Intelligent Transportation Systems

Principal Investigator: Vaneet Aggarwal

The success of modern ride-sharing platforms crucially depends on the profit of the ride-sharing fleet operating companies, and how efficiently the resources are managed. Further, ride-sharing allows sharing costs and, hence, reduces the congestion and emission by making better use of vehicle capacities. The figure alongside depicts the improved performance of proposed strategy, DeepPool, for ride-sharing. The number of customers accepted are higher for same number of vehicles used and ride-sharing improves the costs, travel times, and number of customers served. The aspects are extended to joint pricing, matching, and dispatching problems. The approach is also used in freight management. 

 

Some papers are at:

• Xinwu Qian, Shuocheng Guo, and Vaneet Aggarwal, "DROP: Deep relocating option policy for optimal ride-hailing vehicle repositioning,"Transportation Research Part C, vol. 145, 103923, Dec 2022
• Kaushik Manchella, Marina Haliem, Vaneet Aggarwal, and Bharat Bhargava, "PassGoodPool: Joint Passengers and Goods Fleet Management with Reinforcement Learning aided Pricing, Matching, and Route Planning,"IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 4, pp. 3866-3877, April 2022
• Marina Haliem, Vaneet Aggarwal, and Bharat Bhargava, "AdaPool: A Diurnal-Adaptive Fleet Management Framework using Model-Free Deep Reinforcement Learning and Change Point Detection," IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 3, pp. 2471-2481, March 2022
• Marina Haliem, Ganapathy Mani, Vaneet Aggarwal, and Bharat Bhargava, "A Distributed Model-Free Ride-Sharing Approach for Joint Matching, Pricing, and Dispatching using Deep Reinforcement Learning," IEEE Transactions on Intelligent Transportation Systems, vol. 22, no. 12, pp. 7931-7942, Dec. 2021.
• Jiayu Chen, Abhishek K. Umrawal, Tian Lan, and Vaneet Aggarwal, "DeepFreight: A Model-free Deep-reinforcement-learning-based Algorithm for Multi-transfer Freight Delivery," in Proc. ICAPS, Aug 2021.
• Marina Haliem, Vaneet Aggarwal, and Bharat Bhargava, "AdaPool: An Adaptive Model-Free Ride-Sharing Approach for Vehicle Dispatching using Deep Reinforcement Learning," in Proc. ACM Buildsys, Nov. 2020
• Marina Haliem, Ganapathy Mani, Vaneet Aggarwal, and Bharat Bhargava, "Distributed Model-Free Ride-Sharing Algorithm with Pricing using Deep Reinforcement Learning," in Proc. ACM Computer Science in Cars Symposium (CSCS), Dec 2020
• K. Manchella, A. K. Umrawal, and V. Aggarwal, "FlexPool: A Distributed Model-Free Deep Reinforcement Learning Algorithm for Joint Passengers and Goods Transportation,"  IEEE Transactions on Intelligent Transportation Systems, vol. 22, no. 4, pp. 2035-2047, April 2021. 
• Kaushik Manchella, Marina Haliem, Vaneet Aggarwal, and Bharat Bhargava, "A Distributed Delivery-Fleet Management Framework using Deep Reinforcement Learning and Dynamic Multi-Hop Routing," in Proc. Neurips Workshop on Machine Learning for Autonomous Driving, Dec 2020
• Ashutosh Singh, Abubakr Alabbasi, and Vaneet Aggarwal, "A Distributed Model-Free Algorithm for Multi-hop Ride-sharing using Deep Reinforcement Learning," Accepted to IEEE Transactions on Intelligent Transportation Systems, May 2021.
• Ashutosh Singh, Abubakr Alabbasi, and Vaneet Aggarwal, "A Reinforcement Learning Based Algorithm for Multi-hop Ride-sharing: Model-free Approach," in Proc. Neurips Workshop, Dec 2019. 
• A. Al-Abassi, A. Ghosh, and V. Aggarwal, "DeepPool: Distributed Model-free Algorithm for Ride-sharing using Deep Reinforcement Learning," IEEE Transactions on Intelligent Transportation Systems, vol. 20, no. 12, pp. 4714-4727, Dec. 2019 (Featured as ICAPS 2020 journal paper).