Arian’s Thesis Defense

We are happy to congratulate Dr. Arian Houshmand on his successful Ph.D. defense on May 2020. Although his defense was held virtual given the current worldwide health crisis, he managed to captivate the interest of the attendees (from several parts of the globe) by showing the results of his research on Eco-routing and Scheduling of Connected and Autonomous Vehicles (CAVs).

Arian Houshmand, minutes before starting his dissertation.

Arian arrived at Boston University in 2016 after receiving his B.S and M.S. in Mechanical Engineering at the Sharif University of Technology and at the University of Cincinnati, respectively. Since his arrival at BU, Arian showed deep interest in joining the CODES Lab to become an expert in the Connected and Automated Vehicles field. In his work, he takes advantage of the benefit that connectivity brings to self-driving cars. He uses connectivity to reduce harmful emissions and alleviate traffic congestion in traffic networks.  Specifically, his thesis tackles these challenges by proposing algorithms that make high-level routing decisions of CAVs.

The first section of his dissertation focuses on eco-routing (finding the energy-optimal route) for Plug-In Hybrid Electric Vehicles (PHEVs). He proposed several algorithms that simultaneously calculate an energy-optimal route (eco-route) and an the optimal power-train control strategy along the route. The results show significant energy savings for PHEVs with a near real-time execution time for the algorithms. To read more, please read this paper.

Visualization of eco-route and fastest route on the Boston Transportation Network.

The second half of this dissertation tackles the problem of routing fleets of CAVs in the presence of mixed traffic (coexistence of regular vehicles and CAVs). In this setting, all CAVs are assumed to belong to the same fleet and are routed using a centralized controller. The routing objective is to minimize a given overall fleet traveling cost (travel time or energy consumption). In addition, it assumed that regular vehicles (non-CAVs) choose their routes selfishly to minimize their individual traveling time. This work develops a framework that deals with the routing interaction between CAVs and regular vehicles under different penetration rates (fractions) of CAVs. The results suggest that collaborative routing decisions of CAVs improve not only the cost of CAVs but also that of the non-CAVs. To read more, please read this paper.

The centralized controller is assigning routes to CAVs entering the network. Red, blue, and green links show three different routes for CAVs.

By the end of his dissertation, someone asked Arian to tell us about what, from his research, was the result he was proudest of. Without hesitation he answered the fact that in his research he validated his theory and algorithms with both computer simulations and real vehicles in the road. This highlights his desire for the applicability of his work both in academia and industry.

Without a doubt, Arian excelled at BU and set an example for his labmates at the CODES lab. Apart from his academic success, he won multiple times as best presenter during the Graduate Student Workshop (CGSW) at BU (see note). He now joined Zoox, a self-driving company owned by Amazon, where he is working on the planning and control team. We wish him a successful carrier and hope to see him around soon.

Dr. Houshmand at the 2019 ARPA-E Innovation Summit in Denver

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