PhD Forum: toward a Human-In-The-Loop Smart Ridesharing System with Self-Driving Technologies
The overloaded transportation networks in big modern cities have always been a severe issue, resulting in congestion, environmental pollution, waste of energy, and of people's time and money. In this paper, we will discuss the potential solutions that could be offered by the utilization of a flexible ridesharing system. We will discuss the current standings of existing ridesharing tools and then propose a new flexible ridesharing system that is specifically designed to meet users' time constraints and to increase user satisfaction when there are dynamic road conditions such as traffic incidents. The proposed system is robust in user and traffic flexibility through the use of two main components: Transferring and incentive protocols. We will discuss the necessity for the dynamic road network adaptation and the probabilistic stable routing model, and how they impact the two main components. For final remarks, we will also discuss the challenges of deploying such system into an intelligent transportation system, which includes keeping humans (users) in the loop and adapting to the self-driving technologies.
S. Yeung, "PhD Forum: toward a Human-In-The-Loop Smart Ridesharing System with Self-Driving Technologies," Proceedings of the 2017 IEEE International Conference on Smart Computing (2017, Hong Kong), Institute of Electrical and Electronics Engineers (IEEE), May 2017.
The definitive version is available at https://doi.org/10.1109/SMARTCOMP.2017.7947051
2017 IEEE International Conference on Smart Computing, SMARTCOMP 2017 (2017: May 29-31, Hong Kong)
Keywords and Phrases
Intelligent systems; Roads and streets; Traffic congestion, Dynamic road networks; Environmental pollutions; Human-in-the-loop; Intelligent transportation systems; Overloaded transportations; Time constraints; Traffic incidents; User satisfaction, Transportation
International Standard Book Number (ISBN)
Article - Conference proceedings
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01 May 2017