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Successful visitor transport within large tourist sites should balance visitor experience and operating costs. Inspired by the model of sharing economy, we design a “user‐centered” intelligent visitor transport system to improve the efficiency and quality of experience of transport service in large tourist sites. The system's core approach is a three‐stage heuristic model based on Pareto optimality. Results of the proposed service indicate a drastic reduction of visitor delay time and an improvement in energy efficiency. The proposed scheduling schemes for organizers are more diversified and adaptable than the existing service.

Inspired by the success of the ride-sharing platform, this study designs an intelligent transport system for attractions that can effectively generate user demand-oriented vehicle operation schemes and timely adjust the scheme to match dynamic requests. The system’s core components are a vehicle operation scheme optimization module based on an improved heuristic approach and an adaptive updating module that follows time- and quantity-driven rules. Results of a case study in Xiamen indicate that our system significantly outperforms existing systems in improving tourist experience and saving transport operating costs and can provide more diversified and flexible vehicle operation schemes, thereby contributing to economic, social, and environmental benefits.

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