Passengers Per Hour Per Direction (PPHPD)
PPHPD is a fundamental metric in transit planning that measures the maximum number of passengers that can be transported along a single direction of a transit line in one hour. This metric is crucial for system design, capacity planning, and mode selection.
Basic Formula:
PPHPD = Vehicles per hour × Passengers per vehicle × Load factor
| Transport Mode | Typical PPHPD Range | Vehicle Capacity | Frequency (veh/hr) | Operating Environment |
|---|---|---|---|---|
| Heavy Metro | 30,000-80,000 | 1,200-2,400 | 20-30 | Fully segregated |
| Light Metro | 25,000-45,000 | 600-1,000 | 20-30 | Grade separated |
| Light Rail | 12,000-20,000 | 200-350 | 20-40 | Semi-segregated |
| BRT | 10,000-30,000 | 150-250 | 60-120 | Dedicated lanes |
| Commuter Rail | 15,000-30,000 | 1,000-2,000 | 10-20 | Shared tracks |
| Monorail | 12,000-25,000 | 300-500 | 20-30 | Elevated |
System Characteristics by PPHPD:
| PPHPD Range | Appropriate Modes | Infrastructure Requirements | Investment Level | Example Systems |
|---|---|---|---|---|
| >50,000 | Heavy Metro | • Grade separation • Advanced signaling • High-capacity stations | Very High | Hong Kong MTR Tokyo Metro Paris Metro |
| 30,000-50,000 | Metro/Light Metro | • Dedicated ROW • Platform screen doors • Modern signaling | High | Singapore MRT Delhi Metro Madrid Metro |
| 15,000-30,000 | Light Rail/BRT | • Priority lanes • Station passing lanes • Traffic priority | Medium | Portland MAX Istanbul Metrobüs Lyon Tramway |
| 5,000-15,000 | Tram/Bus | • Mixed traffic • Simple stations • Basic priority | Low-Medium | Melbourne Trams Seattle Streetcar Dublin Luas |
Capacity Influencing Factors:
- Vehicle Design:
| Factor | Impact on Capacity | Optimization Methods |
|---|---|---|
| Seating Layout | 10-30% variation | Longitudinal seating |
| Door Configuration | 15-25% impact | Multiple wide doors |
| Interior Layout | 5-15% variation | Open gangways |
| Standing Space | 20-40% impact | Optimized handholds |
- Operating Parameters:
| Parameter | Typical Range | Capacity Impact |
|---|---|---|
| Headway | 90-180 seconds | Direct multiplier |
| Dwell Time | 20-45 seconds | Inverse relationship |
| Operating Speed | 25-80 km/h | Indirect impact |
| Recovery Time | 5-15% | System reliability |
- Station Design:
| Element | Design Consideration | Capacity Effect |
|---|---|---|
| Platform Width | 3-6 meters | Passenger flow |
| Access Points | 2-8 per platform | Distribution |
| Vertical Transport | 20-40% capacity | Peak handling |
| Fare Collection | 25-35 pax/minute | Entry flow |
System Performance Metrics:
| Metric | Good Performance | Acceptable | Poor Performance |
|---|---|---|---|
| Load Factor | <85% | 85-100% | >100% |
| Dwell Time Adherence | <±5 seconds | ±5-10 seconds | >±10 seconds |
| Headway Adherence | <±30 seconds | ±30-60 seconds | >±60 seconds |
| Service Reliability | >98% | 95-98% | <95% |
Design Considerations by PPHPD:
- Low Capacity (5,000-15,000):
- Simple infrastructure
- Basic signaling
- Mixed traffic operation
- Standard vehicles
- Medium Capacity (15,000-30,000):
- Dedicated lanes
- Priority signals
- Modern vehicles
- Enhanced stations
- High Capacity (30,000-50,000):
- Grade separation
- Advanced signaling
- High-capacity vehicles
- Complex stations
- Very High Capacity (>50,000):
- Full automation
- Platform screen doors
- Maximum length trains
- Multiple platforms
Implementation Success Factors:
- Infrastructure Design:
- Adequate station capacity
- Efficient track layout
- Modern signaling
- Maintenance facilities
- Operational Planning:
- Optimized schedules
- Resource allocation
- Contingency plans
- Performance monitoring
- System Integration:
- Multimodal connections
- Fare integration
- Passenger information
- Emergency response
Modern Trends:
- Technology Enhancement:
- Real-time monitoring
- Dynamic capacity adjustment
- Automated operations
- Predictive maintenance
- Passenger Experience:
- Real-time information
- Level boarding
- Climate control
- Passenger comfort
- Operational Efficiency:
- Energy optimization
- Asset management
- Staff utilization
- Maintenance scheduling
Note: All figures are approximate and may vary based on specific implementations, local conditions, and operational requirements. Actual capacity should be determined through detailed analysis of local conditions and requirements.
