# Transportation Digital Maturity Assessment Tool (T-DMM)
## Transportation Digital Maturity Model Assessment Workbook

---

## 1. Tool Overview

This tool performs a systematic assessment of the transportation digital maturity of a city or organization, based on the T-DMM (Transportation Digital Maturity Model) framework. It is applicable to city transport authorities, transport investment holding groups, highway concessionaires / operators, public transit agencies, metro and rail operators, and other transport stakeholders.

### Assessment Modes
| Mode | # Questions | Time | Use Case |
|------|-------------|------|----------|
| Quick assessment | 15 questions | 15–20 min | Preliminary diagnosis, executive briefing |
| Full assessment | 50+ questions | 2–4 hours | Strategic planning, project kickoff, annual review |

---

## 2. Five Assessment Dimensions

| Code | Dimension | Weight | Description |
|------|-----------|--------|-------------|
| S | Strategy & Governance | 20% | Top-level planning, organizational guarantee, funding |
| D | Data & Platform | 25% | Data governance, platform capability, integration & interoperability |
| I | Innovation & Application | 25% | Business scenario coverage, AI adoption, innovation pilots |
| C | Connectivity & Collaboration | 15% | Sensing network, communications infrastructure, cross-agency collaboration |
| E | Ecosystem & Talent | 15% | Industry ecosystem, talent development, user services |

---

## 3. Full Assessment Questionnaire (52 Questions)

### Dimension S: Strategy & Governance (10 questions)

#### S1. Digital Strategy Planning
| Score | Criteria |
|-------|----------|
| 1 | No explicit digital strategy or planning document |
| 2 | Has an IT/master-plan document, but not elevated to digital-strategy level |
| 3 | An independent digital strategy has been defined, with clear goals and roadmap |
| 4 | Digital strategy is embedded in the corporate/city master strategy, with a KPI framework |
| 5 | Digital strategy runs as an annual iterative framework, deeply coupled with business strategy |

**Score: ___ / 5**

#### S2. Organizational Structure
| Score | Criteria |
|-------|----------|
| 1 | No dedicated digital department or role |
| 2 | Part-time IT/ICT administrators only |
| 3 | An independent digital/ICT department is established |
| 4 | A CDO/CIO role exists; digital function reports to executive leadership |
| 5 | A digital committee is formed; matrix-style digital organization with digital business partners (BPs) per business line |

**Score: ___ / 5**

#### S3. Digital Budget Share
| Score | Criteria |
|-------|----------|
| 1 | Digital spend < 0.5% of revenue / total budget |
| 2 | Digital spend 0.5%–1% |
| 3 | Digital spend 1%–3% |
| 4 | Digital spend 3%–5% |
| 5 | Digital spend > 5% |

**Score: ___ / 5**

#### S4. Digital Performance Management
| Score | Criteria |
|-------|----------|
| 1 | No digital-related performance metrics |
| 2 | A few IT KPIs exist but are not formally assessed |
| 3 | Digital KPIs are included in departmental appraisals |
| 4 | Digital KPIs are in all-staff appraisals, linked to compensation |
| 5 | A recurring digital-maturity assessment framework exists; results tied to promotion / resource allocation |

**Score: ___ / 5**

#### S5. Top-Level Planning Maturity
| Score | Criteria |
|-------|----------|
| 1 | No unified architecture design |
| 2 | A simple system architecture diagram exists |
| 3 | A complete digital top-level plan exists (business + data + application + technology architecture) |
| 4 | The top-level plan is reviewed by external experts and continuously refreshed |
| 5 | Architecture governance is mature; all new projects must pass architecture review |

**Score: ___ / 5**

#### S6. Standards System
| Score | Criteria |
|-------|----------|
| 1 | No standards system |
| 2 | Adopts generic industry standards, no localization |
| 3 | Some data / interface standards have been published |
| 4 | Standards cover data, technology, security, and management domains |
| 5 | Standards are certified; participates in international/national standards authoring |

**Score: ___ / 5**

#### S7. Investment Decision Framework
| Score | Criteria |
|-------|----------|
| 1 | No formal investment decision process |
| 2 | Follows traditional IT project approval process |
| 3 | A digital project initiation review board is established |
| 4 | Project review includes a digital-maturity contribution assessment |
| 5 | Portfolio management in place; digital investment priorities dynamically adjusted |

**Score: ___ / 5**

#### S8. Digital Culture
| Score | Criteria |
|-------|----------|
| 1 | Organization is skeptical / resistant to digitalization |
| 2 | Management is aware, but grassroots participation is low |
| 3 | Regular digital training; staff digital awareness is building |
| 4 | Data-driven decision culture formed; fault-tolerant framework for innovation failure |
| 5 | Digital-literacy pass rate > 80%; active bottom-up innovation |

**Score: ___ / 5**

#### S9. Regulatory Environment & Compliance
| Score | Criteria |
|-------|----------|
| 1 | Does not track industry regulatory developments |
| 2 | Passively aware of national / industry regulations |
| 3 | Dedicated staff track regulations and respond promptly |
| 4 | Actively participates in regulatory consultations; pre-positions ahead of change |
| 5 | Contributes to standards setting; serves as industry pilot and benchmark |

**Score: ___ / 5**

#### S10. Disaster Recovery & Business Continuity
| Score | Criteria |
|-------|----------|
| 1 | No backup / DR plan |
| 2 | Basic backups exist, no drills performed |
| 3 | A DR center is established; annual drills |
| 4 | Active-active / multi-active architecture; RTO < 30 min, RPO < 5 min |
| 5 | Chaos engineering is routine; BCMS certified to ISO 22301 |

**Score: ___ / 5**

---

### Dimension D: Data & Platform (13 questions)

#### D1. Data Collection Coverage
| Score | Criteria |
|-------|----------|
| 1 | Mainly manual entry; automated collection < 20% |
| 2 | Some core systems automated; coverage 20%–40% |
| 3 | Major business systems automated; coverage 40%–60% |
| 4 | Extensive IoT sensing deployment; coverage 60%–80% |
| 5 | Full-element sensing; coverage > 80%, multi-source (video, radar, inductive loop, etc.) |

**Score: ___ / 5**

#### D2. Data Standardization
| Score | Criteria |
|-------|----------|
| 1 | No unified data standards; formats vary across systems |
| 2 | Some core data has internal standards |
| 3 | Standards cover major data domains, aligned to international/national standards |
| 4 | Master Data Management (MDM) mature; "one fact, one source" |
| 5 | Complete data asset catalog; data lineage traceable |

**Score: ___ / 5**

#### D3. Data Quality Management
| Score | Criteria |
|-------|----------|
| 1 | No data quality management framework |
| 2 | Reactive fixes after problems are found |
| 3 | Data quality rule library; periodic quality checks |
| 4 | Automated data quality monitoring; pass rate > 95% |
| 5 | Closed-loop quality management; source governance + AI-assisted cleansing |

**Score: ___ / 5**

#### D4. Data Sharing & Exchange
| Score | Criteria |
|-------|----------|
| 1 | Systems store data independently; no sharing |
| 2 | Point-to-point interfaces for exchange |
| 3 | Unified data sharing & exchange platform |
| 4 | Data is serviceized; standardized APIs; > 100k calls/day |
| 5 | Data federation / data mesh; trusted cross-organization data flow |

**Score: ___ / 5**

#### D5. Big Data Platform Capability
| Score | Criteria |
|-------|----------|
| 1 | No big data platform |
| 2 | Traditional data warehouse only |
| 3 | Hadoop/Spark-style platform deployed; batch processing |
| 4 | Stream-batch unified architecture; real-time + offline analytics |
| 5 | Lakehouse architecture; multi-model compute; PB-scale daily processing |

**Score: ___ / 5**

#### D6. Data Security & Privacy
| Score | Criteria |
|-------|----------|
| 1 | No data security measures |
| 2 | Basic access control; backup framework exists |
| 3 | Data classification; sensitive data encrypted; security policy in place |
| 4 | End-to-end data security (collect/transmit/store/use/destroy); ISO 27001 certified |
| 5 | Privacy-enhancing tech (federated learning / differential privacy); ISO 27701 certified |

**Score: ___ / 5**

#### D7. Video / Image Analytics
| Score | Criteria |
|-------|----------|
| 1 | No intelligent video analytics |
| 2 | Basic video surveillance; manual review |
| 3 | AI video analytics in some scenarios (ALPR, etc.) |
| 4 | Full-scenario video AI coverage; automatic event detection |
| 5 | Multimodal fusion (video + radar + audio); real-time situational awareness |

**Score: ___ / 5**

#### D8. GIS / BIM / CIM Capability
| Score | Criteria |
|-------|----------|
| 1 | No GIS platform |
| 2 | Basic digital basemap |
| 3 | GIS single-pane map built; major assets mapped |
| 4 | BIM + GIS fusion; core infrastructure digital twin |
| 5 | CIM (City Information Model) platform; full-element digital twin of the city |

**Score: ___ / 5**

#### D9. Cloud Infrastructure
| Score | Criteria |
|-------|----------|
| 1 | All on-prem physical servers |
| 2 | Some systems virtualized |
| 3 | Private cloud; key systems migrated |
| 4 | Hybrid cloud; elastic scaling |
| 5 | Cloud-native; containerized + Kubernetes; Serverless widely used |

**Score: ___ / 5**

#### D10. IoT Platform Capability
| Score | Criteria |
|-------|----------|
| 1 | No IoT platform |
| 2 | Devices connect directly to systems; no unified management |
| 3 | Unified device management; mainstream protocols supported |
| 4 | Million-device access; edge computing coordination |
| 5 | Cloud-edge-end integrated; AIoT O&M; self-healing devices |

**Score: ___ / 5**

#### D11. Data Governance Organization
| Score | Criteria |
|-------|----------|
| 1 | No data governance role |
| 2 | Technical staff double as data managers |
| 3 | Data management role established; governance policy exists |
| 4 | Three-tier governance: data council + data owners + data stewards |
| 5 | Governance embedded in business processes; data culture & literacy widespread |

**Score: ___ / 5**

#### D12. AI / ML Platform Capability
| Score | Criteria |
|-------|----------|
| 1 | No AI/ML platform |
| 2 | Point AI apps, independently built & deployed |
| 3 | Unified AI dev platform; model training & management |
| 4 | Mature MLOps; full model lifecycle management |
| 5 | LLMOps; full pipeline of LLM train / fine-tune / inference / evaluation |

**Score: ___ / 5**

#### D13. Data Assetization
| Score | Criteria |
|-------|----------|
| 1 | Data not treated as an asset |
| 2 | Initial inventory of core data assets |
| 3 | Data asset catalog built; valuation method exists |
| 4 | Exploring data asset capitalization; data products offered externally |
| 5 | Active data asset capitalization; routine data trading |

**Score: ___ / 5**

---

### Dimension I: Innovation & Application (13 questions)

#### I1. Traffic Operations Monitoring
| Score | Criteria |
|-------|----------|
| 1 | No operations monitoring system |
| 2 | Basic monitoring wall; static info only |
| 3 | A Traffic Management Center (TMC) is built; real-time state monitoring |
| 4 | Holographic sensing + situation projection; proactive early warning |
| 5 | Digital-twin intelligent transport management platform; autonomous decision + coordinated control |

**Score: ___ / 5**

#### I2. Signal Control Intelligence
| Score | Criteria |
|-------|----------|
| 1 | Fixed-time signal control |
| 2 | Multi-period fixed-cycle control |
| 3 | Isolated adaptive / actuated control |
| 4 | Arterial / area coordinated control; AI-assisted timing optimization |
| 5 | Citywide signal optimization; V2X signal priority |

**Score: ___ / 5**

#### I3. Traveler Information Service
| Score | Criteria |
|-------|----------|
| 1 | No public information service |
| 2 | Static publishing (website / social media) |
| 3 | Real-time traffic info published; multi-channel coverage |
| 4 | Personalized trip planning; initial MaaS adoption |
| 5 | One-stop MaaS platform; multi-modal optimal recommendation + carbon credits |

**Score: ___ / 5**

#### I4. Public Transit Intelligence
| Score | Criteria |
|-------|----------|
| 1 | Basic transit operations system |
| 2 | Transit AVL + automated stop announcements |
| 3 | Intelligent dispatch; dynamic scheduling optimization |
| 4 | Demand-responsive transit; AI network optimization |
| 5 | Fully automated buses + Connected & Automated vehicles + on-demand mobility |

**Score: ___ / 5**

#### I5. Parking Intelligence
| Score | Criteria |
|-------|----------|
| 1 | Manual toll management |
| 2 | Some lots use ALPR-based payment |
| 3 | On- and off-street parking networked; guidance publishing |
| 4 | Shared / reserved parking; frictionless payment |
| 5 | Citywide parking single network; AVP (automated valet parking) |

**Score: ___ / 5**

#### I6. Enforcement Intelligence
| Score | Criteria |
|-------|----------|
| 1 | Fully manual enforcement |
| 2 | Some automated enforcement / ANPR checkpoints |
| 3 | AI non-site enforcement covers major violations |
| 4 | Full-scenario smart enforcement; minimal staff |
| 5 | Digital enforcement closed loop; integrated notice-adjudication-payment |

**Score: ___ / 5**

#### I7. Asset Management Digitalization
| Score | Criteria |
|-------|----------|
| 1 | Paper ledger management |
| 2 | Spreadsheets / basic IT management |
| 3 | Asset management system; full lifecycle management |
| 4 | BIM + IoT digital asset management; predictive maintenance |
| 5 | Transport asset digital twin; AI-driven full-lifecycle optimization |

**Score: ___ / 5**

#### I8. Emergency Command & Dispatch
| Score | Criteria |
|-------|----------|
| 1 | Manual phone dispatch |
| 2 | Electronic emergency plans |
| 3 | Emergency command platform; multi-agency coordination |
| 4 | AI-assisted plan matching + resource dispatch optimization |
| 5 | Digital-twin drills + intelligent simulation + automatic response |

**Score: ___ / 5**

#### I9. Logistics Digitalization
| Score | Criteria |
|-------|----------|
| 1 | Traditional logistics management |
| 2 | Transport Management System (TMS) live |
| 3 | Digital freight platform; intelligent capacity matching |
| 4 | Multimodal single-document; blockchain e-BL |
| 5 | Autonomous logistics + drone delivery + digital supply chain |

**Score: ___ / 5**

#### I10. Mobility as a Service (MaaS)
| Score | Criteria |
|-------|----------|
| 1 | No MaaS concept |
| 2 | Single-mode online service |
| 3 | Multi-modal information integration & display |
| 4 | MaaS platform live; cross-modal payment & planning |
| 5 | Mature MaaS ecosystem; subscription mobility + carbon-credit incentives |

**Score: ___ / 5**

#### I11. AI / AIGC Application Scenarios
| Score | Criteria |
|-------|----------|
| 1 | No AI application |
| 2 | Trialing isolated AI features |
| 3 | 3–5 mature AI scenarios in steady operation |
| 4 | 10+ AI scenarios live; LLM-assisted decision making |
| 5 | AI deeply embedded in processes; in-house / deeply adapted transport LLM |

**Score: ___ / 5**

#### I12. Digital Twin Application
| Score | Criteria |
|-------|----------|
| 1 | No digital twin application |
| 2 | Visualization wall (early digital twin) |
| 3 | Digital twin of key areas; static + dynamic data fusion |
| 4 | Citywide / network-wide digital twin; simulation & projection |
| 5 | Digital twin closed loop with real-time control; virtual-physical linkage |

**Score: ___ / 5**

#### I13. Green Transport Digitalization
| Score | Criteria |
|-------|----------|
| 1 | No carbon monitoring |
| 2 | Manual carbon emissions accounting |
| 3 | Online carbon monitoring platform; partial coverage |
| 4 | All-mode carbon monitoring; mobility-credit (carbon inclusive) program running |
| 5 | Participates in carbon trading; AI-driven decarbonization optimization |

**Score: ___ / 5**

---

### Dimension C: Connectivity & Collaboration (8 questions)

#### C1. Communications Network Coverage
| Score | Criteria |
|-------|----------|
| 1 | No dedicated communications network |
| 2 | Leases public carrier networks |
| 3 | Hybrid (fiber private + 4G/5G); key nodes on private network |
| 4 | 5G / C-V2X full coverage of main roads; edge nodes deployed |
| 5 | 5G-Advanced / 6G trial + satellite comms + drone relay; space-air-ground integrated |

**Score: ___ / 5**

#### C2. Sensing Device Density
| Score | Criteria |
|-------|----------|
| 1 | Almost no automated sensing devices |
| 2 | Cameras at key intersections / segments |
| 3 | Major-road sensing coverage; multiple sensors (video + radar + loop) |
| 4 | Network-wide multi-dimensional sensing; radar-video fusion |
| 5 | Holographic sensing intersections; > 50 sensors/km; millisecond sampling |

**Score: ___ / 5**

#### C3. Cross-Agency Data Collaboration
| Score | Criteria |
|-------|----------|
| 1 | Agencies fully siloed |
| 2 | Occasional exchange; manual coordination |
| 3 | Cross-agency data-sharing framework; periodic exchange |
| 4 | Unified data sharing & exchange platform; real-time sharing |
| 5 | Data federation / trusted data space; automated cross-agency, cross-tier collaboration |

**Score: ___ / 5**

#### C4. Cross-Region Collaboration
| Score | Criteria |
|-------|----------|
| 1 | No cross-region collaboration |
| 2 | Inter-city / inter-state information notification framework |
| 3 | Regional transport integration platform built |
| 4 | Cross-region transport dispatch collaboration routine |
| 5 | Metro-area intelligent transport platform coordination; cross-region linked control |

**Score: ___ / 5**

#### C5. On-Vehicle / Mobile Coverage
| Score | Criteria |
|-------|----------|
| 1 | No on-vehicle / mobile system |
| 2 | Some fleet vehicles have GPS |
| 3 | 100% smart-terminal coverage of regulated fleets (coaches, hazmat carriers) |
| 4 | V2X onboard penetration > 10%; mobile app services covered |
| 5 | Vehicle-Infra-Cloud integration; OEM V2X penetration > 30%; phone-as-V2X covered |

**Score: ___ / 5**

#### C6. Edge Computing Capability
| Score | Criteria |
|-------|----------|
| 1 | No edge computing |
| 2 | A few edge gateway devices |
| 3 | Edge nodes at key intersections / segments |
| 4 | Three-tier compute (edge–zone–center) architecture |
| 5 | Cloud-edge-end collaborative AI inference; edge autonomy |

**Score: ___ / 5**

#### C7. Communications Network Security
| Score | Criteria |
|-------|----------|
| 1 | No network security measures |
| 2 | Basic firewall and antivirus |
| 3 | ISO 27001 / NIS2 compliant; security management system |
| 4 | End-to-end encryption; security situational-awareness platform |
| 5 | Zero-trust architecture; post-quantum encryption pilot |

**Score: ___ / 5**

#### C8. V2X / Cooperative ITS Application
| Score | Criteria |
|-------|----------|
| 1 | No cooperative ITS |
| 2 | Cooperative ITS proof of concept |
| 3 | Cooperative ITS at flagship corridors (green-wave, safety warning, etc.) |
| 4 | Scaled cooperative ITS deployment; multiple applications |
| 5 | Vehicle-Infra-Cloud commercial operation; autonomous-driving coordination |

**Score: ___ / 5**

---

### Dimension E: Ecosystem & Talent (8 questions)

#### E1. Digital Talent Share
| Score | Criteria |
|-------|----------|
| 1 | Digital professionals < 1% |
| 2 | Digital professionals 1%–3% |
| 3 | Digital professionals 3%–8% |
| 4 | Digital professionals 8%–15% |
| 5 | Digital professionals > 15%; AI/data engineers > 5% |

**Score: ___ / 5**

#### E2. Talent Development System
| Score | Criteria |
|-------|----------|
| 1 | No digital training |
| 2 | Occasional external training |
| 3 | Internal training system; annual digital training plan |
| 4 | Digital talent certification + dual career tracks |
| 5 | Digital academy / corporate university; deep industry-academia-research integration |

**Score: ___ / 5**

#### E3. Industry Collaboration Ecosystem
| Score | Criteria |
|-------|----------|
| 1 | No external partners |
| 2 | Single-vendor dependency |
| 3 | Multi-vendor cooperation; partner management framework |
| 4 | Innovation ecosystem; joint labs / innovation centers |
| 5 | Open platform + ecosystem; integrated industry-academia-research-application innovation |

**Score: ___ / 5**

#### E4. User Service Touchpoints
| Score | Criteria |
|-------|----------|
| 1 | No online user service |
| 2 | Official website / social media only |
| 3 | App / mini-program live with basic services |
| 4 | Omni-channel service (app / mini-program / smart assistant / hotline); user profiles |
| 5 | Full-journey personalized service; user NPS > 50; bot resolution > 80% |

**Score: ___ / 5**

#### E5. Standards Participation
| Score | Criteria |
|-------|----------|
| 1 | No standards involvement |
| 2 | Tracks industry standards information |
| 3 | Contributes to regional / consortium standards |
| 4 | Contributes to industry / national standards |
| 5 | Leads / initiates standards; participates in international standards |

**Score: ___ / 5**

#### E6. Innovation Investment
| Score | Criteria |
|-------|----------|
| 1 | No innovation investment |
| 2 | Annual innovation budget < 5% of IT budget |
| 3 | Innovation lab / dedicated fund; 5%–10% of annual spend |
| 4 | Innovation incubation framework; 10+ projects/year |
| 5 | Innovation drives growth; spun-off independent business units |

**Score: ___ / 5**

#### E7. Research Commercialization
| Score | Criteria |
|-------|----------|
| 1 | No research collaboration |
| 2 | Occasional university project collaboration |
| 3 | Stable industry-academia-research collaboration; annual R&D projects |
| 4 | Research commercialization framework; patents / software copyrights output |
| 5 | National / ministerial research platform; industrialized outcomes |

**Score: ___ / 5**

#### E8. Open Data & Ecosystem Enablement
| Score | Criteria |
|-------|----------|
| 1 | No data openness |
| 2 | A few statistical datasets published |
| 3 | Some transport data opened to the public |
| 4 | Open data platform; API openness; incubates innovative apps |
| 5 | Data-element marketization; data trust / data space |

**Score: ___ / 5**

---

## 4. Quick Assessment Version (15 questions, 15 min)

| # | Question | Maps to full item |
|---|----------|-------------------|
| Q1 | Is there a clear digital strategy? | S1 |
| Q2 | Digital budget as % of total budget / revenue? | S3 |
| Q3 | Is a CDO/CIO or independent digital department in place? | S2 |
| Q4 | Data automated-collection coverage? | D1 |
| Q5 | Is a unified big-data platform built? | D5 |
| Q6 | Data sharing & exchange capability level? | D4 |
| Q7 | Traffic Management Center (TMC) maturity? | I1 |
| Q8 | Signal control intelligence level? | I2 |
| Q9 | Are AI / LLM applications deployed? | I11 |
| Q10 | Is a MaaS platform built? | I10 |
| Q11 | Communications network (5G / C-V2X) coverage? | C1 |
| Q12 | Sensing device density? | C2 |
| Q13 | Digital talent share? | E1 |
| Q14 | Carbon monitoring / green-transport digitalization level? | I13 |
| Q15 | Digital twin application level? | I12 |

---

## 5. Scoring Method

### 5.1 Dimension Score
```
Dimension Score = SUM(question scores in dimension) / (number of questions × 5) × 100
```

### 5.2 Weighted Total Score
```
Total = S×20% + D×25% + I×25% + C×15% + E×15%
```

### 5.3 Maturity Level
| Total Score | Level | Label | Description |
|-------------|-------|-------|-------------|
| 0–20 | L1 | Initial | Digitalization at the starting point; mostly point IT |
| 21–40 | L2 | Defined | Core systems computerized; digital transformation planning begins |
| 41–60 | L3 | Integrated | Platform integration; data connected; key scenarios intelligent |
| 45–70 | L4 | Optimized | Data-driven operations; AI widely used; ecosystem emerging |
| 71–85 | L5 | Leading | Fully digital; digital twin + AI deeply fused; industry benchmark |
| 86–100 | L5+ | Excellent | Globally leading; defines industry standards; continuous innovation |

---

## 6. Result Radar Chart (text description)

```
                  Strategy & Governance (S)
                        /\
                       /  \
                      /    \
                     /      \
                    /   ★    \
                   /   score  \
       Ecosystem & Talent (E) /____________\ Data & Platform (D)
                  |\            /|
                  | \          / |
                  |  \        /  |
                  |   \      /   |
                  |    \    /    |
                  |     \  /     |
                  |      \/      |
                  |      /\      |
                  |     /  \     |
                  |    /    \    |
                  |   /      \   |
                  |  /        \  |
                  | /          \ |
                  |/____________\|
   Connectivity & Collaboration (C)   Innovation & Application (I)
```

**How to draw:** Plot each dimension's percentage score on its axis; connect into a closed polygon. Larger area = higher maturity.

---

## 7. Gap Analysis Template

### 7.1 Dimension Gap Analysis
| Dimension | Current | Industry Avg | Leading | Gap | Priority |
|-----------|---------|--------------|---------|-----|----------|
| S Strategy & Governance | ___ | ___ | ___ | -___ | High/Med/Low |
| D Data & Platform | ___ | ___ | ___ | -___ | High/Med/Low |
| I Innovation & Application | ___ | ___ | ___ | -___ | High/Med/Low |
| C Connectivity & Collaboration | ___ | ___ | -___ | -___ | High/Med/Low |
| E Ecosystem & Talent | ___ | ___ | ___ | -___ | High/Med/Low |

### 7.2 Key Shortfall Analysis
| # | Shortfall | Current | Target | Root Cause | Impact |
|---|-----------|---------|--------|------------|--------|
| 1 | | ___ | ___ | | High/Med/Low |
| 2 | | ___ | ___ | | High/Med/Low |
| 3 | | ___ | ___ | | High/Med/Low |

### 7.3 Strength Consolidation Analysis
| # | Strength | Current | Lead Margin | Sustain Strategy |
|---|----------|---------|-------------|------------------|
| 1 | | ___ | +___ | |
| 2 | | ___ | +___ | |

---

## 8. Recommendation Engine

### 8.1 Action Paths by Maturity Level

#### L1 Initial → Recommended Actions
| Priority | Action | Expected Effect | Cycle | Reference Investment |
|----------|--------|-----------------|-------|----------------------|
| P0 | Define digital strategy | Direction & resources | 3–6 mo | $0.7M–$1.4M |
| P0 | Build core IT systems | Solid data foundation | 6–12 mo | $7M–$28M |
| P1 | Form digital team | Org guarantee | 3–6 mo | $2.8M–$7M/yr (staff) |
| P1 | Deploy IoT sensing | Raise collection coverage | 12–18 mo | $14M–$70M |
| P2 | Establish data standards | Governance base | 6–12 mo | $1.4M–$4.2M |

#### L2 Defined → Recommended Actions
| Priority | Action | Expected Effect | Cycle | Reference Investment |
|----------|--------|-----------------|-------|----------------------|
| P0 | Build data hub / big-data platform | Connect data | 12–18 mo | $14M–$42M |
| P0 | Upgrade Traffic Management Center (TMC) | Ops monitoring | 6–12 mo | $7M–$28M |
| P1 | Implement data governance | Quality uplift | Ongoing | $4.2M–$11M/yr |
| P1 | AI signal optimization | +15–25% throughput | 12–18 mo | $7M–$21M |
| P2 | Launch AI pilots | Innovation drive | 6–12 mo | $2.8M–$7M |

#### L3 Integrated → Recommended Actions
| Priority | Action | Expected Effect | Cycle | Reference Investment |
|----------|--------|-----------------|-------|----------------------|
| P0 | Digital twin platform | Holographic + simulation | 12–24 mo | $28M–$70M |
| P0 | Deepen cross-agency data collaboration | Coordination uplift | 6–12 mo | $4.2M–$11M |
| P1 | MaaS platform | Service upgrade | 12–18 mo | $14M–$42M |
| P1 | LLM scenario rollout | AI leap | 6–12 mo | $7M–$21M |
| P2 | Carbon monitoring & green transport | Climate compliance | 6–12 mo | $4.2M–$11M |

#### L4 Optimized → Recommended Actions
| Priority | Action | Expected Effect | Cycle | Reference Investment |
|----------|--------|-----------------|-------|----------------------|
| P0 | Vehicle-Infra-Cloud integration | AV coordination | 18–36 mo | $70M–$280M |
| P0 | Data asset operation | Data monetization | Ongoing | $7M–$21M/yr |
| P1 | Industry open platform | Ecosystem enablement | 12–18 mo | $14M–$42M |
| P1 | Low-altitude economy digitalization | New growth curve | 12–24 mo | $28M–$70M |
| P2 | In-house / deeply adapted transport LLM | AI leadership | 12–24 mo | $28M–$70M |

#### L5 Leading → Recommended Actions
| Priority | Action | Expected Effect | Cycle | Reference Investment |
|----------|--------|-----------------|-------|----------------------|
| P0 | Standards export & model replication | Industry influence | Ongoing | $4.2M–$11M/yr |
| P0 | Frontier R&D (6G / quantum / AV) | Stay ahead | Ongoing | $14M–$42M/yr |
| P1 | International cooperation | Global influence | Ongoing | Case-by-case |
| P1 | Data-element market participation | Data economy | Ongoing | Case-by-case |

---

## 9. Benchmark Comparison (by city / organization tier)

### 9.1 Smart Urban Transport Digital Baseline (2024–2025 reference)
| Tier | Representative Cities / Organizations | Avg Total | S | D | I | C | E | Trait |
|------|---------------------------------------|-----------|---|---|---|---|---|-------|
| Global Tier-1 cities | Singapore, London, Tokyo, Amsterdam | 68–82 | 70 | 72 | 75 | 70 | 65 | Fully leading |
| Leading global cities | Dubai, Seoul, Sydney, Toronto | 55–68 | 62 | 60 | 58 | 55 | 52 | Rapid growth |
| Developing metros | Istanbul, Bogotá, Jakarta, Manila | 42–55 | 48 | 45 | 45 | 42 | 40 | Steady catch-up |
| Smaller / midsize cities | Regional & secondary cities | 28–42 | 35 | 30 | 32 | 30 | 25 | Infrastructure build-out |
| Major highway concessionaire | Large national motorway operator | 55–70 | 60 | 58 | 55 | 52 | 50 | IT → digital transition |
| Large transit agency | Capital-city transit authority | 40–58 | 45 | 42 | 45 | 38 | 35 | Intelligent dispatch focus |
| Metro / rail operator | Major metro / rail company | 50–65 | 55 | 50 | 52 | 48 | 45 | High automation |

### 9.2 Industry Best-Practice Snapshot
| Domain | Benchmark Case | Highlight | Reference Index |
|--------|---------------|----------|-----------------|
| Traffic Management Center | London TfL (Traffic Operations) | City-scale digital twin + AI decisions | ★★★★★ |
| Signal Control | Pittsburgh Surtrac / London SCOOT | Citywide AI signal optimization | ★★★★★ |
| MaaS | Helsinki Whim | Mobility credits + MaaS | ★★★★★ |
| Smart Motorway | A14 Brescia–Bologna (Italy) / Colorado smart corridor | All-weather + C-V2X | ★★★★☆ |
| Smart Transit | Los Angeles Metro / TfL buses | Demand-responsive transit | ★★★★☆ |
| Parking | San Francisco / Amsterdam smart parking | Reservation at hot spots | ★★★★☆ |
| Data Operation | Amsterdam / Estonia data exchange | Data assetization exploration | ★★★☆☆ |

---

## 10. Auto-Generated Assessment Report Template

### Report Structure
```
============================================================================
              Transportation Digital Maturity Assessment Report
============================================================================

[Basic Info]
Subject: ____________________
Date: ____________________
Mode: ☐ Quick (15 q)  ☐ Full (52 q)
Team: ____________________
Source: ☐ Self-assessment  ☐ Third-party  ☐ Hybrid

----------------------------------------------------------------------------
1. Overview
----------------------------------------------------------------------------
Weighted Total: _____ / 100
Maturity Level: L__ (_____)
Level Band: _____ to _____
Industry Position: ☐ Leading (top 20%)  ☐ Good (top 40%)  ☐ Average (40–60%)  ☐ Needs improvement (bottom 40%)

Radar Scores:
  Strategy & Governance (S): _____  ██████████░░░
  Data & Platform (D):       _____  ██████████░░░
  Innovation & Application (I): _____  ██████████░░░
  Connectivity & Collaboration (C): _____  ██████████░░░
  Ecosystem & Talent (E):     _____  ██████████░░░

----------------------------------------------------------------------------
2. Dimension Detail
----------------------------------------------------------------------------
[S Strategy & Governance: _____]

Strengths (score ≥ 4):
  - Sx: ____________________ (___)

Shortfalls (score ≤ 2):
  - Sx: ____________________ (___)

Recommendation: __________________________________________________

[D Data & Platform: _____]    (same structure)
[I Innovation & Application: _____]  (same structure)
[C Connectivity & Collaboration: _____]  (same structure)
[E Ecosystem & Talent: _____]  (same structure)

----------------------------------------------------------------------------
3. Gap Analysis
----------------------------------------------------------------------------
[Gap analysis tables — see Section 7]

----------------------------------------------------------------------------
4. Recommended Execution Plan
----------------------------------------------------------------------------
[Recommended action paths — see Section 8]

Short term (0–6 mo):
  1. ____________________________________ (budget: $_____)
  2. ____________________________________ (budget: $_____)

Medium term (6–12 mo):
  1. ____________________________________ (budget: $_____)
  2. ____________________________________ (budget: $_____)

Long term (12–24 mo):
  1. ____________________________________ (budget: $_____)
  2. ____________________________________ (budget: $_____)

----------------------------------------------------------------------------
5. Benchmarking
----------------------------------------------------------------------------
[Benchmark data — see Section 9]

----------------------------------------------------------------------------
6. Risk Notes
----------------------------------------------------------------------------
  1. ____________________________________
  2. ____________________________________
  3. ____________________________________

----------------------------------------------------------------------------
7. Next Steps
----------------------------------------------------------------------------
  1. ____________________________________
  2. ____________________________________

============================================================================
Disclaimer: This report is based on information available at the time and is for reference only. Re-assess annually.
============================================================================
```

---

## 11. Usage Instructions

1. **Select mode**: Choose quick or full assessment based on time and need.
2. **Assemble team**: Include IT, business, and management perspectives; 5–10 people.
3. **Score each question**: Assign 1–5 per the criteria.
4. **Compute scores**: Use the formulas in Section 5 for dimension and total scores.
5. **Generate report**: Use the template in Section 10.
6. **Build execution plan**: Use the recommendation engine in Section 8 for phased actions.
7. **Re-assess periodically**: Recommended every 12 months to track progress.
