This document discusses transportation infrastructure investment needs and congestion costs globally and in Europe. It notes that addressing congestion could free up "capacity reserves" by reducing unused network capacity. The document then examines case studies in Egypt and Indonesia to analyze capacity reserves by identifying "capacity dampers" that reduce speed and increase density. It finds both case studies showed over 40% unused capacity due to dampers like design flaws, traffic management issues, parking issues, and land use problems. It concludes by proposing a road maintenance algorithm that integrates capacity dampers and potential remedies.

1. Bishoy M. Kelleny
The German University in Cairo, Research Group of Travel Behavior Modeling
and Intelligent Transportation Systems

2. • World widely, the global roads infrastructure demand requires $16.6
trillions by 2013 (approx. 1% of the global GDP)
• In Europe, the total inland
transport infrastructure
investments per GDP is
approximately 1% in 2013
[Source: OECD]

3. • On another hand, In Europe, Congestion costs about 1% of Gross
Domestic Product (GDP) every year. [Sources: (Appendix 5 of the
Impact Assessment accompanying the White Paper, SEC(2011) 358)]
• In developing and transitional economies, these remarkable figures
become more significant (Cairo congestion losses are representing
3.6% of the country’s GDP, whilst 8.9 per cent of the country’s GDP is
allocated for roads infrastructure development and maintenance.

4. • In reference to these findings regarding the demand for transport
infrastructure investments and congestion costs, resources
allocation becomes questionable.
• Then, in light of the global tension on cutting budgets, these
“Capacity Reserves” could be a potential release for the
overwhelmed economies.
• These “Capacity Reserves” indicates the un-used fraction of the
network capacity (inhibited capacity) due to avoidable traffic
congestions.

5. • The primary research question then was how to descriptively
analyze this un-used fraction of the network capacity in terms of the
capacity damping leading parameters.
• How to reflect this basic understanding of what is so called “Capacity
Dampers” on a given link, so that a quantitative investigation can be
feasibly conducted.
• Finally, how to integrate these capacity dampers as a valuable
parameter in the road maintenance management plans.

6. • An investigative congestion
analysis was conducted with
respect to the two influencing
factors; the overall speed and
the density.
• Capacity Reserves Potential
Parameters that have direct
impact on the speed or the
density are highlighted here,
along with their symptoms.

7. • The Concept of Capacity introduced here is described as the
maximum hourly flow that can be dispatched at the roadway
segment end point (intersection) at acceptable time headway
OR
• The used carrying infrastructure (used no. of lanes).
• Hence, a declined speed, along with aggravating densities, as well as
taken-away traffic lane indicate a clear state of inhibited capacity.
• An audit form was designed to perform this analysis for both case
studies.

8. • Case Study 1: Egypt
Cairo- Kamel Sedky Street (El
Faggala Area)
• Case Study 2: Indonesia
Kesehatan Street (Sardjito Regional
Hospital Area)

9. Capacity Reserves
Parameters
Corresponding Capacity Dampers
Case Study 1: Egypt Case Study 2: Indonesia
Design Features - Pedestrian merges to the roadway-
Enforced Lane Changing Action
- Pedestrian merges to the roadway
and Bumpy road surface- Enforced
Lane Changing Action
Traffic management and
control
- Stop and go and delays due to the
unwanted turns at the local streets
leading to the segment
- Delays due to entry and exit to
hospital and medical Faculty
Parking supply and demand - Excess in parking demand - Excess in parking demand
Land use planning - Commercial activities as traffic
generator
- Illegal parking and spillover
commercial activities
- Hospital and Campus as traffic
generator
- Illegal parking and street hawker
due to weak law enforcement
Actual operational capacity 40% 60%
• Both Case Studies showed significant capacity hindrance due to the
methodologically highlighted capacity dampers.

10. • Road Network Capacity Dampers are
underrated parameter in the
Programmable Problem of Road
Maintenance Management System.
• Here is shown a developed Road Asset
Management-Capacity Reclamation
Decision Planning Algorithm that
integrates these “Dampers”, along
with their “Potential Remedial
Measures”.