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Build a Port Congestion Aware Green Drayage Route Planner

Correlate Singapore real-time traffic camera and road incident data with electric and diesel heavy prime mover fleets. Optimize container hauling routes to minimize carbon emissions during port corridor congestion.

Business OperationsHosted by Vera

What you are building

Correlate Singapore real-time traffic camera and road incident data with electric and diesel heavy prime mover fleets. Optimize container hauling routes to minimize carbon emissions during port corridor congestion.

Green logistics fleet coordinator

Ingest Singapore Expressway camera images and real-time congestion incidents via open data APIs.

Extract speed bottlenecks on primary freight arteries including AYE and West Coast Highway.

Calculate vehicle emissions differentials between electric haulers and diesel trucks idling in queues.

Synthesize dynamic route adjustments and output emission reduction audit logs for corporate ESG reports.

Live fleet dispatch console displaying arterial speed estimates, hauler powertrain types, and rerouting prompts.

Use mock traffic incident payloads conforming to data.gov.sg real-time traffic condition datasets. Starter examples below are synthetic. They are not downloaded records.

Singapore open data API Leverages the data.gov.sg real-time API specifications for traffic conditions and speed bands along Singapore port expressways.

dspy, httpx, pydantic. DSPy compiles robust prompt pipelines that optimize emission factor evaluations and route trade-off reasoning. Instruction-tuned model evaluated with DSPy teleprompters for zero-shot route selection accuracy.

Submit runnable source, pinned dependencies, setup commands, a working interface, example outputs, and a recorded end-to-end demo. Include tests and an action log.

Processes real-time expressway congestion metrics structured according to data.gov.sg schemas.

Reroutes diesel vehicles when bottleneck delay exceeds 30 minutes to reduce idling carbon footprint.

Outputs an ESG-compliant trip record quantifying estimated CO2 savings in kilograms.

```json [ { "input": { "trip_id": "TRIP-EV-881", "vehicle_type": "DIESEL_EURO_6", "origin": "Jurong_Island", "destination": "Tanjong_Pagar_Distripark", "corridor": "AYE", "corridor_speed_kmh": 12, "normal_speed_kmh": 60, "distance_km": 18 }, "expected_output": { "reroute_recommended": true, "alternate_corridor": "WEST_COAST_HIGHWAY", "estimated_time_saving_minutes": 22, "avoided_idling_co2_kg": 4.8 } }, { "input": { "trip_id": "TRIP-EV-882", "vehicle_type": "BATTERY_ELECTRIC", "origin": "Tuas_South", "destination": "Pasir_Panjang", "corridor": "AYE", "corridor_speed_kmh": 55, "normal_speed_kmh": 60, "distance_km": 25 }, "expected_output": { "reroute_recommended": false, "alternate_corridor": null, "estimated_time_saving_minutes": 0, "avoided_idling_co2_kg": 0 } } ] ```

Outputs routing recommendations strictly as suggestions for fleet dispatchers; vehicle steering is not automated. Use mock external writes. Require human review before any real deployment.

Rules

Outputs routing recommendations strictly as suggestions for fleet dispatchers; vehicle steering is not automated. Use mock external writes and human review.

How work is evaluated

Evaluation

Processes real-time expressway congestion metrics structured according to data.gov.sg schemas. Reroutes diesel vehicles when bottleneck delay exceeds 30 minutes to reduce idling carbon footprint. Outputs an ESG-compliant trip record quantifying estimated CO2 savings in kilograms.

Submission format

Runnable source, pinned dependencies, setup commands, working interface, example outputs, recorded demo, tests, and action logs.

Datasets

Public datasets, plus the private datasets you have access to.

How submissions are scored

Dimensions
4 scoring checks
Binary
1 pass or fail dimensions
Ordinal
3 scaled dimensions
Dimension 1

Complete workflow

Ingest Singapore Expressway camera images and real-time congestion incidents via open data APIs. Extract speed bottlenecks on primary freight arteries including AYE and West Coast Highway. Calculate vehicle emissions differentials between electric haulers and diesel trucks idling in queues. Synthesize dynamic route adjustments and output emission reduction audit logs for corporate ESG reports.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 2

Correctness and evidence

Processes real-time expressway congestion metrics structured according to data.gov.sg schemas. Reroutes diesel vehicles when bottleneck delay exceeds 30 minutes to reduce idling carbon footprint. Outputs an ESG-compliant trip record quantifying estimated CO2 savings in kilograms.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 3

Review interface

Live fleet dispatch console displaying arterial speed estimates, hauler powertrain types, and rerouting prompts.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 4

Safe execution

Outputs routing recommendations strictly as suggestions for fleet dispatchers; vehicle steering is not automated.

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Learning goals

  • Ingest Singapore Expressway camera images and real-time congestion incidents via open data APIs.

  • Extract speed bottlenecks on primary freight arteries including AYE and West Coast Highway.

  • Calculate vehicle emissions differentials between electric haulers and diesel trucks idling in queues.

  • Synthesize dynamic route adjustments and output emission reduction audit logs for corporate ESG reports.

Resources

Dataset notes

Use mock traffic incident payloads conforming to data.gov.sg real-time traffic condition datasets. Supplied starter examples are synthetic, not source extracts.

Challenge setup

Challenge input

Input details are not configured.

DSPy

Prompt and LM program optimization framework.

Evaluated output

No output checks are configured.

Evaluation checks
  • Ingest Singapore Expressway camera images and real-time congestion incidents via open data APIs. Extract sp...
  • Processes real-time expressway congestion metrics structured according to data.gov.sg schemas. Reroutes die...
  • Live fleet dispatch console displaying arterial speed estimates, hauler powertrain types, and rerouting pro...
Configured evaluation evidence
  • 2 public reference cases
Configured runtime
  • 3 configured tools

Shows the first task, up to three tools, and up to three evidence items.

View technical recipe

Configured tools

Action Space
  • DSPy · Optional
Training Infra
  • DSPy · Optional
Orchestration
  • DSPy · Optional

Evaluation contract

  • Complete workflow · Weight 40
  • Correctness and evidence · Weight 30
  • Review interface · Weight 20
  • Safe execution · Weight 10

Reference cases

  • 2 public reference cases

Workflow tasks

No workflow tasks are configured.

Recipe freeze marker

No recipe freeze time is recorded.

Frequently Asked Questions about Build a Port Congestion Aware Green Drayage Route Planner