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In order to improve the traffic efficiency and fuel utilization efficiency of intelligent connected vehicles （ICVs） under urban traffic networks，a multilane spatiotemporal trajectory optimization method is proposed in this paper. Firstly，the state and constraints of the ICVs are defined based on the multi-lane spatiotemporal position relationship and the compound optimization model of spatiotemporal trajectory is constructed by considering the traffic efficiency and fuel economy，which is solved by the Pontryagin Maximum algorithm. Furthermore，the rules of cooperative lane change are designed to obtain the optimal lane change strategy by Q-learning algorithm. Finally，the SUMO/Python co-simulation tests show that the method can effectively improve the traffic efficiency under different vehicle saturation levels，split allocation，and minimum traffic speed conditions，with great improvement of fuel 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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