講座名稱：Eco-driving of Autonomous Vehicles Approaching Multiple Signalized Intersections

講座人：孟祥宇 副教授

講座時(shí)間：7月15日10:00

講座地點(diǎn)：騰訊會(huì)議直播（ID:219 123 301https://meeting.tencent.com/s/qHWj29FJdisK）

講座人介紹：

孟祥宇，現(xiàn)任美國路易斯安那州立大學(xué)電氣與計(jì)算機(jī)工程系副教授。他在加拿大阿爾伯塔大學(xué)電氣與計(jì)算機(jī)工程系獲得控制系統(tǒng)博士學(xué)位。2014年12月至2016年12月，新加坡南洋理工大學(xué)電氣與電子工程學(xué)院任職Research Fellow。 2017年1月至2018年12月，美國波士頓大學(xué)系統(tǒng)工程系，博士后。他的研究興趣包括多智能體系統(tǒng)的事件觸發(fā)控制、節(jié)能多智能體覆蓋控制和聯(lián)網(wǎng)自動(dòng)駕駛汽車的生態(tài)駕駛。

講座內(nèi)容：

Connected and automated vehicles provide an intriguing opportunity for enabling users to better monitor transportation network conditions and to improve traffic flow. Their proliferation has rapidly grown, largely as a result of Vehicle-to-X technology which refers to an intelligent transportation system where all vehicles and infrastructure components are interconnected with each other. Such connectivity provides precise knowledge of the traffic situation across the entire road network, which in turn helps optimize traffic flows, enhance safety, reduce congestion, and minimize emissions. This talk will present the problem of optimally controlling trajectories of autonomous vehicles to jointly minimize travel time and energy consumption in the presence of multiple signalized intersections, which are modeled as spatiotemporal constraints on these trajectories. In addition to state and input constraints, the spatial equality and temporal inequality constraints can be viewed as interior-point constraints. This problem is addressed by first identifying the structure of the optimal acceleration profile and showing that it is characterized by several parameters subsequently used for trajectory design optimization. Therefore, the infinite dimensional optimal control problem is transformed into a finite dimensional parametric optimization problem. The simulation results show quantitatively the advantages of the proposed algorithm in terms of energy consumption and travel time.

主辦單位：機(jī)電工程學(xué)院