Intelligent Optimization Design of APP Display Interface for Intelligent Transportation
Abstract
The improvement of socio-economic conditions in China, and the increasing amount of urbanization and roadway construction have made the road traffic environment increasingly complex. Intelligent transportation application (APP) software plays an important role in alleviating traffic pressure and improving the efficiency of public transportation. The scale of the transportation system is huge and the travel needs of the masses are also diverse. The current APP display interface in intelligent transportation still has some defects in terms of function realization and user experience. To meet different user needs and improve user experience, in this study, in-depth research was conducted on the intelligent optimization design of APP display interface in intelligent transportation, analyzed functional requirement from the aspects of travel route planning, traffic information query and vehicle condition detection and optimized the design of APP display interface based on design principles such as ease-of-use and consistency. To determine the effectiveness of the proposed display interface, this article conducted experimental analysis from two aspects: performance testing and owner satisfaction testing. The results of the satisfaction testing showed that users who were very satisfied with the visual design effect, usability and interaction effect of the display interface of the intelligent transportation APP were 21.44%, 19.67% and 20.58%, respectively. The experimental results indicated that the intelligent optimization design of the APP display interface in intelligent transportation can effectively meet user needs, improving
their experience and satisfaction.
Keywords: display interface design, intelligent transportation, intelligent optimization, application performance, traffic information data
Cite As
C. Zhang, W. Gu, D. Kim, Y. Gu, "Intelligent Optimization Design of APP Display Interface
for Intelligent Transportation", Engineering Intelligent Systems, vol. 30 no. 4, pp. 349-358, 2024.