel’s viscosity, decreasing the lubricating oil flow ability and the storage performance of battery. Current electrical heating method can improve the engine starting performance in low temperature condition, but this method adds an external power to the engine, leading to the engine cannot maintain an efficient energy utilization. A warming device using the solar energy is designed to conserve the energy during the daytime, and directly warm up the engine at the time when the engine turns off for a long time, especially during the night. A solar collector installed on the top of the vehicle is used to convert the solar energy to the thermal energy, which is then transferred to the heat accumulator that contain the phase-change medium which can increase the heat storage performance.

Eddy current retarder (ECR) shares a large market of auxiliary brakes in China, but shortcomings of the short continuous braking time and the high additional energy consumption are also obvious. The propose of combined braking partakes the braking torque of ECR. However, the existed serial-parallel braking strategy could hardly balance well the relationship between the braking stability and the energy recovery efficiency. This research puts forward an energy management strategy of combined braking system which aims to maximize energy recovery while ensure the brake stability. The motor speed, the braking request and the state of charge (SoC) of the storage module are analyzed synthetically to calculate the reasonable braking torque distribution proportion. And the recovered energy is priority for using in the braking unit to reduce the additional energy consumption in this strategy.