By utilizing artificial intelligence (AI), big data, the Internet of Things (IoT), 5G, and cloud computing technologies, we aim to create a secure, efficient, green, and personalized future travel ecosystem. Our mission is to make travel smarter, more convenient, and more sustainable, providing comprehensive intelligent travel solutions for governments, businesses, and individuals.
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1、 Market background and demand
1. Pain points in urban transportation
·Severe congestion: low traffic efficiency during morning and evening rush hours, and high commuting time costs.
·Difficulty in parking: Parking resources are scarce, and finding a parking spot takes time and consumes fuel.
·Frequent accidents: human driving errors and traffic violations lead to safety hazards.
·High carbon emissions: Fuel vehicles account for a large proportion, and traffic pollution affects urban air quality.
2. Policies and Trends
·National policy: The country vigorously promotes "new infrastructure", "smart cities", and "dual carbon goals", with intelligent transportation becoming a key development direction.
·Technological maturity: The rapid development of technologies such as 5G, AI, and autonomous driving provides support for intelligent travel.
·User demand: Consumers' demand for personalized, convenient, and green travel is increasing day by day.
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2、 Core solution
1. Smart Navigation and Travel Planning (MaaS)
·Multi mode travel integration: integrating public transportation, subway, shared bicycles, ride hailing services, etc., providing one-stop travel planning.
·Dynamic route optimization: Based on real-time road conditions, weather, construction and other information, intelligently recommend the optimal route.
·AR real-life navigation: Combining augmented reality (AR) technology to provide a more intuitive navigation experience.
2. Intelligent parking system
·Real time monitoring of parking spaces: Detecting the occupancy of parking spaces through geomagnetic/camera sensors and guiding vehicles to park quickly.
·Unconscious payment: supports ETC and license plate recognition automatic deduction, reducing manual intervention.
·Off peak shared parking: Integrate parking resources in commercial and residential areas to improve parking utilization.
3. Vehicle to Road Collaboration (V2X)
·Intelligent traffic lights: dynamically adjust the timing of traffic lights to reduce waiting time.
·Protection of vulnerable traffic participants: Identify pedestrians and non motorized vehicles to reduce the risk of accidents.
·Autonomous driving support: providing high-precision traffic data for intelligent connected vehicles.
4. Optimization of shared travel
·Intelligent scheduling algorithm: Based on spatiotemporal prediction, optimize the distribution of shared bicycles and ride hailing services to reduce empty driving rates.
·Carbon point incentive: Encourage users to choose low-carbon travel methods (such as public transportation and bike sharing) and redeem rewards.
5. Intelligent services for new energy vehicles
·Intelligent navigation for charging stations: Real time display of available charging stations, supporting reserved charging.
·Battery health management: AI predicts battery degradation, optimizes charging strategies, and extends battery life.
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3、 Technical advantages
✅ AI+Big Data Driven: Deep learning algorithms achieve high-precision traffic prediction and optimization.
✅ 5G low latency communication: supports real-time interaction of vehicle to road collaboration (V2X).
✅ Cloud edge end collaboration: edge computing reduces latency and cloud platform achieves global optimization.
✅ Open ecosystem: supports interconnection with map manufacturers, car companies, and travel platform APIs.
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4、 Application scenarios
1. Smart city traffic management
·Relieve morning and evening rush hour congestion
·Optimize bus routes and signal timing
·Reduce traffic accident rate
2. Smart Park/Scenic Area
·Unmanned shuttle bus
·Intelligent parking guidance
·Management of pedestrian and vehicle separation
3. Highways
·Intelligent speed limit control
·Automatic detection and warning of accidents
·Adverse weather traffic management
4. Personal travel
·Personalized navigation recommendations
·Optimization of shared travel
·Carbon footprint recording and incentives
