To make better use of agricultural residues and solve the problem of residues pollution, it is necessary to carry out regional management, which means spatial planning of the entire region is essential. This study developed a methodology based on GIS for determining the suitable locations, optimal sizes and number of biogas plants for the entire region while meeting the conditions that all biomass can be collected. Based on the optimization of transportation distance, the nearest facility model and the modified location allocation model were used to obtain the correspondence between plants and supply points, the transportation path and the plants’ capacity under different numbers of plants. Based on economic optimization, the economic model was constructed to calculate the total cost of different numbers of biogas plants and the optimal number was obtained after comparing. The cross path was adjusted for the selected plan to ensure that there was no crossover in the plants’ collection area. This approach was applied (as a case study) in Funan County, Anhui Province. Based on the existing results, the optimal construction number of biogas plants in the region was 9.

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Recently, the ever-increasing vehicle population has become a severe challenge to traffic safety, especially the problem of a single-vehicle overtaking a platoon on the Two-Lane Two-Way (TLTW) road. Platooning has the potential to improve traffic efficiency and safety. However, there exists a perilous situation of ''Neither overtake nor give up'' when the single-vehicle overtakes a platoon on the TLTW road. This paper presents a flexible framework to automatically filter a large quantity of Advanced Driver Assistance Strategies (ADAS) and select the most suitable driver assistance information for the single-vehicle overtakes a platoon on the TLTW road. A step-by-step Single Vehicle Overtakes Platoon (SVOP) algorithm is designed to generate the coarse ADAS, which had given plenty of consideration to the vehicle safety, traffic efficiency, and driving comfort. Then, this paper obtains the raw data about the single-vehicle overtakes a platoon on the TLTW by using CARLA, which can help us to get 20 drivers' upper and down boundaries of both velocity and acceleration. In addition, the extracted ranges of velocity and acceleration are used to quantitatively analyse the drivers' driving features and filter the ADAS information. Finally, a Bayesian nonparametric approach is developed to segment driver's driving raw data temporal sequences into small analytically interpretable components without using prior knowledge. So that the accurately overtaking characteristics can be obtained, and the ADAS can be further filtered. Experimental results demonstrate that the obtained coarse ADAS are only valid in theory but not acceptable by most of the drivers. Nonetheless, by leveraging the nonparametric Bayes algorithm, the driver's overtaking behavior can be divided into different primitives, from which some could obtain the driver's acceptance range for the velocity and acceleration. 92.3% ∼ 94.78% invalid SVOP ADAS could be filtered out by leveraging the primitive-based SVOP approach. Thus, after filtering, the overtaking scheme is the most acceptable strategy for drivers. INDEX TERMS Two-lane two-way, single vehicle overtaking platoon, non-parametric Bayesian algorithm, advanced driver assistance systems.

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