Introduction – Addressing Core Industry Pain Points
The global micro-mobility landscape faces a persistent challenge: ensuring rider safety and operational efficiency for electric two-wheelers (e-scooters, e-bikes, electric motorcycles) as urban adoption accelerates. Conventional two-wheelers lack advanced driver-assistance systems (ADAS), real-time navigation, collision warning, and vehicle-to-vehicle (V2X) communication—features standard in modern cars. Riders face risks from blind spots, sudden braking, hazardous road conditions, and limited situational awareness. Manufacturers and fleet operators increasingly demand smart driving of two-wheelers—the integration of artificial intelligence (AI), IoT, sensors, and connectivity technologies into electric scooters, e-bikes, and motorcycles to enhance safety, efficiency, and user experience. These systems enable adaptive cruise control, collision warning, lane-keeping assistance, real-time navigation, energy-efficient riding modes, and V2X communication. Global Leading Market Research Publisher QYResearch announces the release of its latest report “Smart Driving of Two-wheelers – Global Market Share and Ranking, Overall Sales and Demand Forecast 2026-2032″. Based on current situation and impact historical analysis (2021-2025) and forecast calculations (2026-2032), this report provides a comprehensive analysis of the global Smart Driving of Two-wheelers market, including market size, share, demand, industry development status, and forecasts for the next few years.
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Market Sizing & Growth Trajectory
The global market for Smart Driving of Two-wheelers was estimated to be worth US$ 71.5 million in 2025 and is projected to reach US$ 122 million, growing at a CAGR of 8.1% from 2026 to 2032. In 2024, global Smart Driving of Two-wheelers revenue reached approximately US$ 63 million. According to QYResearch’s interim tracking (January–June 2026), the market is driven by: (1) accelerating adoption of electric two-wheelers (global e-scooter/e-bike sales estimated 40M+ units annually), (2) declining sensor and connectivity costs (LiDAR, radar, cameras, 5G/C-V2X modules), (3) government safety regulations and urban micro-mobility infrastructure investments. The intelligent connectivity segment dominates (45-50% market share), followed by intelligent interaction (30-35%) and other ADAS features (15-20%). Electric two-wheeled vehicles account for 70-75% of application demand.
独家观察 – From Basic Connectivity to Full ADAS for Two-Wheelers
Smart driving of two-wheelers encompasses three core technology categories:
- Intelligent Connectivity – 4G/5G telematics (real-time location, remote diagnostics, over-the-air updates), V2X (vehicle-to-vehicle, vehicle-to-infrastructure, vehicle-to-pedestrian), fleet management APIs (for shared scooter operators), and cloud-based analytics (riding patterns, battery optimization).
- Intelligent Interaction – Smart instrument clusters (TFT displays, smartphone mirroring), voice control (navigation, music, calls), gesture recognition, biometric authentication (fingerprint, face ID for scooter unlock), and haptic feedback (vibration alerts for navigation or hazards).
- Other (ADAS for Two-Wheelers) – Adaptive cruise control (maintains following distance using radar/camera), collision warning (forward, blind spot, rear cross-traffic), lane departure warning, automatic emergency braking (limited deployment, weight/size constraints), traction control (prevents wheel slip on wet surfaces), and cornering ABS (lean-angle sensitive braking).
From a discrete manufacturing perspective (vehicle assembly with electronic component integration), smart driving systems for two-wheelers differ from automotive ADAS through: (1) extreme miniaturization (limited space on handlebars/frame), (2) power constraints (battery-powered, low energy budget), (3) weatherproofing (IP65/IP67 for rain, dust, vibration), (4) cost sensitivity (targeting $50-500 per vehicle vs. $1,000-5,000 for automotive), and (5) rider acceptance (non-intrusive, must not distract).
Six-Month Trends (H1 2026)
Three trends reshape the market: (1) Radar-based blind spot detection – Compact 77GHz radar modules ($30-80) for rear and side monitoring, alerting riders to approaching vehicles; adoption by tier 1 scooter manufacturers (Niu, Yadea, Segway); (2) Shared scooter fleet intelligence – Remote speed limiting (geo-fencing in low-speed zones), no-parking detection (image recognition of sidewalk/street), and battery swapping optimization; operators report 15-25% reduction in citations and vandalism; (3) AI-powered predictive maintenance – Analyzing motor vibration, battery health, tire pressure, and brake wear to predict failures before they occur; integrated into connectivity platforms (HUAWEI, Qualcomm, Microchip).
User Case Example – Shared E-Scooter Fleet Optimization, Europe
A European shared e-scooter operator (12,000 vehicles across 15 cities) deployed intelligent connectivity and interaction solutions (Qualcomm + Nine Tech) from September 2025. Features: real-time telematics (GPS, cellular), remote diagnostics (battery, motor, brakes), geo-fencing (speed limits in pedestrian zones), and rider behavior analytics (hard braking, rapid acceleration). Results (March 2026 vs. pre-deployment): fleet utilization increased 22% (optimized redistribution based on demand patterns); maintenance costs reduced 31% (predictive alerts, remote diagnostics, fewer physical inspections); battery life extended 18% (adaptive charging based on usage patterns); safety incidents (reported collisions) reduced 35% (riders alerted to high-risk zones via app). Operator reported positive ROI within 9 months.
Technical Challenge – Sensor Fusion Under Size, Power, and Cost Constraints
A key technical challenge for smart driving of two-wheelers is fusing data from multiple sensors (camera, radar, IMU, GPS) while respecting size, power, and cost constraints that are more severe than automotive applications:
| Sensor | Automotive Cost | Two-Wheeler Cost | Power Consumption | Size | Two-Wheeler Feasibility |
|---|---|---|---|---|---|
| Camera (monocular) | $30-100 | $15-40 | 1-3W | Small | High (already deployed) |
| Radar (77GHz) | $50-200 | $30-80 | 2-5W | Small-Medium | Emerging |
| LiDAR (solid-state) | $500-2,000 | $200-500 | 5-15W | Medium | Low (cost, power) |
| Ultrasonic | $10-30 | $5-15 | 0.5-1W | Small | High (parking, low-speed) |
| IMU (6/9-axis) | $5-20 | $3-10 | 0.1-0.5W | Very small | High (standard) |
| GPS (multi-band) | $20-50 | $10-30 | 0.5-1W | Very small | High (standard) |
Power constraints are particularly challenging for battery-electric two-wheelers (range anxiety already exists). ADAS features must consume <5W total to avoid meaningful range reduction. Solution approaches: (1) event-triggered wake-up (sensors idle most of time), (2) edge processing (on-device inference to avoid cloud round-trips), (3) integration with existing scooter ECUs (sharing power, CAN bus).
独家观察 – Intelligent Connectivity vs. Intelligent Interaction
| Feature Category | Key Components | Target Value Proposition | Adoption Rate (2026) | Key Providers |
|---|---|---|---|---|
| Intelligent Connectivity | 4G/5G module, GPS, accelerometer, cloud platform | Fleet management, theft recovery, remote diagnostics, OTA updates | 60-70% (new e-scooters) | Qualcomm, HUAWEI, Microchip, Abup Technology |
| Intelligent Interaction | TFT display, Bluetooth, voice assistant, touch/grip sensors | Rider convenience, navigation, music, call handling | 25-35% (premium models) | Cerence, Nine Tech, BOSCH |
| ADAS (emerging) | Radar, camera, IMU, control unit | Collision avoidance, adaptive cruise, lane keeping | 5-10% (high-end, early adopter) | BOSCH, HUAWEI, Qualcomm |
Downstream Demand & Competitive Landscape
Applications: Electric Two-wheeled Vehicles (e-scooters, e-bikes – largest segment, 70-75% market share), Motorcycles (higher-end, premium models – faster-growing from lower base). Key players: Microchip (telematics/connectivity), BOSCH (sensors, ADAS, ABS), Qualcomm (Snapdragon platforms, 5G/V2X), HUAWEI (full-stack: connectivity, cloud, sensors), Abup Technology (OTA and device management), Cerence Communications Technology (voice AI), Nine Tech Co., Ltd. (shared scooter intelligence). The market is transitioning from basic connectivity (telematics, GPS tracking) to full ADAS integration (radar, automatic emergency braking) as component costs decline.
Segmentation Summary
The Smart Driving of Two-wheelers market is segmented as below:
Segment by Type – Intelligent Connectivity (largest, telematics, fleet management), Intelligent Interaction (TFT displays, voice control, biometrics), Other (ADAS: collision warning, adaptive cruise, lane keeping – fastest-growing)
Segment by Application – Electric Two-wheeled Vehicles (dominant, 70-75% share), Motorcycles (premium, emerging)
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