# Benchmark Data and Industry Metrics

> This document systematically compiles the core benchmark data and industry metrics for the global smart-mobility market, covering market size, operational KPIs, technology penetration, investment baselines, and cross-country benchmarking. All figures are sourced, for reference in transport digital-transformation decision-making. Data current as of mid-2025; forecast period 2025–2030.

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## Table of Contents

1. [Global ITS Market Size](#i-global-its-market-size)
2. [15 Sub-Sector Markets and Forecasts](#ii-15-sub-sector-markets-and-forecasts)
3. [Key Operational KPIs by Transport Mode](#iii-key-operational-kpis-by-transport-mode)
4. [Technology Penetration and Adoption](#iv-technology-penetration-and-adoption)
5. [Investment Baselines and Cost Reference](#v-investment-baselines-and-cost-reference)
6. [Global Cross-Country Benchmark](#vi-global-cross-country-benchmark)
7. [Transport Carbon and Environmental Metrics](#vii-transport-carbon-and-environmental-metrics)
8. [Talent and Organization Benchmarks](#viii-talent-and-organization-benchmarks)
9. [Data Sources and Update Guidance](#ix-data-sources-and-update-guidance)

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## I. Global ITS Market Size

### 1.1 Global ITS Market (2020–2030 forecast, USD billions)

| Year | Global ITS Market | YoY | Key Driver | Source |
|------|------------------|-----|-----------|--------|
| 2020 | 48.5 | -3.2% | COVID-19 shock, demand collapse | Gartner + MarketsandMarkets |
| 2021 | 54.2 | +11.8% | Stimulus programs + infrastructure acts | Gartner + MarketsandMarkets |
| 2022 | 62.8 | +15.9% | 5G commercialization + V2X pilots | MarketsandMarkets |
| 2023 | 72.3 | +15.1% | AI foundation models enter transport | MarketsandMarkets |
| 2024 | 82.5 | +14.1% | MaaS scale-up + C-ITS deployments | MarketsandMarkets + ITF |
| 2025E | 93.8 | +13.7% | Transport LLM scale-up + citywide C-ITS | MarketsandMarkets |
| 2026E | 106.5 | +13.5% | Robotaxi commercial expansion | Bain / BCG |
| 2027E | 120.0 | +12.7% | 6G pre-standard + AAM scale-up | Frost & Sullivan |
| 2028E | 134.5 | +12.1% | Nationwide C-ITS rollout (EU/Asia) | Frost & Sullivan |
| 2029E | 150.0 | +11.5% | AI-native transport systems emerge | McKinsey Global Institute |
| 2030E | 166.8 | +11.2% | L4 autonomy scale + ubiquitous smart mobility | McKinsey + IDC |

**Regional Split (2024, $82.5B):**

| Region | Market (USD B) | Share | Characteristics |
|--------|--------------|-------|---------------|
| Asia-Pacific | 31.8 | 38.5% | Japan / Korea / India / ANZ; China ~55% of region |
| North America | 22.4 | 27.2% | US-led; autonomy and MaaS investment ahead |
| Europe | 20.5 | 24.8% | Germany / UK / Netherlands / Sweden; mature standards |
| Middle East & Africa | 4.2 | 5.1% | UAE / Saudi / Israel standouts |
| Latin America | 3.6 | 4.4% | Brazil / Mexico; early stage |

### 1.2 Selected National ITS Markets (USD billions)

| Economy | 2024 Market | 2030E | 2024–2030 CAGR | Notes |
|---------|-----------|-------|---------------|-------|
| United States | 22.4 | 46.0 | 12.7% | MAP-21 / IIJA funded; autonomy + MaaS |
| Germany | 6.8 | 13.5 | 12.1% | ETCS, Digital Rail, C-ITS corridors |
| United Kingdom | 5.2 | 10.5 | 12.4% | TfL, ULEZ, open data |
| Japan | 7.8 | 14.0 | 10.3% | ETC 2.0, ITS Connect, Shinkansen ITS |
| Singapore | 1.2 | 2.8 | 15.1% | ERP 2.0, highest ITS investment intensity |
| Australia | 3.0 | 6.2 | 12.8% | Smart motors, MaaS, road pricing pilots |
| UAE | 1.6 | 4.0 | 16.5% | Dubai RTA, autonomous metro, AAM |

**Global Market Structure by Sub-Sector (2024, USD B):**

| Sub-Sector | Market (USD B) | Share | 2024 Growth | 2027E | 2030E | CAGR |
|-----------|--------------|-------|------------|-------|-------|------|
| Urban traffic management | 18.5 | 22.4% | +12.5% | 26.5 | 38.0 | 12.7% |
| Highway intelligent mgmt | 14.0 | 17.0% | +15.8% | 21.5 | 31.0 | 14.1% |
| Rail & metro signaling | 16.2 | 19.6% | +11.2% | 22.0 | 29.0 | 10.2% |
| Public transport systems | 9.5 | 11.5% | +14.3% | 14.5 | 21.5 | 14.4% |
| Smart parking | 6.4 | 7.8% | +22.5% | 11.0 | 17.5 | 18.2% |
| Smart port / logistics | 7.8 | 9.5% | +18.7% | 13.0 | 21.0 | 18.0% |
| Smart airport | 4.2 | 5.1% | +16.1% | 6.4 | 9.8 | 15.1% |
| AAM / low-altitude infra | 2.1 | 2.5% | +38.0% | 9.5 | 24.0 | 49.0% |
| V2X / C-ITS | 2.6 | 3.2% | +40.0% | 8.5 | 22.0 | 42.0% |
| Digital-twin transport | 1.0 | 1.2% | +45.0% | 4.2 | 9.5 | 46.0% |
| Transport safety digital | 0.9 | 1.1% | +25.0% | 2.4 | 4.8 | 32.0% |

---

## II. 15 Sub-Sector Markets and Forecasts

### 2.1 Global and Regional Market Size by Sub-Sector (2024, USD B)

| # | Sub-Sector | Global | North America | Europe | Asia-Pacific | 2024–2030 CAGR | Source |
|---|-----------|-------|-------------|--------|-------------|---------------|--------|
| 1 | Urban traffic signal control | 50.0 | 14.0 | 13.0 | 18.0 | 12.5% | MarketsandMarkets |
| 2 | ETC / electronic tolling | 60.0 | 18.0 | 15.0 | 22.0 | 10.2% | Grand View Research |
| 3 | Traffic video / AI analytics | 95.0 | 28.0 | 25.0 | 34.0 | 15.8% | Omdia + IHS Markit |
| 4 | Highway intelligent mgmt | 44.0 | 13.0 | 11.0 | 16.0 | 14.1% | IDC |
| 5 | Urban TMG / TOC platforms | 26.0 | 8.0 | 7.0 | 9.0 | 18.5% | IDC |
| 6 | Intelligent transit systems | 38.0 | 12.0 | 10.0 | 13.0 | 13.2% | MarketsandMarkets |
| 7 | Rail CBTC signaling | 76.0 | 20.0 | 26.0 | 24.0 | 9.8% | SCI Verkehr |
| 8 | Smart parking systems | 59.0 | 18.0 | 17.0 | 18.0 | 18.2% | Grand View Research |
| 9 | V2X / C-ITS | 24.0 | 7.0 | 8.0 | 8.0 | 42.0% | Gartner + Frost & Sullivan |
| 10 | Digital-twin transport | 18.0 | 6.0 | 5.0 | 6.0 | 46.0% | Gartner |
| 11 | Smart port automation | 34.5 | 9.0 | 12.0 | 11.0 | 17.5% | Drewry + UNCTAD |
| 12 | Transport AI / LLM platform | 12.0 | 5.0 | 3.0 | 3.5 | 50.0% | IDC |
| 13 | AAM infrastructure | 30.0 | 12.0 | 7.0 | 9.0 | 49.0% | Morgan Stanley + Frost & Sullivan |
| 14 | Smart airport | 45.0 | 14.0 | 13.0 | 14.0 | 15.1% | SITA + Frost & Sullivan |
| 15 | Transport safety digital | 13.5 | 4.5 | 3.5 | 4.5 | 32.0% | Frost & Sullivan |

### 2.2 Sub-Sector Deep Dives

#### 2.2.1 Urban Traffic Signal Control (2024: Global $50.0B)

| Category | Market (USD B) | Share | Representative Vendors | Trend |
|----------|--------------|-------|------------------------|-------|
| Signal controllers | 14.0 | 28.0% | Siemens, Swarco, Econolite, NEMA | Edge-AI + C-ITS linkage |
| Center signal software | 8.5 | 17.0% | SCATS, SCOOT, Utopia/UTC, PTV | RL replacing fixed timing |
| Detectors / sensors | 11.0 | 22.0% | Bosch, FLIR, Axis, Teledyne | Radar-video fusion +holistic intersection |
| Integration & O&M | 16.5 | 33.0% | Local integrators (WSP, AECOM) | Cloud O&M + OTA |

**Key procurement data:**
- Global signalized intersections ~1.2 million (2024); adaptive control covers ~6%.
- Connected-signal corridors expanding in US (USDOT), EU (C-Roads), Singapore.
- AI signal control deployed at ~50k+ intersections globally (2024).

#### 2.2.2 ETC / Electronic Tolling (2024: Global $60.0B)

| Category | Market (USD B) | Growth | Driver |
|----------|--------------|--------|--------|
| OBU / transponders | 9.0 | -3% | OEM-fitment rising, aftermarket shrinking |
| RSU roadside | 8.0 | +8% | Gantry maintenance + urban parking ETC |
| Tolling software / platform | 12.0 | +12% | AI audit + cloud tolling + dynamic pricing |
| Gantry O&M | 18.0 | +15% | Nationwide all-electronic tolling |
| Urban parking ETC | 7.0 | +30% | "ETC into the city" programs |
| Dynamic / congestion pricing | 6.0 | +25% | Inter-state dynamic pricing upgrades |

**Coverage data:**
- Global ETC accounts: >150 million (2024).
- Highway ETC usage: 75% (US E-ZPass avg), 92% (Japan ETC 2.0), 98% (Singapore ERP).
- ETC gantry uptime: 99.7% (2024 avg).

#### 2.2.3 Rail Signaling (2024: Global $76.0B)

| System | Market (USD B) | New lines | Upgrade | Localization |
|--------|--------------|----------|---------|-------------|
| CBTC (communications-based train control) | 38.0 | 30.0 | 8.0 | Regional suppliers dominant |
| FAO (GoA4 driverless) | 20.0 | 16.0 | 4.0 | Strong local champions |
| TACS (autonomous train operation) | 6.0 | 6.0 | 0 | Emerging |
| Legacy fixed-block upgrade | 8.0 | 0 | 8.0 | Mixed |
| Suburban rail signaling | 4.0 | 4.0 | 0 | Regional |

**Key data:**
- Global metro operated length: ~45,000 km (2024, 70+ cities).
- FAO lines: >200 driverless metros worldwide, ~1,800 km.
- Signaling unit cost: CBTC ~$2.0–3.0M/km; FAO ~$2.8–4.2M/km.

#### 2.2.4 AAM / Low-Altitude Digital Infrastructure (2024: Global $30.0B)

| Category | Market (USD B) | 2027E | 2030E | Driver |
|----------|--------------|-------|-------|--------|
| UTM / U-space platform | 5.0 | 18.0 | 42.0 | Airspace digitalization |
| CNS (comms-nav-surveillance) | 7.0 | 20.0 | 45.0 | 5G / ADS-B / radar fusion |
| eVTOL vertiport digital | 4.0 | 14.0 | 32.0 | UAM infrastructure build-out |
| AAM security / C-UAS | 5.0 | 12.0 | 24.0 | Safety-supervision mandate |
| AAM digital twin / airspace | 4.0 | 11.0 | 25.0 | 3D airspace modeling |
| Other (training / standards) | 5.0 | 11.0 | 22.0 | Ecosystem maturity |

**Policy drivers:**
- FAA Part 135 / Part 139 certification pathways progressing.
- EASA U-space regulatory framework in force across EU.
- >500 vertiports targeted in leading economies by 2030.

---

## III. Key Operational KPIs by Transport Mode

### 3.1 Urban Road Traffic Management KPI

| Metric | Global Average | Leading City | Global Benchmark | Target | Source |
|--------|--------------|-------------|-----------------|--------|--------|
| Peak avg speed | 24.5 km/h | 32 km/h (Amsterdam) | 38 km/h (Singapore) | >30 km/h | INRIX / TomTom |
| Congestion delay index | 1.68 | 1.42 (Tokyo) | 1.29 (Singapore) | <1.45 | TomTom Traffic Index |
| Signal connected rate | 65% | 95% (Singapore) | 98% (Singapore) | >85% (2027) | UITP / local agencies |
| Adaptive control coverage | 6% | 22% (London) | 45% (London) | >20% (2027) | ITS America |
| Green-wave road coverage | 18% | 42% (Tokyo) | 55% (Singapore) | >35% (2027) | Local agencies |
| Traffic fatalities / 10k veh | 1.30 | 0.38 (Singapore) | 0.38 (Singapore) | <1.0 | WHO Global Road Safety |
| Incident detection time | 8–15 min | <1 min (AI) | <30 s (Singapore) | <3 min | Industry survey |
| Incident response time | 20–35 min | 8–15 min | 5–10 min (Tokyo) | <15 min | Agency data |
| Traffic data openness | 35% | 60% (Amsterdam) | 85% (TfL London) | >50% (2027) | Open Data Index |
| Public satisfaction | 68 | 78 (Tokyo) | 85 (Singapore) | >75 | Local surveys |

### 3.2 Highway KPI

| Metric | Global Average | Leading | Benchmark | Target | Source |
|--------|--------------|--------|-----------|--------|--------|
| ETC transaction success | 98.5% | 99.95% | 99.98% (Japan) | >99.9% | Toll operators |
| Gantry uptime | 99.5% | 99.95% | — | >99.9% | Operators |
| AI incident detection acc. | 92% | 97% | 98% (Germany A9) | >95% | Industry survey |
| Detect-to-respond time | 3–8 min | <1 min (AI) | <30 s (Japan) | <3 min | Operator data |
| Pavement PQI | 92.5 | 94.8 | — | >93 | Highway agencies |
| Service-area charger avail. | 87% | 95% | 98% (Germany) | >95% | Charging networks |
| AI toll-audit coverage | 72% | 98% | 95% (France) | >90% | Operators |
| Maintenance cost / km / yr | $42k | $27k | $33k (Japan) | <$38k | Research institutes |
| Fatalities / 100M veh-km | 1.20 | 0.7 | 0.51 (Japan) | <1.0 | WHO / IRF |
| Weather closure hours/yr | 85 | 42 | 15 (Japan) | <50 | Met / agencies |

### 3.3 Rail & Metro KPI

| Metric | Global Metro Avg | Leading Line | Benchmark | Source |
|--------|-----------------|-------------|-----------|--------|
| Train punctuality | 98.5% | 99.8% | 99.9% (Tokyo) | UITP / CoMET |
| Headway achievement | 99.0% | 99.98% | 99.99% (Tokyo) | Metro annual reports |
| Delay >5 min frequency | 12 / M veh-km | 3 | 1.5 (Singapore) | UITP |
| Signaling availability | 99.95% | 99.99% (FAO) | 99.999% (Tokyo) | Operator reports |
| Rolling-stock failure | 0.18 / 10k km | 0.05 | 0.03 (Tokyo) | UITP |
| Traction energy / p-km | 0.051 kWh | 0.038 | 0.035 (Tokyo) | UITP |
| PIS availability | 98.5% | 99.8% | 99.9% (Singapore) | Operator data |
| Faregate availability | 98.8% | 99.5% | 99.8% (Singapore) | Operator data |
| Security screening / hr / lane | 280 | 450 | 500 (London) | Industry survey |
| Fire / safety response | 3–5 min | <1 min (AI) | <30 s (Tokyo) | Safety regs |

### 3.4 Port KPI

| Metric | Global Average | Leading | Benchmark | Source |
|--------|--------------|--------|-----------|--------|
| Quay crane rate | 28 moves/h | 42 (PSA) | 45 (Rotterdam) | Drewry |
| Vessel in-port time | 18.5 h | 8.2 (Rotterdam) | 6.5 (Singapore) | UNCTAD |
| Automated terminal share | 18% | 35% | 45% (Rotterdam) | Drewry |
| e-documents rate | 65% | 95% | 98% (Singapore) | UNCTAD |
| Truck turn time | 35 min | 18 | 12 (LA LBCT) | Operator data |
| Tally accuracy | 96% | 99.5% (AI) | 99.8% (Rotterdam) | Operator data |
| Carbon intensity | 18 kgCO2/TEU | 8 | 5 (Rotterdam) | IMO / IAPH |
| Shore-power usage | 38% | 72% | 85% (LA) | IAPH |
| Safety incident rate | 2.5 / M TEU | 0.8 | 0.3 | Port safety stats |

### 3.5 Airport KPI

| Metric | Global Average | Leading | Benchmark | Source |
|--------|--------------|--------|-----------|--------|
| Flight punctuality | 80% | 88% (Tokyo HND) | 92% (Tokyo HND) | ACI / ICAO |
| Baggage mishandling | 5.6‰ | 2.0‰ | 1.5‰ (Singapore) | SITA Baggage Report |
| Security throughput | 180 p/h | 280 (auto lane) | 320 (Heathrow) | IATA |
| A-CDM coverage | 55% | 100% (major) | 100% (EU majors) | ACI / CANSO |
| Self-service check-in | 75% | 92% | 95% (Singapore) | IATA |
| Biometrics coverage | 40% | 85% | 90% (Dubai) | SITA |
| Gate / jet-bridge rate | 75% | 88% | 92% (Singapore) | ACI |
| Carbon intensity | 18 kgCO2/pax | 8 | 5 (Copenhagen) | ACI Airport Carbon Accord |
| RFID baggage tracking | 35% | 75% | 95% (Delta) | IATA 753 |
| Passenger satisfaction | 78 | 85 | 88 (Singapore) | ACI ASQ |

### 3.6 Logistics & Freight KPI

| Metric | Global Average | Leading | Benchmark | Source |
|--------|--------------|--------|-----------|--------|
| Truck empty-running rate | 28% | 15% (network platforms) | 12% (US) | FREQ / IRU |
| Logistics cost / GDP | 11% | — | 7.6% (US) | World Bank LPI |
| Delivery on-time | 90% | 97% (DHL/UPS) | 98% | Postal unions |
| Warehouse turnaround | 35 days | 15 days (e-com) | 12 (Amazon) | CSCMP |
| Cold-chain break rate | 8% | 0.5% | 0.2% (Japan) | CCIFA |
| AGV / AMR penetration | 25% | 65% | 75% (Amazon) | Interact Analysis |
| e-waybill rate | 70% | 95% | 98% (EU) | UN/CEFACT |
| Multimodal share | 8% | 15% | 35% (EU) | ITF |
| Last-mile cost share | 28% | 22% | 20% (Amazon) | CSCMP |
| Carbon intensity | 0.30 kgCO2/t-km | 0.20 (EV) | 0.18 (DHL) | IRU |

### 3.7 Advanced Air Mobility (AAM) KPI

| Metric | Current Level | 2027E Target | Benchmark | Source |
|--------|--------------|-------------|-----------|--------|
| Registered drones | 1.5M (US FAA) | 3.5M | 1.5M (US) | FAA / EASA |
| eVTOL type-certified | 2 (US Joby/Archer) | 8–12 | 2 (US) | FAA / EASA |
| U-space / UTM coverage | 12 pilot cities | 60+ | US nationwide | FAA / EASA |
| Daily drone deliveries | 28k | 500k | 12k (Wing US) | Operator data |
| eVTOL unit cost | $2.0–3.5M | $1.8–2.8M | $2.0–3.5M (Joby) | Analyst data |
| Vertiport build cost | $10–25M | $8–15M | $20–50M | Industry research |

### 3.8 C-ITS / Autonomous Driving KPI

| Metric | Current Level | 2027E | US / EU Level | Source |
|--------|--------------|-------|--------------|--------|
| Robotaxi cumulative trips | 5M+ (Waymo) | 50M+ | 15M+ (Waymo) | Operator data |
| Robotaxi cities | 4 (Waymo) | 20+ | 4 (Waymo) | Announcements |
| AV test mileage | 150M mi (Waymo) | 500M mi | 150M mi (Waymo) | DMV / reports |
| MPI (miles / disengagement) | 12k km | 50k km | 17k mi (Waymo) | DMV reports |
| C-V2X RSU deployed | 12k+ | 80k+ | — | 3GPP / C2C-CC |
| V2X OEM fitment | 15% (new models) | 45% | 8% (US/EU) | OEM announcements |
| National test zones | 10 (US DOT) | 30+ | 10 (US DOT) | USDOT |

---

## IV. Technology Penetration and Adoption

### 4.1 Core Digital-Transport Technology Penetration (Global, 2024 vs 2027E vs 2030E)

| Technology | 2024 | 2027E | 2030E | Basis | Source |
|-----------|------|-------|-------|-------|--------|
| ETC (highway usage) | 75% | 85% | 92% | Toll-transaction share | Operators |
| Signal connectivity (urban) | 65% | 85% | 95% | Connected / total | Agencies |
| AI signal control | 6% | 20% | 40% | AI-adaptive / total | ITS America |
| Video AI analytics | 35% | 65% | 85% | AI-covered cameras | Industry survey |
| Digital-twin transport | 8% | 25% | 50% | Cities deployed | Gartner |
| V2X RSU coverage (highway) | 4% | 25% | 55% | RSU km / total | C2C-CC |
| V2X OEM fitment (new car) | 15% | 45% | 80% | V2X-equipped rate | OEM / 5GAA |
| 5G transport private net | 6% | 28% | 60% | Private-5G coverage | IDC |
| MEC edge computing | 10% | 32% | 60% | MEC at key nodes | IDC |
| GNSS high-precision pos. | 30% | 55% | 80% | Transport terminals w/ GNSS | GNSS assoc. |
| Transport LLM adoption | 6% | 35% | 70% | Major agencies / firms | IDC |
| FAO metro share (new lines) | 18% | 30% | 48% | FAO km / total | UITP |
| Automated terminal share | 20% | 32% | 50% | Auto berths / total | Drewry |
| Drone inspection (highway) | 10% | 32% | 60% | Drone km / total | Agencies |
| RFID baggage tracking | 35% | 65% | 90% | RFID flights | SITA |
| Electric bus share | 25% | 45% | 70% | e-buses / total | UITP |

### 4.2 Global Technology Penetration Benchmark (2024)

| Technology | Global Avg | North America | Europe | Japan | Korea | Singapore |
|-----------|:----------:|:-------------:|:------:|:-----:|:-----:|:--------:|
| ETC / electronic toll | 72% | 75% (E-ZPass) | 60% | 92% | 85% | 98% (ERP 2.0) |
| Signal connectivity | 65% | 70% | 60% | 85% | 78% | 98% |
| Video AI analytics | 35% | 32% | 28% | 45% | 35% | 55% |
| V2X OEM fitment | 12% | 8% (C-V2X/DSRC) | 6% (ITS-G5) | 20% | 12% | 18% |
| L4 robotaxi cities | — | 4 | 1 (limited) | 2 | 1 | 1 |
| Digital-twin city traffic | 8% | 12% | 8% | 5% | 10% | 25% |
| Transport LLM use | 5% | 8% | 4% | 2% | 5% | 8% |
| FAO metro share | 18% | 8% | 15% | 18% | 22% | 35% |
| Automated terminal | 20% | 22% | 35% | 18% | 28% | 85% (PSA) |

### 4.3 Data-Asset Maturity Penetration

| Data-Asset Stage | Penetration | Characteristics | 2027E |
|------------------|-----------|----------------|-------|
| Data catalog established | 45% of agencies | Resource catalog in place | 80% |
| Data governance platform | 28% of agencies | Governance + quality monitoring | 60% |
| Data asset capitalization | 5% of firms | Data → asset → financials | 30% |
| Data trading / productization | 2% of firms | Data products listed/exchanged | 15% |

---

## V. Investment Baselines and Cost Reference

> Costs are indicative and expressed in USD (EUR equivalents in parentheses). Hardware prices trend down ~8–15%/yr; software/services are stable. Baseline Q4-2024.

### 5.1 Smart-Construction Investment Baselines by Mode

#### 5.1.1 Urban Traffic

| Item | Unit | Basic | Standard | Leading | Notes |
|------|------|-------|---------|--------|-------|
| Smart intersection (radar-video + edge + signal) | $k/intersection | 7–11 | 17–28 | 35–55 | Device + SW + install |
| AI adaptive signal | $k/intersection (SW) | 3–7 | 11–21 | 28–49 | Algo + platform + O&M |
| Urban TMG / TOC platform | $k/city | 1.1–2.8M | 4.2–11M | 17–35M | Platform + governance + AI |
| Traffic digital twin | $k/city | 0.4–1.1M | 2.1–5.6M | 8.4–21M | 3D + data + sim |
| Traffic big-data platform | $k/city | 0.7–2.1M | 4.2–8.4M | 11–25M | Lake + governance + dev |
| Transport LLM platform | $k/city | 0.7–1.7M | 3.5–7M | 11–25M | Base + fine-tune + inference |
| Enforcement camera system | $k/set | 4–7 | 7–14 | 17–28 | Camera + ALPR + edge |
| Traffic private cloud | $k/100 nodes | 1.7–2.8M | 4.2–7M | 11–21M | Cloud OS + security |

#### 5.1.2 Highway

| Item | Unit | Basic | Standard | Leading | Notes |
|------|------|-------|---------|--------|-------|
| Smart highway (greenfield) | $k/km | 112–210 | 350–560 | 700–1,120 | Sensing + comms + platform |
| Smart highway (retrofit) | $k/km | 42–84 | 140–250 | 280–490 | Upgrade of existing |
| Free-flow toll gantry | $k/set | 84–126 | 140–210 | 250–390 | RSU + ALPR + edge |
| Radar-video roadside | $k/set | 4–7 | 8–17 | 21–35 | 500m, 8-lane coverage |
| C-V2X RSU | $k/set | 3–6 | 7–11 | 14–21 | RSU + antenna + edge |
| Service-area smart upgrade | $k/pair | 280–560 | 840–1,680 | 2,800–5,600 | Charging + PV + guidance |
| AI incident detection (SW) | $k/100 km | 70–140 | 210–420 | 560–1,120 | Algo + alert linkage |
| Bridge health monitoring | $k/bridge | 140–420 | 700–1,680 | 2,800–7,000 | Sensors + AI |
| Tunnel smart monitoring | $k/km | 112–210 | 280–560 | 630–1,120 | Fire / vent / light / evac |

#### 5.1.3 Rail & Metro

| Item | Unit | Basic | Standard | Leading | Notes |
|------|------|-------|---------|--------|-------|
| CBTC signaling | $k/main-km | 2.1–3.1M | 3.1–4.2M | 4.2–5.6M | ATP/ATO/ATS/interlock |
| FAO driverless (GoA4) | $k/main-km | 2.8–4.2M | 4.2–6.3M | 6.3–8.4M | Vehicle retrofit incl. |
| Smart station (each) | $k/station | 280–560 | 840–1,680 | 2,800–4,900 | Devices + digital twin |
| Network command center | $k/network | 2.1–4.2M | 7–14M | 21–35M | Wall + comms + monitor |
| Rail cloud platform | $k/network | 2.8–5.6M | 8.4–17M | 25–42M | Cloud + big data + AI |
| Smart security screening | $k/station | 70–140 | 210–420 | 560–1,120 | CT + AI + centralized |
| Rail PHM | $k/line | 420–840 | 1.1–2.1M | 2.8–5.6M | Sensors + prediction |

#### 5.1.4 Port

| Item | Unit | Basic | Standard | Leading | Notes |
|------|------|-------|---------|--------|-------|
| Automated terminal (greenfield) | $M/berth | 70–112 | 140–210 | 280–420 | Crane + AGV + TOS |
| Automated retrofit | $M/berth | 21–42 | 56–112 | 140–210 | Upgrade existing |
| AGV / autonomous truck | $k/unit | 84–140 | 168–280 | 350–560 | Vehicle + AV kit + dispatch |
| TOS | $k/terminal | 420–1.1M | 2.1–4.2M | 7–14M | Implement + integrate |
| Smart tally | $k/crane | 21–35 | 56–98 | 140–250 | AI camera + platform |
| Port digital twin | $k/port | 280–700 | 1.1–2.1M | 3.5–7M | 3D + realtime + sim |

#### 5.1.5 Smart Airport

| Item | Unit | Basic | Standard | Leading | Notes |
|------|------|-------|---------|--------|-------|
| A-CDM | $k/airport | 420–1.1M | 2.1–4.2M | 7–11M | Collaborative decision |
| Smart terminal | $k/10k m² | 280–560 | 700–1.4M | 2.1–4.2M | Self-service + mgmt |
| AI screening (CT + AI) | $k/lane | 84–168 | 250–420 | 630–840 | CT + AI judgment |
| Airport digital twin | $k/airport | 1.1–2.8M | 4.2–8.4M | 14–25M | BIM + GIS + IoT + sim |
| Smart gate / jet-bridge | $k/gate | 7–14 | 21–42 | 56–112 | Vision guidance + AI |
| RFID baggage E2E | $/pax throughput | 3–7 | 11–17 | 21–35 | Tag + readers + platform |

#### 5.1.6 Advanced Air Mobility

| Item | Unit | Basic | Standard | Leading | Notes |
|------|------|-------|---------|--------|-------|
| UTM / U-space platform | $k/city | 700–2.1M | 4.2–8.4M | 14–28M | Airspace + flight plan + surveil |
| CNS (comms-nav-surveil) | $k/city | 1.1–2.8M | 4.2–8.4M | 11–21M | 5G + radar + ADS-B |
| eVTOL vertiport | $k/each | 700–1.4M | 2.1–4.2M | 5.6–11M | Charge + comms + security |
| Drone automated dock | $k/set | 21–42 | 56–112 | 168–280 | Charge + weather + edge |
| AAM security (C-UAS) | $k/set | 42–84 | 112–210 | 280–560 | Radar + RF + EO + jam |

#### 5.1.7 C-ITS / Autonomous Driving

| Item | Unit | Basic | Standard | Leading | Notes |
|------|------|-------|---------|--------|-------|
| C-ITS pilot zone | $M/100 km² | 42–70 | 112–210 | 280–490 | Sensing/RSU/MEC/cloud |
| Single-road C-ITS | $k/km | 21–35 | 49–84 | 112–168 | RSU + sensing + MEC |
| C-ITS cloud platform | $k/city | 700–1.7M | 3.5–7M | 11–21M | V2X server + twin + dispatch |
| AV test track | $M/each | 7–21 | 28–70 | 112–210 | Closed track + sim + data |
| HD map production | $k/100 km | 112–210 | 280–490 | 700–1.1M | Collect + build + update/yr |

### 5.2 Annual O&M Cost Baseline (OPEX)

| System Type | O&M Rate (% of capex) | Basic | Standard | Leading |
|-----------|:---------------------:|-------|---------|--------|
| Urban TMG / TOC | 15–20% | $0.4–1.1M/yr | $2.1–5.6M/yr | $8.4–17M/yr |
| Highway smart system | 12–18% | $4–11k/km/yr | $17–35k/km/yr | $42–84k/km/yr |
| Rail signaling | 8–12% | $14–21k/km/yr | $28–49k/km/yr | $56–84k/km/yr |
| Port automation | 10–15% | $1.4–4.2M/yr | $7–14M/yr | $21–42M/yr |
| Airport smart systems | 12–18% | $0.7–2.1M/yr | $4.2–8.4M/yr | $11–21M/yr |
| C-ITS / pilot zone | 15–22% | $0.7–2.8M/yr | $4.2–11M/yr | $14–35M/yr |

### 5.3 Staffing Baseline

| Organization Type | IT Headcount | IT % of Staff | Digital Roles | Outsource % | Budget ($k/person/yr) |
|-------------------|-------------|-------------|--------------|-----------|----------------------|
| National transport dept (IT unit) | 5–15 | — | 2–5 | 80% | 55–90 |
| City transport authority (tech office) | 5–20 | — | 2–8 | 70% | 45–75 |
| Highway operator (info center) | 15–30 | 1.5–3% | 5–12 | 50% | 55–110 |
| Metro operator (IT dept) | 20–50 | 1–2% | 8–20 | 40% | 55–100 |
| Port group (IT) | 20–80 | 1–3% | 5–25 | 35% | 55–130 |
| Airport group (IT) | 30–80 | 1–2.5% | 10–30 | 45% | 55–110 |
| Transit agency (info center) | 10–40 | 0.5–2% | 3–15 | 60% | 40–75 |
| City TMG operations center | 15–60 | — | 5–25 | 30% | 65–150 |

---

## VI. Global Cross-Country Benchmark

### 6.1 Full Benchmark Across 12 Indicators

| Indicator | US | EU | Japan | Korea | Singapore | Global Leader |
|-----------|----|----|-------|-------|-----------|--------------|
| **Market 2024 ($B)** | 22.4 | 20.5 | 7.8 | 4.5 | 1.2 | US |
| **ITS invest / transport capex** | 5.5% | 4.8% | 6.2% | 5.8% | 12.5% | Singapore |
| **Traffic data openness** | 65% | 70% | 35% | 45% | 85% | Singapore / London |
| **ETC highway usage** | 75% | 55% | 92% | 85% | 98% | Japan / Singapore |
| **Signal connection rate** | 70% | 60% | 85% | 78% | 98% | Singapore |
| **Adaptive control coverage** | 12% | 18% | 25% | 15% | 55% | Singapore |
| **L4 robotaxi operation** | 4 cities | 1 (limited) | 2 | 1 | 1 | US |
| **C-ITS / V2X deployment** | ★★★ | ★★★★ | ★★★★ | ★★★ | ★★★★ | EU / Singapore |
| **Urban congestion charging** | 1 (NYC) | 6 | 0 | 1 (Seoul) | 1 | Singapore / London |
| **MaaS maturity** | ★★★ | ★★★★★ | ★★★ | ★★★★ | ★★★★★ | Helsinki |
| **Rail automation (FAO)** | 8% | 15% | 18% | 22% | 35% | Dubai / Singapore |
| **Port automation** | 22% | 35% | 18% | 28% | 85% | Singapore / Rotterdam |
| **Transport carbon intensity** | High | Low-Med | Low | Med | Low | Japan |
| **Safety (fatal / 10k veh)** | 1.37 | 0.51 | 0.38 | 0.62 | 0.38 | Japan / Singapore |
| **Transport LLM adoption** | ★★★★ | ★★★ | ★★ | ★★★ | ★★★ | US |
| **AAM infrastructure** | ★★★★ | ★★ | ★★ | ★★★ | ★ | US |

### 6.2 Leading-City ITS Investment Comparison

| City | Annual ITS Spend (USD M) | Focus | % of Transport Budget | Highlight |
|------|------------------------|-------|----------------------|----------|
| Singapore | 1,800 | ERP 2.0 + MaaS + rail | 12.5% | Highest ITS intensity |
| London | 2,500 | ULEZ + open data + CC | 8.2% | TfL open-data API benchmark |
| Tokyo | 2,200 | ETC 2.0 + ITS Spot | 5.8% | Most mature VICS/ETC 2.0 |
| New York | 1,800 | Congestion pricing + transit | 3.5% | MTA transit digitalization |
| Dubai | 1,500 | Autonomous + air taxi + Hyperloop | 9.5% | 25% trips autonomous by 2030 |
| Seoul | 1,200 | TOPIS + smart signals | 5.5% | TOPIS info-center benchmark |
| Amsterdam | 900 | MaaS + cycling + EV | 7.0% | GLOBAL MaaS pioneer (Whim) |
| Los Angeles | 1,100 | Metro digital + signals | 4.0% | Metro NextGen |

### 6.3 Global Smart-Mobility Standards Benchmark

| Domain | US | EU | Japan | International |
|--------|----|----|-------|--------------|
| ITS framework | US NTCIP / ARC-IT | DATEX II / UTMC | Japan ITS Architecture | ISO 14813 |
| V2X comms | DSRC (802.11p) → C-V2X | ITS-G5 / C-V2X | ITS Connect (760MHz) | 3GPP C-V2X |
| Signal protocol | NTCIP 1202 | OCIT / UTMC | UTMS | — |
| Tolling | ISO 18000-6C | CEN/TC 278 | ISO 18000-6C | ISO 17575 |
| Data exchange | TMDD | DATEX II | Road traffic info std | ISO 19468 |
| Cybersecurity | NIST CSF 2.0 | NIS2 Directive | Cybersecurity Basic Act | ISO 27001 |
| Vehicle cyber | NHTSA Cybersecurity | UN R155/156 | JASO TP 15002 | ISO 21434 |

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## VII. Transport Carbon and Environmental Metrics

### 7.1 Global Transport Carbon Overview

| Indicator | 2020 | 2022 | 2024 | 2025E | 2030E | Source |
|----------|------|------|------|-------|-------|--------|
| Transport CO2 (Gt) | 7.6 | 8.0 | 8.4 | 8.6 | 7.9 (peak) | IEA |
| Share of total emissions | 23% | 23% | 23% | 23% | <22% | IPCC / IEA |
| Road share | 72% | 71% | 70% | 69% | 64% | ITF |
| Rail share | 2% | 2% | 2% | 2% | 1.5% | UIC |
| Shipping share | 11% | 11% | 11% | 11% | 11% | IMO |
| Aviation share | 11% | 12% | 13% | 14% | 15% | ICAO |
| Intensity (kgCO2/t-km) | 0.42 | 0.39 | 0.34 | 0.31 | 0.25 | ITF |

### 7.2 Estimated Smart-Mobility Emission Abatement

| Measure | Abatement (MtCO2/yr) | Mechanism | $/t abatement |
|---------|---------------------|-----------|-------------|
| AI signal optimization (wide) | 12–18 | Less idling / stop-start | 30–50 |
| Free-flow tolling (less queuing) | 3.5–5 | Less deceleration/accel | Low (marginal) |
| Smart transit scheduling | 2–3.5 | Higher load factor | 20–35 |
| Truck platooning (2030E) | 2.5–4 | Drag reduction, 10–15% fuel | 70–110 |
| Multimodal "one-bill" (2030E) | 5–8 | Shift to rail / water | 40–70 |
| MaaS + green incentives (2030E) | 3–5 | Shift to transit / active | 15–30 |
| Roadside PV (2030E) | 8–12 | Clean energy on ROW | 50–70 |
| Port shore-power (2030E) | 1.5–2.5 | Shore power vs aux engine | 30–50 |

---

## VIII. Talent and Organization Benchmarks

### 8.1 Global Smart-Mobility Talent Supply-Demand

| Category | 2024 Employed | 2027E Demand | 2030E Demand | Gap | Source |
|----------|--------------|------------|------------|-----|--------|
| Transport IT engineer | 280k | 450k | 650k | 38% | ITS America / ERTICO |
| Transport data analyst | 120k | 250k | 400k | 52% | IDC |
| Transport AI engineer | 50k | 150k | 300k | 67% | LinkedIn Talent |
| V2X / C-ITS engineer | 80k | 220k | 380k | 64% | 5GAA / C2C-CC |
| Transport cyber engineer | 60k | 150k | 280k | 58% | (ISC)² |
| Smart-mobility PM | 50k | 120k | 200k | 55% | Industry survey |
| AAM professional | 30k | 150k | 350k | 80% | FAA / EASA |

### 8.2 Global Smart-Mobility Salary Baseline (USD, annual)

| Role | Junior (1–3y) | Mid (3–5y) | Senior (5–10y) | Expert (10y+) |
|------|--------------|-----------|---------------|--------------|
| Transport AI engineer | 70–110k | 120–180k | 180–300k | 300–450k |
| Smart-mobility solution architect | 80–120k | 130–190k | 200–320k | 320–480k |
| Transport data engineer | 65–100k | 110–160k | 170–280k | 280–420k |
| V2X systems engineer | 75–120k | 120–180k | 190–300k | 300–420k |
| Transport digital-twin engineer | 80–120k | 130–190k | 200–320k | 320–480k |
| Transport cyber engineer | 70–110k | 120–170k | 180–280k | 280–420k |
| Transport product manager | 70–110k | 120–170k | 180–280k | 280–420k |
| Smart-mobility PM | 70–110k | 115–165k | 180–270k | 280–420k |

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## IX. Data Sources and Update Guidance

### 9.1 Core Data Sources

| Data Type | Primary | Secondary | Frequency |
|----------|---------|----------|----------|
| Global ITS market | MarketsandMarkets, Frost & Sullivan, Gartner | McKinsey, IDC | Annual / quarterly |
| Tech penetration | Agencies, C2C-CC, 5GAA | IDC, Gartner | Annual |
| Safety KPI | WHO Global Road Safety, IRF | NHTSA, ETSC | Annual |
| Transport carbon | IEA, ITF | IPCC, IMO, ICAO | Annual |
| ITS investment | Public budgets, listed-company reports | Procurement disclosures | Annual / monthly |
| Operations data | Operator annual reports | Statistical yearbooks | Annual / quarterly |
| Global benchmark | World Bank, ITF/OECD, UNECE | National transport depts | Annual |
| V2X / autonomy | USDOT, C2C-CC, 5GAA | OEM reports | Semi-annual |
| AAM | FAA, EASA | Frost & Sullivan | Quarterly |
| Talent | LinkedIn Talent, (ISC)² | Salary surveys | Semi-annual |
| Procurement | Public tender platforms | Third-party data | Real-time / monthly |

### 9.2 Update Guidance

| Data Type | Frequency | Owner | Trigger | Note |
|----------|----------|-------|---------|------|
| Market size | Every 6 mo | Research analyst | New major report | Track IDC / Frost / Gartner cadence |
| Tech penetration | Annual | Tech analyst | Year-end stats | Use UITP / ERTICO annual |
| Investment baseline | Quarterly | Cost analyst | Tender price change >10% | Track procurement data |
| KPI | Annual | Data analyst | Official stats | Sync global benchmark |
| Regulations | Real-time | Research analyst | New rule published | Flag effective date + transition |
| Vendor data | Every 6 mo | Vendor analyst | Annual / quarterly reports | Watch M&A and major contracts |
| Global benchmark | Annual | Intl research team | Intl org annual report | Translate + localize |

### 9.3 Data-Quality Notes

1. **Forecast uncertainty**: Post-2026 figures are synthesized from multiple sources; actuals may deviate due to policy, technology, or macro shifts. Apply ±15% tolerance.
2. **Regional variance**: National figures differ widely; leading regions (EU, Singapore, Japan) typically run 3–5 years ahead of the global average.
3. **Definition variance**: ITS / smart-mobility definitions differ across research houses. This document prioritizes ITF / UITP framing globally and MarketsandMarkets for market sizing.
4. **Cost timing**: Hardware prices fall ~8–15%/yr (Moore's-law trend); software/services stable. Baseline Q4-2024; adjust for inflation and price erosion.
5. **Feedback**: Report discrepancies or newer sources via the document-maintenance channel to continuously improve quality.

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> **Legal Notice**: This document is a reference file of the *Transportation Digital & AI Transformation Expert (Standard Edition)* Skill. Data is drawn from public reports and industry research for learning reference only. Project decisions should rely on real-time professional advice.

> **Last updated**: July 2025 | **Next update**: January 2026 (per annual data-release cycle)
