Work

A Personalized Navigation Route Recommendation Strategy Based on Differential Perceptron Tracking User’s Driving Preference

Year: 2023

Type: article

Abstract: With the increasing frequency of autonomous driving, more and more attention is paid to personalized path planning. However, the path selection preferences of users will change with internal or external factors. Therefore, this paper proposes a personalized path recommendation strategy that can track and study user’s path preference. First, we collect the data of the system, establish the relationship with the user preference factor, and get the user’s initial preference weight vector by dichotomizing the K‐means algorithm. The system then determines whether user preferences change based on a set threshold, and when the user’s preference changes, the current preference weight vector can be obtained by redefining the preference factor or calling difference perception. Finally, the road network is quantized separately according to the user preference weight vector, and the optimal path is obtained by using Tabu search algorithm. The simulation results of two scenarios show that the proposed strategy can meet the requirements of autopilot even when user preferences change.

Source: Computational Intelligence and Neuroscience

DOI: 10.1155/2023/8978398

Authors: Pengzhan Chen, Jihua Wu, Ning Li

Institutions: Taizhou University, Taizhou University

Language: English

Topic: Transportation Planning and Optimization

Subfield: Transportation

Field: Social Sciences

Domain: Social Sciences

Open Access status: hybrid

Estimated APC paid: $2,550

Funder: National Natural Science Foundation of China