Assessing network performance

Many different metrics exist to evaluate the quality of service of transportation networks. Such variety stems not only from the necessity to take into account different quality parameters (e.g. environmental, financial, legal) but also the application context (metrics for freeways are different from those for urban facilities and rural areas) and user perspective (a pedestrian demands different services from the transportation network compared to an automobile driver).

To determine how appropriately a road serves traffic demand, the United States Transportation Research Board publishes a very detailed, regularly updated manual for use by analysts and trans- portation engineers: the Highway Capacity Manual [HCM10]. Should the reader wish to know more about the broad topic of transportation planning, this is a good manual to study. It explains a set of methodologies for evaluating the capacity of freeways, multilane and two-lane highways, urban facilities (i.e. major urban arteries like avenues) and urban segments (i.e. a segment of road between two consecutive intersections), intersections with and without traffic lights, round- abouts and other network facilities. The perspectives of automobile drivers, pedestrians, bicyclists

and transit passengers (public transportation users) are all taken into account. There are some important base concepts.

• Level of service (LOS): it is one of the major concepts involved in the understanding of a network facility’s quality of service. It is typically used by analysts to more easily convey their observations to non-specialized stakeholders. LOS has six levels, ranging from A to F. A represents exceptionally good service, while F stands for the worst possible service; • Free flow speed: the average speed of vehicles running on a portion of the network when

no obstacles are present. Although similar to the concept of speed limit, free flow speed also takes into account the diminished velocity when taking turns and riding curvy roads. • Control delay: the average amount of time that a vehicle has to wait at a roundabout or

intersection (with or without traffic lights) before being able to proceed;

• Volume-to-capacity ratio: the quotient between demand in a given traffic facility and its maximum capacity (in vehicles per hour) before traffic jams occur. Values greater than 1 signify that the capacity of the road is exceeded and traffic congestions will occur. A road’s capacity can be estimated from observation or approximated using the road’s speed limit, average car length and average distance between cars, using some formula similar to2.1.7

Capacity= maxSpeed

avgTimeDistanceBetweenVehicles∗ maxSpeed + avgVehicleLength (2.1) According to the Highway Capacity Manual, for urban facilities and road segments, the values of table2.1apply when computing LOS.

Table 2.1: LOS for urban facilities and road segments Average travel speed as a percentage of free flow

speed (%)

LOS by volume-to-capacity ratio ≤ 1.0 >1.0 >85 A F >67-85 B F >50-67 C F >40-50 D F >30-40 E F ≤ 30 F F

The values of table2.2apply when computing LOS for intersections with traffic lights (sig- nalized), intersections without traffic lights (unsignalized) and roundabouts. Control delay values are higher for intersections with traffic lights because drivers expect the existence of lights as in- dicators of roads with higher volumes of traffic (causing greater delays). Also, since drivers are in control at intersections without traffic lights, delays become less predictable, reducing tolerance.

7_{As an example, for a road with speed limit of 50 km/h, considering an average time distance between vehicles of 2}

Table 2.2: LOS for intersections with and without traffic lights and roundabouts

Control delay by junction type (seconds per vehicle) LOS by volume-to-capacity ratio At intersections with traffic

lights

At intersections without traf- fic lights and roundabouts

≤ 1.0 >1.0 ≤ 10 ≤ 10 A F >10-20 >10-15 B F >20-35 >15-25 C F >35-55 >25-35 D F >55-80 >35-50 E F >80 >50 F F

Some of the most damaging impacts of a network facility on the environment are the decrease in air quality, which leads to respiratory conditions and smog; greenhouse gas emissions, which cause global warming; and noise, which, above certain levels, has negative effects on the daily life of a city’s inhabitants.

The European Parliament and Council have established regulations with the purpose of keep- ing air pollutants in the atmosphere below certain levels to preserve human health and vegeta- tion [Eur08]. They also enforce limit levels for vehicle manufacturers, regarding both air pollutant emissions [Eur07] (called Euro standards, the last of which is Euro 6), and greenhouse gas emis- sions [Eur09]. Computational models have been developed with the purpose of describing average emission factors for different classes of vehicles under several operating conditions, such as the Handbook Emission Factors for Road Transport, also known as HBEFA [INF]. This model is implemented in SUMO.

The legislation for maximum noise levels is not so well defined, but there are studies from accredited authorities, like the United States Environmental Protection Agency, concerning safe levels for the protection of human health (both indoors and outdoors), some of which date back to the 1970s [U.S78]. In Europe, maximum noise levels are not enforced at a federal level, but some directives [Eur02] suggest the need to develop methodologies for the assessment and man- agement of environmental noise. One of the results of those directives was the development of the Harmonoise model for the estimation of noise caused by road traffic and other transportation infrastructures such as train rails. Like HBEFA, the Harmonoise model is implemented in SUMO.