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To address the issue of high energy consumption in battery electric buses at signalized intersections, this paper proposes an eco-driving optimization model based on the Twin Delayed Deep Deterministic (TD3) policy gradient algorithm. First, a simulation training platform is developed using SUMO, which balances energy consumption, travel efficiency, comfort, and safety in a multi-objective optimized reinforcement learning reward function. Next, an eco-driving optimization model is created within the TD3 framework, tailored to the operational characteristics of electric buses at signalized intersections, and its parameters are trained. Finally, the performance of the proposed model is validated against the classic intersection passage strategy, Green Light Optimal Speed Advisory (GLOSA). The results show that the proposed eco-driving strategy reduces energy consumption by 9.82%, 26.13%， 19.00% and 14.51% in four typical intersection scenarios, while also maintaining vehicle safety, comfort, and travel efficiency.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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