RESEARCH APPROACH ABOUT RELIABILITY OF ... - BHLS - HOME

COST 

(European Cooperation in Science and Technology) 

UNIVERSITA’ DEGLI STUDI MEDITERRANEA 

DI REGGIO CALABRIA 

Facoltà di Ingegneria 

Short Term Scientific Mission – ITALY 

Manchester BHLS 

RESEARCH APPROACH ABOUT 

RELIABILITY OF BHLS 

COST research project 

(Action TU 0603 - Buses with a high level of service) 

Professor: 

Domenico Gattuso 

Student: 

Salvatore Napoli

INTRODUCTION 

pag.3 

CHAPTER I – REASEARCH APPROACH 

1.1. Introduction pag.4 

1.2. State of the performance indicators systems for Public Transport pag. 4 

1.3. General approach to the evaluation of performance indicators pag.5 

1.4. Approach to the analysis of reliability parameters pag.8 

1.4.1. Definition of reliability pag.9 

1.4.2. Components of public transport reliability pag.1 

1.4.3. Reliability measurement methods and monitoring processes 

proposed by some literature studies 

CHAPTER II – 

PROPOSED APPROACH TO EVALUATE 

RELIABILITY ON PUBLIC TRANSPORT SERVICES 

0 

pag.1 

2.1. Definition of reliability pag.1 

8 

2.2. Defining the type of service pag.1 

9 

2.3. Approaches for estimating the value of reliability pag.1 

9 

2.3.1. Run based services pag.1 

9 

2.3.2. Frequency based services pag.2 

CHAPTER III – ORGANIZATION AND EXECUTIONS OF THE 

RELIABILITY ANALYSIS ON THE FIELD 

1 

1 

3.1. Operations on site : Characteristics of the analyzed line pag.2 

3 

3.2. Collected Data pag.2 

8 

3.3. Reliability Indicators Valuation pag.3 

8 

3.4. Overview and conclusions pag.4 

3 

Bibliography 

pag.4 

4 

| Short term Scientific Mission -ITALY 2

INTRODUCTION 

The research for the Short Term Scientific Mission in COST (Action TU 0603 - Buses 

with a High Level of Service), supported by European Community, achieves two specific 

goals: 

- analysis of a “Bus High Level Service” for an European city (Manchester); 

- analysis of performances of a BHLS line in Manchester, and in particular reliability 

of BHLS service. 

The first phase of research includes a literature analysis which tries to identify the technical 

features concerning BHLS transport systems. The second phase is characterized by on site 

analysis through the utilization of a Template provided by COST and through several 

meetings with the company management. During this phase it was very important to meet 

the management that organizes the transport system (GMPTE), to obtain information about 

vehicles and line features, and future developments. 

After the collected Data Base valuation, the third and last phase was developed which 

consists of an analysis of the reliability of a specific line. There were descriptions about the 

line and its critical points, focusing the attention on the valuation of several reliability 

indicators in concordance with the data collected during the short mission. 


CHAPTER I – RESEARCH APPROACH 

1.1. Introduction 

As in the productive field, in which there are many regulations on quality, it was also 

necessary to introduce the same regulations to the services field because of their different 

backgrounds. 

Many different users and community requirements must be satisfied because of the 

important role that the transport field has in our society, the complexity of its features, the 

strong demand to improve the level of service and efficiency production, and the need to 

respect the environment. 

The basic concepts such as the system view, the process management, the continuous 

improvement, customer satisfaction and all contents that are reported by ISO9000 standard 

and Total Quality Management, represent the reference for all the organizations that decide 

to direct their management according to the principles of quality. 

Every transport company must analyze the characteristics of realized service and define a 

set of standards, through efficiency and effectiveness factors of the system; these are 

obtained through the analysis of performances offered to the customers and continuously 

monitored and updated. 

There are different studies in literature that analyze these factors and provide indicators 

and approaches to the quantitative measure; the most important indicators are the 

following, focusing on the reliability indicators. 

1.2 State of the performance indicators systems for Public Transport 

The evaluation of the performances of a public transport system is a complex problem due 

to the straight co-relation among the different objectives pursued by different stakeholders 

to express an opinion (service provider, customers, community). 

According to the service provider, namely the operator of public transport system, its main 

interest is to produce the service in a way to satisfy the demand, compatibly respecting the 

resources constraint. Users who represent those who are using the public service would 

like to obtain the service as cheap as possible, but also have it be reliable and with a good 


level in quality and safety. 

Each social component (service provider, users and community) has different needs and 

therefore its own perception about the performances of the public transport system. The 

service provider, according to a far-sighted business, also considers the customer and 

community needs. 

Usually, the public transport evaluations are developed to check the differences between 

actual and past performances, obtaining a comprised evaluation during the time. The 

evaluation can also be used to provide a benchmark with another company, or as the best 

term of comparison. Obviously, the comparison needs to be founded on shared and 

uniquely determined parameters. 

In the field of specialized literature (Coelli et al., 1998; Russo and Varipapa, 2000; 

Cantarella and Di Gangi, 2002), methods to analyze performances of public transport 

companies are classified in two different types: 

• parameters methods; 

• non- parameters methods. 

Actually, to analyze the performances of a public transport company the indicators 

analysis is used, but there are also other methods like stochastic frontiers, econometric 

models of production, and Data Envelopment Analysis whose parameters need to be 

calibrated; further more these methods are being developed. 

Between the indicators based methods it’s possible to distinguish two approaches: the first 

assumes that just one indicator is enough to evaluate the system performances (Hensher, 

1992; Obeng et al., 1992; Oum and Yu, 1995; Preston, 1995; Tretheway and Waters II, 

1995). On the other hand, the second approach is based on the research of a set of 

indicators to provide an analytical approach to analyze the system (OCSE, 1980; Miller et 

al., 1984; Fielding et. al., 1985; MacDorman, 1988; Gattuso, 1992; Di Gangi and Montella, 

1995; CERTU, 1997; Gattuso et al., 2002). This work focuses attention on the second 

approach provided before and on the evaluation methods of indicators about 

reliability/regularity/punctuality that are linked to both a service provider and users. 

1.3 General approach to the evaluation of performance indicators 


The set of indicators approach, developed by different authors, (Fielding et al., 1985) 

focuses attention on the public transport system performances evaluations according to the 

service provider perspective. 

Any uniform set of transit performance indicators must be constructed with due regard to 

both their intended use, and to the limitations of available data. Although transit operators 

are apprehensive about the use of performance indicators, they should appreciate the 

benefits. Performance indicators provide an opportunity to elevate the general 

understanding of transit's capabilities and costs by emphasizing the productive use of 

capital and labor, rather than focusing performance only on ridership and operating costs. 

According to Fielding et al. during the evaluation it’s important to refer to two types of 

indicators: 

efficiency indicators, that measure the relationship between the input used in the 

system productive process and the output used in the service provided; 

effectiveness indicators, that measure the system capability to pursue a determinate 

objective. 

In the proposed conceptual model (see Fig. 1.1), the individuation of effectiveness and 

efficiency indicators is linked with the knowledge of data about: 

service inputs (workforce, capital, energy); 

service outputs, (vehicles-hour, vehicles-km, seats-km); 

utilization of service provided (passengers, passengers-km, revenues). 

SERVICE 

INPUTS 

Workers 

Capital 

Energy 

Cost efficiency 

Cost Effectiveness 

SERVICE 

OUTPUTS 

Vehicles-hour 

Vehicles-Km 

Capacity-Km 

Service Effectiveness 

UTILIZED 

SERVICE 

Passengers 

Passengers-Km 

Profits 


Fig. 1.1 – Conceptual model of Fielding et al. (1985) 

An opportune ratio between output and input measures, allow to define the costs efficiency 

indicators (work efficiency, vehicles efficiency, efficiency in fuel consumption, efficiency 

of maintenance, output per unit of cost). An opportune ratio between output and input 

measures, allow to define the costs efficiency indicators (work efficiency, vehicles 

efficiency, efficiency in fuel consumption, efficiency of maintenance, output per unit of 

cost). 

The effectiveness costs indicators are derived by the ratio between utilized service and 

input measures ( utilized service per unit of cost, revenues production per unit of cost). 

Finally, with the ratio between utilized service and output measures, it’s possible to obtain 

the service effectiveness indicators (service utilized, operative safety, revenues production, 

public economic support). 

One evolution of the conceptual scheme is provided by Gattuso (Gattuso, 1992), according 

to whom evaluates the public transport system performances, the service provider has to 

quantify three different aspects: 

- system productivity; 

- users satisfaction level (effectiveness); 

- regularity and reliability of the services. 

The first aspect is estimated through the classic parameters of efficiency (the efficiency 

describes the relations between provided output and resources used for the production). 

The level of satisfaction of users request can be obtained through parameters of 

effectiveness and of utilization of the service provided. 

Finally, it is important to underline the difference between regularity and the reliability of 

the service; regularity checks the differences between the provided service and the 

scheduled service (e.g. time of runs), while reliability considers the probability that the 

system can have a crisis (e.g. failures and accidents). The definition of parameters above 

(Fig.1.2) is linked to the relations among the different types of measures: 

- company’s resources; 


- provided service; 

- scheduled service; 

- utilized service. 

Fig.1.2- Scheme of the relations among service provider interest 

1.4 Approach to the analysis of reliability parameters 

The mobility problems and in particular, the cities' congestion are tightly linked with the 

modal disequilibrium choosing the means of transportation. In fact, private cars are chosen 

over public transport service. 

The users' choice, for short trips in the urban context, is influenced mostly by the time 

attribute. For this reason the public transport company commitment is not only to try to 

respect the travel time and the adherence between scheduled time and real time, but also to 

try to reduce the waiting time at the stops and to guarantee more information to the 

passengers. 

It’s easy to understand the need to adopt opportune parameters that allow the analysis of 

the system and the individuation of problems to fix in order to obtain a service that can be 

defined as “reliable” from the users. 


1.4.1. Definition of reliability 

There are different definitions of reliability, particularly within transport, and different 

modes have different sources of reliability which relate to uncertainty within individual 

aspects of their journey. 

The term ‘reliability’ within a transport context relates to an uncertainty in the time taken 

to travel from the start to the end of a person’s journey. This uncertainty means that a 

person must make some allowance in the timing of their journey to adjust for this 

uncertainty so that they can still reach the end within a desirable time span. Reliability is 

important for operators and passengers alike. For operators, unreliable services cause 

difficulties in timetabling and resource planning. Also, unreliable services are typically 

loaded more unevenly, causing issues of passenger overloading and possible breaching of 

loading licenses. 

Valuations of reliability can be estimated using revealed and stated preference data. 

However, most valuations are undertaken using stated preference techniques, where a 

survey asks respondents about hypothetical situations. From these situations, values can be 

determined for changes in average delay and the variation in delay (which are both service 

characteristics), or by using more complex scheduling models that focus more on 

passenger travel information. 

The concepts of reliability can be divided into departure time, (punctuality and variability 

around expected departure time), travel time (variability around expected travel time) and 

arrival time (punctuality and variability around expected arrival time). 

Besides the various new activities around the reliability of transport systems, there is an 

OECD working group preparing a report on the “Surface Transport Networks: Improving 

Reliability and Levels of Service”. This report will be edited in September 2009 (JTRC, 

2009). 

The transport reliability literature review, done by the OECD working group reveals a 

number of ways in which transport reliability can be defined. A useful definition 

recognizes that network users time their actions according to expected network 

performance. That’s why the OECD defined reliability as “The ability of the transport 


system to provide the expected level of service quality, on which users have organized 

their activities”. According to this definition, reliability can be improved either by 

supplying better reliability or by changing expectations of the level of reliability. 

1.4.2 Components of public transport reliability 

The most important components of public transport reliability are the following: 

• punctuality, is defined as adherence to schedule and is measured through the mean 

delay percentage outside of comfort zone ( e.g. un minute – early to 5 minute late); 

• cancellations, are defined as whether scheduled bus actually arrives; cancellation 

can happen at the departure or during the trip. Can be measured by mean delay. 

• variability, around expected time, it’s usually measured using standard deviation 

Tab.1.1 - Notion of public transport reliability (Vincent, 2008) 

Term Definition Standard measures 

Punctuality 

Adherence to schedule 

Mean delay 

• departure 

Percentage outside of “comfort 

• arrival 

zone”(e.g.1min-erlay to 5 min late) 

Cancellations 

• at departure 

• during trip 

Variability around expected 

• departure time 

• travel time 

• arrival time 

Whether a scheduled train or bus 

actually arrives 

Spread around “expected x time” 

Note: “expected x time” can be: 

• average time; 

• targeted time (e.g. 

scheduled time) 

Mean delay (which is a function of 

headway) 

Standard deviation 

Waiting time variability Spread around average waiting time Standard deviation 

*The UK rail industry uses “reliability” to refer to the term described here as “cancellations” 

The interpretation of variability depends crucially on the meaning assigned to the term 

‘expected value’. For example, consider a bus that is always late relative to schedule, by x 

minutes: 

if ‘expected value’ is based on the bus schedule then the bus is exhibiting 

variability; 

if ‘expected value’ is based on the expectations of a passenger not familiar with the 

bus then the bus is exhibiting variability; 


ut if ‘expected value’ is based on observed lateness over the past few months then 

the bus would be exhibiting no variability. 

In general, throughout the literature, sources agree that variability should refer to the 

unpredictable component of variability, i.e. the component of variability that remains after 

predictable variations (e.g. longer trip times during peak hours) are removed. 

The concepts of reliability can be further broken down into departure time, travel time and 

arrival time, as shown in Table 1.2. 

Components 

Departure time 

Travel time 

Arrival time 

Tab.1.2 - Concepts of reliability ( Vincent, 2008) 

Subcategories 

Punctuality 

Variability around expected departure time 

Variability around expected travel time 

Punctuality 

Variability around expected arrival time 

Note: departure time punctuality + travel time variability= arrival time punctuality 

Most studies of reliability focus on either travel time variability or arrival time variability. 

Only a few studies direct attention to waiting time variability. 

The relationship between travel time variability and arrival time variability is worth noting. 

If departure time is certain (as is presumed in a number of studies) then travel time 

variability is equivalent to arrival time variability. In such studies, a researcher can focus 

on either travel time variability or arrival time variability. 

1.4.3 Reliability measurement methods and monitoring processes proposed by some 

literature studies 

The study of “Land Transport New Zealand Research Report” (Vincent, 2008) about 

Measurement Valuation of Public Transport Reliability provides an overview of the 

concept of reliability, particularly the impact that service reliability has on passengers and 

operators. The ‘reliability’ within a transport context relates to an uncertainty in the time 

taken to travel from the start to the end of a person’s journey. 

A reliability valuation approach is applied to a New Zealand context. Finally, the 

implications of the approach for planning are outlined. 


Three main measures are used for valuing reliability: 

- value of delay minutes (average minutes’ lateness); 

- reliability ratio (variance approach); 

- scheduling costs. 

The main approaches to estimate the value of reliability are functions of delay. The 

following are some of the available models: 

 

The mean delay approach, incorporates either delays or expected delays into the 

estimated utility function. The approach focuses on delays relative to schedule and 

therefore is only applicable to public transport. The model equation is:: 

Utility = T + λ E(DM) 

where T = scheduled travel time; E(DM) = expected delay minutes after schedule; 

λ= model parameter. 

 

The variance delay approach attempts to value variability in travel times explicitly 

by incorporating it into an estimated utility function. The main measures of 

variability used are standard deviations and coefficients of variation. The variance 

delay approach is commonly applied, perhaps because it is relatively easy to 

implement and it produces reliability ratios. 

The reliability ratio is commonly associated with studies where respondents are 

presented with representative trips in a stated preference format. To calculate the 

reliability ratio, researchers estimate a utility function and then divide the 

coefficient on the standard deviation of travel time (generally) by the coefficient of 

travel time. The reliability ratio can be easily used to value improvements in 

transport reliability. The model equation is: 

Utility = T + λ f(S) 

where T = scheduled travel time; f(S) = Standard Deviation (SD) or coefficient of 

variation of travel time; λ = model parameter. 

 

The scheduling cost approach directs attention away from actual variability and 

towards the costs of variability, i.e. the costs associated with being early or late. 

The scheduling cost approach presents respondents with a Preferred Arrival Time 

(PAT) (e.g. a time when they want to be at their destination) and gives them a 


choice of alternatives. Each alternative has different implications for the 

respondent’s arrival relative to their preferred arrival time. The scheduling cost 

approach uses their responses to infer the cost associated with being early or late to 

the destination. The scheduling cost approach is often preferred in academic studies 

because it has strong theoretical grounds and perhaps because it focuses on the 

main reasons why travelers value reliability: they want to get to work on time 

without leaving home too early. The model equation is: 

Utility = αE(T) + βE(SDE) + γE(SDL) + θP 

where E(T) = expected travel time; E(SDE) = expected time before Preferred 

Arrival Time (PAT); E(SDL) = expected time after PAT; P = probability of arriving 

after PAT; β, γ, θ = model parameters. 

For passengers, unreliable services cause adjustments in an individual’s desired trip 

making behavior to account for the possibility of a service not operating ‘as normal’: 

Arrival time variability causes the public transport user to arrive at their destination 

late and/or forces the traveler to take an earlier service. Arrival time variability can 

also cause the traveler to arrive at their destination too early. 

Departure time variability has the following costs for public transport users: 

• increased waiting times for the traveler. Late services cause travelers to have 

to wait some time after arriving at their stop or station. Early services also 

increase waiting times because they force the traveler to wait for the next 

service; 

• increased concern and anxiety caused purely by uncertainty about when the 

next service will arrive. 

In-vehicle-time (IVT) variability has the following costs for public transport users: 

• increased anxiety caused by fears of arriving late at the destination; 

• increased anxiety caused by uncertainty about how long they will have to 

spend in the service. 

The relationship between travel time variability and arrival time variability is worth noting. 

If departure time is certain (as is presumed in a number of studies) then travel time 

variability is equivalent to arrival time variability. In such studies, a researcher can focus 

on either travel time variability or arrival time variability. 


. 

The study “The (in)efficiency of trams and buses in Brussels: a fine geographical 

analysis”, proposed by Courtois and Dobruszkes (2008), analyzes the geography of traffic 

conditions affecting the trams and buses of Brussels’ main mass transit network; the goal 

of this study is the valuation of three indicators: 

• commercial speed; 

• irregularity; 

• lost time. 

This analysis is based fundamentally on the data that STIB/MIVB collects through its 

Operating Aid System (OAS); this system must be able to follow the vehicles’ progress in 

real time and take action if problem arose. The approach involved two inputs are as 

follows: 

the raw data were extracted from the OAS (segment by segment, line by line, in first 

one and then the other direction) and pre-processed to be regrouped by 15, 30 or 60 

minute periods, and then they were regrouped in a single database; 

Then digitizing the STIB/MIVB network completely and assigning the STIB/MIVB’s 

standard code to each segment (geocoding) enabled to connect the data with their 

segments for mapping and analysis. 

The data that they used refer to all the segments between stops that were covered by the 

operator’s trams and buses during the week from 6 a.m. to 11 p.m. for one month (this 

period was sufficiently extensive to avoid atypical situations). In addition, they excluded 

the 5% of extreme travel times (minima and maxima) that often correspond to unusual 

situations (vehicle break-downs, driver absent or late when s/he theoretically should have 

clocked in, one-off work done at the start or end of the day, and so on). 

This study added to the classical measurement of commercial speed that of irregularity of 

service and time lost by the vehicles; these three indicators would give complementary 

information about the network’s performances on the segment level. 

The analysis underlines how great the variations in commercial speed and irregularity of 

service are in the course of a day. It is possible to see a parallel between the drop in 

commercial speed and increase in irregularity, which complicates the operator’s job even 

more. 


Analysis of commercial speed 

Commercial speed gives an idea of the network’s performance through the speed at what a 

trip may be made. For the passenger, it contributes to the total time of her/his trip. For the 

operator, the commercial speed has a direct impact on the number of vehicles to put on line 

to the extent that this figure is directly linked to the route travel time and frequency of 

service. The analysis underlines the tram and the bus line segments’ rankings by 

commercial speed. It is possible to see the segments that are covered at very low 

commercial speeds. 

Analysis of irregularity over a given period 

The segment travel times vary greatly over time. Beyond the peak and off-peak 

performance differences, one must also consider the variations over a given period, for 

example, the morning rush hour. For the operator, the variability of travel time for a given 

period makes it more difficult to draw up the timetables. For the passengers, the 

uncertainty of travel times means that they have to allow greater safety margins for all trips 

that require that they reach their destination at a specific time. 

The irregularity of travel time is easy to detect through their standard deviations for a given 

period. This methodological approach shows that the geography of irregularity during the 

morning peak hours is not identical to that of commercial speed. 

Analysis of time lost by the vehicles in a day 

As soon as the commercial speed fluctuates, one can assume that the deterioration in the 

travel time compared with the periods of maximum fluidity (early in the morning or late at 

night) entails a time loss for the vehicles. This time loss can be calculated from the 

difference between the travel time at each period of the day and a fluid reference period (in 

that case, from 9 to 10 p.m.), multiplied by the number of passes on the line. 

In this analysis it is obtained the amounts of time lost on the bus and tram networks at the 

end of a day calculated from the differences in travel times compared with the fluid 

situation observed between 9 and 10 p.m. 

Measuring transport reliability consists to define indicators that provide appropriate 

measures of the inconsistency in travelling within the network. It is possible distinguish 

between the network provider or operator and the user point of views. For the network 


provider the reliability indicators must focuses on the system robustness (or vulnerability) 

and on its operating performance. The used indicators are for example, the connectivity of 

the network, its capacity to respond to unpredictable demand or the supply conditions 

offered by a degraded network, etc. 

From the user point of view, the invariability of the experienced travel time corresponds to 

the main index. Indicators must focus on this travel time variability quantification. Several 

definitions for travel time reliability exist and many different relevant indicators have been 

proposed (Lomax et al. (2003); Van Lint (2004)). Some of them are statistical range 

indicators such as the “Standard Deviation” or the “Variation Coefficient” computed for a 

given time of day or day of a week. Other approaches are related to the Buffer Index, the 

tardy trips and width of the travel time distribution. Depending on the travel time 

reliability study, it may be more appropriate to use one indicator than another. For 

example, the standard deviation (or spread) of travel times can be advised as cost effective 

measures to monitor travel time variation and reliability, however the buffer index 

indicator can be more useful for the users information. 

In the literature, the Buffer Index appears to relate particularly well to the way in which 

travelers make their decisions (TRB/NCHRP, 2008). The investigations are focused on 

these indicators to compare the impact of the ramp metering on the travel time reliability. 

Buffer Index (BI): is defined as the extra time a user has to add to the average travel time 

so one is on time 95% of the time. It is computed as the difference between the 95th 

percentile travel time (TT 95 ) and mean travel time (M), divided by mean travel time. 

1 

2BI = (TT 95 –M)/M 

3 

The 95th Percentile Travel Time (TT 95 ) expresses how much delay will be on the heaviest 

travel days. The Buffer Index is useful in the user’s assessment of how much extra time 

has to be allowed for uncertainty in the travel conditions. It hence answers simple 

questions such as “How much time do I need to allow?” “When should I leave?” For 

example, if the average travel time, M = 20 minutes, the Buffer index, BI=40 %, the Buffer 

time = 20 × 0.40 = 8 minutes. Therefore, the traveler should allow 28 minutes for their trip 

in order to ensure on-time arrival 95 percent of the journey time. 

4 


Planning Time Index: total time needed to plan for an on-time arrival 95% of the time as 

compared to the free flow travel time. It is computed as 95th percentile travel time (TT 95 ) 

divided by free-flow travel time (TT free-flow ): 

5 

6PTI = TT 95 / TT free-flow 

7 

For example, a PTI= 1.60, TT free-flow = 15 minutes, a traveler should plan 24 minutes in total 

to ensure on-time arrival at 95% of the time. 

Because these indicators one can use the 95-percentile value of the travel time distribution 

as a reference of the definitions, they take into account more explicitly the extreme travel 

time delays. 

Travel Time Index: average time it takes to travel during peak hours compared to free flow 

conditions, computed as mean travel time divided by free flow travel time. 

8 

9TTI = M/ TT free-flow 

10 

TTI indicator is known as a congestion indicator and will be used to compare the reliability 

with the congestion states (see Fig.1.3). 

Fig. 1.3- Reliability indicators relationship (Turner, 2006) 


CHAPTER II – PROPOSED APRROACH TO EVALUATE RELIABILITY ON 

PUBLIC TRANSPORT SERVICES 

In this chapter will follow a scientific methodology useful for application in different 

contexts in order to analyze and compare different performances of Public Transport. 

There is a different approach in function of the service type (represented by runs or 

frequency), because the user behavior is different and changes with the different 

company’s supply. The following approach was used during the BHLS studying phase 

within the missions abroad. 

2.1 Definition of reliability 

A useful definition recognizes that users plan their actions in function of the network 

performances. That’s why they defined reliability as “The ability of the transport system to 

provide the expected level of service quality, on which users have organized their 

activities” (OCDE, September 2009). According to this definition, reliability can be 

improved either by supplying better reliability or by changing expectations of the level of 

reliability. The expectations of public transport reliability are linked with the service type 

(runs or frequency) and from these differences will follow different user behavior, 

according to the random utility theory in which the user makes a “rational decision.” 

Reliability indicators, that are tightly linked to the objectives of different parties (service 

provider, users and community), need to be evaluated differently in the two types of public 

transport service. 

Particularly reliability can be subdivided as: 

punctuality- the adherence between the scheduled time and the real time (at the 

departure, during the trip and at the destination arrival); 

regularity- the respect of the frequency during a window time; 

crisis- the capability to fix unexpected problems that can break the regularity of 

service. 


2.2 Definition of the service typologies 

The supply system for public transport can be modeled through the graph theory. 

Particularly there are two different methods to represent, and it depends if the link i-j is just 

a spatial connection or also has a temporal connotation given by the time in which the 

service is active. 

Subsequently the word “line” will be used to indicate the path followed by a mean of 

transportation made by a sequence of stops; on the other hand the word “run” will be used 

to refer to a space-time path, made by a sequence of stops with a set time of departure and 

arrival at the bus stop. 

It follows that the generic link that represent the service, in the first case, will have 

associated the line features, on the other hand the second will have the features of the 

single run; it will be possible to obtain the system representation through a line based 

graph for frequency network and a run based graph for the time approach. 

2.3. Approaches for estimating the value of reliability 

2.3.1 Run based services 

The reliability, as said, is mainly function of delay time that present the transport system in 

the different singular points (stops) toward to a scheduled time. 

The steps to be followed are generally carried out in this order: 

characterization of the system from the infrastructural point of view; 

definition and modeling of the transport lines; 

modeling of the runs within each transport lines; 

analysis of the transport company database; 

confrontation between real times (relieved on board) and scheduled times; 

construction of the diachronic graph with the real time and scheduled time; 

calculation of the reliability indicators. 

The first analysis of reliability characterizes the transport system by the infrastructural 

features of the lines and subsequently focalizes the attention on the runs of each lines. 


This phase is characterized by the collection of geometric data of the transport lines and 

the analysis of the technological characteristics of the transport vectors and information 

(ITS, Intelligent Transport System). 

Subsequently the analysis is based on the relief on board of transport system data and then 

subsequently on the confrontation between real times (relieved on board) and scheduled 

times; in this way it is underlined the value of delay time that the transport system 

produces on the terminals and on the stops with negative consequences for the users. 

The differences between real times and scheduled times can be underlined trough an 

instrument that is the diachronic graph. The diachronic graph consists of representing 

every run of every line, with the representation of the time variable related to the schedule 

of the service. The graph produced with this change is said diachronic graph: one general 

exemplification inherent the representation of the runs is brought in the Fig.2.1. 

. 

Fig.2.1- Example of diachronic graph. 

Within the diachronic graph it is possible to represent the differences between the real 

times and scheduled times underlining the possible critical points of the system (Fig. 2.2). 

This procedure must affect every run of the transport lines. 

. 


Fig.2.2- Example of diachronic graph that underlines differences of the times 

The calculation of reliability indicators is based on the relief of the delay times and then on 

the irregularity of the transport system. 

The main reliefs that can be effected are the following: 

differences between the real times and scheduled times on the stops and on the 

terminals; 

delay time accumulated; 

number of the runs deleted; 

number of the runs that respect the scheduled time for the stops and the terminal. 

With these measures it is possible to obtain a series of reliability indicators, that can be 

calculated as follows: 

Variability on the stops(Arrival Time, Departure Time, Travel Time): V= ∑∆ i / N° f 

; 

Crisis of System : % failed runs: F= R F /R T ; 

Delay accumulated on stops: D= ∑ D i ; 

% runs on time : OR= R O /R T . 

2.3.2. Frequency based services 


The frequency-based modeling approach refers to a line-based supply representation, for 

which assignment results can be carried out in terms of average flow on each line. 

The system line representation, allow to: 

a) not explicit the service time; 

b) share the access/egress system with other systems; 

c) reduce to the most important components the services network. 

On the Fig. 2.3 is showed a scheme of a particular high frequency network, whose stop 

node is divided by 2 different nodes, one represents the access/egress node that is the 

stop’s spatial location, the other (called diversion node) represent the happened decision of 

the user to use the public transport service in that stop; all these nodes are connected by 

links, as showed on Fig. 2.3. 

Fig. 2.3 - Modeling of stop for high frequency services 

The steps to be followed can be, in general, resumed in: 

characterization of the system from the infrastructural point of view; 

definition and modeling of the transport lines; 

modeling of the service line within the System Transport; 


analysis of the transport company database; 

confrontation between real times (relieved on board) and scheduled times; 

calculation of the reliability indicators. 

The calculation of reliability indicators is based on the relief of the passages times on the 

stops and then on the irregularity of the transport system in this stops. 

The main reliefs that can be effected are the followings: 

differences between the real frequency and scheduled frequency on the stops; 

differences between the frequency during the different time periods; 

number of the runs that failed the scheduled frequency; 

the dwell time on the stops of the line; 

The main reliability indicators that it is possible to obtain are the follows: 

Frequency irregularity (FR), expressed as Standard Deviation of average frequency: 

FR=[∑ i=1,..,n (x i –AF) 2 /n] 1/2 

where: 

n = number of passages; 

x i = punctual frequency; 

AF = Average frequency. 

RELIABILITY, % of runs that respect the scheduled frequency: 

RELIABILITY = 1 - R F /R Tot ; 

where: 

R F = number of failed runs respect to the scheduled frequency; 

R Tot = total number of runs. 

CHAPTER III – ORGANIZATION AND EXECUTIONS OF THE RELIABILITY 

ANALYSIS ON SITE 

3.1. Operations on site : characteristics of the analyzed line 


During the Short Mission in Manchester the studies have been addressed to the BHLS on 

the route 192 (Manchester City Centre - Hazel Grove, Fig.3.1), because this route during 

the peak hours is very congested. The 192 route currently runs along the A6 corridor 

between Hazel Grove and Manchester City Centre. It commences at A523 Macclesfield 

Road (Bus Layby), travels along the A6 London Road, A6 Buxton Road, A6 Wellington 

Road, A6 Stockport Road onto Ardwick Green South and into the city centre. The 192 

route is approximately 14.9 km long inbound and 14.7 km long on the outbound journey. It 

takes an average of nearly 68 minutes to travel between Hazel Grove and Manchester City 

in the morning and just over 58 minutes in the evening peak. 

Fig.3.1. Route 192 (Manchester – Hazel Grove) 

Fig.3.2. Details of Route 192 (Manchester – Hazel Grove) 


There are a high number of notable junction delays travelling inbound during the 

morning peak. The most significant delays occur at: 

A6 London Road / Hope Street; 

London Road / Commercial Road; 

Junctions between A6 Buxton Road / Woodsmoor Lane and Wellington Road 

South /Longshut Lane; 

A6 Stockport Road / Hulme Street ; 

A6 Stockport Road / Albert Road; 

A6 Stockport Road / Slade Lane traffic signals; 

A6 London Road / Fairfield Street traffic signals. 

Travelling outbound towards Hazel Grove in the evening peak notable junction delay 

problems occur at: 

A6 Stockport Road / Plymouth Grove; 

Kirkmanshulme Lane and Cromwell Grove traffic signals; 

Wellington Road North / School Lane; 

Wellington Road South / St Petersgate; 

Wellington Road South / Higher Hillgate; 

A6 London Road / Fairfield Street and; 

A6 London Road / Store Street. 

There are a total of 30 critical junctions along this corridor that are a cause of delay to 

buses and should therefore be prioritized for review. In addition, eleven high priority 

junctions have been identified. 

There are 52 bus stops northbound and 49 southbound between Manchester and Hazel 

Grove. 

Northbound in the morning peak, bus stops SG3998 Kennerley Road and SG4000 

Nangreave Road show higher than expected delays and should be prioritized for review. 

No southbound stops have been identified as requiring review. 

The following figure sets out the results of this route performance review, illustrating 

critical junctions; bus stops and links where current performance is significantly below 

standards and; where intervention is likely to deliver the greatest benefits to buses. 


Fig.3.3. Junction delays of route 192 


Tab.3.1. Main characteristics of route 192 

Bus Route 

District/s 

Section Assessed 

Section Length 

Source Data 

Analysis Data 

Route 192 Hazel Grove - Manchester 

Stockport / Manchester 

Hazel Grove – Manchester 

14.9km Inbound, 14.7km Outbound 

…Data\Route 192 Manchester to Hazel Grove \QBC Bus Service 192 to Manchester 

Nov 2008.xls 

…\Reports\Analysis\Route 192.xls 

Date of Source Data November 2008 

GMTU Report 

…\Data\Route 192 Manchester-Hazel Grove \GMTU Rep1356 Manchester Hazel 

Grove QBC November 2008 .doc 

Tab.3.2. Performance summary of route 192 

Performance Summary 

Hazel Grove - Manchester 

AM 

Inbound 

PM 

Outbound 

Bus average total journey time including dwell time (hh:mm:ss) 01:07:44 00:58:28 

Bus average total journey time excluding dwell time (hh:mm:ss) 00:51:15 00:47:53 

Bus average journey time per km (hh:mm:ss) 00:04:33 00:03:59 

Bus average speed inc. boarding and alighting (kmh) 13.19 15.05 

Frequency of traffic signal Junctions (m) 355 366 

Frequency of pedestrian crossings (m) 514 490 

Frequency of Bus Stops (m) 287 300 

Total junction and pedestrian crossing delays (hh:mm:ss) 00:18:57 00:17:44 

% of all junction/pedestrian crossing on route 28% 30% 

Total bus stop dwell time on route (hh:mm:ss) 00:16:29 00:10:35 

% dwell time on route (hh:mm:ss) 24% 18% 

Variability (CoV) 9.29 10.32 

In summary: 

o 

the 192 service currently takes an average of nearly 68 minutes to travel between 

Hazel Grove and Manchester City in the morning and just over 58 minutes in the 

evening peak; 

o 

the frequency of traffic signal junctions is average for this type of corridor; but the 

frequency of pedestrian crossings and bus stops is low and; 

o 

the percentage of journey time attributable to dwell time is 6% higher in the morning 

peak. 

3.2. Collected Data 


During the mission and the interviews with GMPTE managers, a discussion about the 

performances of the service, about investments and about future programs has been 

developed; particularly the GMPTE has furnished a series of data on the rout 192 listed 

following: 

Performance summary (See Table 3.2, AM inbound & PM outbound) 

Junction Delays Map (Critical points) 

Bus average total journey time including dwell time 

Bus average total journey time excluding dwell time 

Bus average journey time per km 

Bus average speed incl. boarding and alighting 

Frequency of traffic signal junctions 

Frequency of pedestrian crossings 

Frequency of bus stops 

Total junction and pedestrian crossing delays 

% of all junction/pedestrian crossing on route 

Total bus stop dwell time on route 

% dwell time on route 

Variability (CoV) 

Comparison with Network Averages 

JUNCTION DELAYS Inbound & Outbound 


Intersection, Type of intersection, Average delay time (sec), Difference from 

average 

Timing 

Point 

Tab.3.3. Example of data of junction delay 

Route Intersection type Intersection with 

Junction 

aver.delay (s) 

A523 Macclesfield Road (Bus 

1 Layby) Traffic Signals A523 Macclesfield Road 

40,30 

2 A523 Macclesfield Road Traffic Signals A6 London Road 3,03 

3 A6 London Road Bus Stop SG4010 Norbury Church (Stop B) 7,23 

4 A6 London Road Traffic Signals A627 Torkington Road 12,70 

5 A6 London Road Traffic Signals Brook Street (McDonalds) 3,07 

6 A6 London Road Bus Stop SG4011 Torkington Road 14,27 

7 A6 London Road Signalised Pedestrian Grundy Street (Queens Road) 8,27 

8 A6 London Road Bus Stop SG4018 Queens Road 25,30 

9 A6 London Road Signalised Pedestrian Hatherlow Lane (Chapel St) 2,93 

10 A6 London Road Signalised Pedestrian Hope Street (Vine St) 36,77 

11 A6 London Road Traffic Signals Commercial Road 47,83 

12 A6 London Road Bus Stop SG4001 Commercial Road 45,87 

13 A6 London Road Signalised Pedestrian Brewers Green (Vernon St) 15,23 

…... ……………… ……………… ……………… …... 

BUS STOP DELAYS Inbound & Outbound 

Average times per passenger in seconds 

BUS STOP ANALYSES Inbound & Outbound 

Average delay 

Average passengers (boarders and alighted) 

Expected boarding and alighting delay 

Total expected delay 

EWT ANALYSES 

Stop description, Service, Actual time, Destination, Level of traffic, Weather, Time 

period, Actual difference, Expected waiting time for stops (EWT). 

Besides a review has been effected on board of the journey time and dwell time of a 

generic run in the considered peak hours (9 March 2009, see Tables 3.4). 

During the review dwell times on the stops of the single analyzed runs were collected. A 

comparison was operated with the average values elaborated by the GMPTE. 

Tab. 3.4a. Data collected on-board (Run 9,30 : Manchester-Hazel Grove) 


Stop 

Arrival time 

(hh,mm) 

Departure time 

(hh. mm) 

Dwell time 

(sec) 

Piccadilly 9,29 9,30 60 

Apollo teathre 9,34 9,34 30 

Longhsit Shopping Centre 9,38 9,38 20 

Slade lane 9,41 9,41 40 

Matthews Lane 9,43 9,43 10 

Carrill Grove 9,44 9,44 10 

Broom lane 9,46 9,46 7 

Heaton Road 9,52 9,52 40 

Belmont way 9,54 9,55 60 

Mersey square 9,56 9,59 180 

Grand Central 10,00 10,00 20 

Stockport college 10,01 10,02 40 

Brentnall street 10,03 10,03 7 

Longshut lane 10,03 10,04 20 

Nangreave Road 10,05 10,06 15 

Kennerley Road 10,06 10,07 15 

Corbar road 10,07 10,07 10 

Cherry Tree Lane 10,09 10,09 20 

Dialstone Lane 10,09 10,09 7 

Stepping Hill Hospital 10,11 

Tab. 3.4b. Data collected on-board (Run 10,20 : Hazel Grove-Manchester) 

Arrival time Departure time Dwell time 

Stop 

(hh,mm) (hh. mm) (sec) 

Dialstone Lane 10,20 

Corbar Road 10,22 10,22 15 

Nangreave Road 10,24 10,24 10 

Wellington Grove 10,26 10,26 10 

Stockport College 10,27 10,28 20 

Grand Central 10,30 10,31 60 

Mersey Square 10,32 10,35 150 

Belmont Bridge 10,37 10,37 15 

Heaton Road 10,38 10,38 20 

Milwain Drive 10,41 10,41 10 

Lloyd Road 10,43 10,44 40 

Broom Lane 10,45 10,45 15 

Albert Road 10,48 10,48 15 

Woodford Avenue 10,50 10,50 10 

East Road 10,52 10,53 30 

Longsight H. Centre 10,55 10,57 80 

Plymouth Grove 10,59 11,00 30 

Winterford A. 11,01 11,01 15 

Devonshire Street 11,02 11,02 10 


Covanagh Close 11,02 11,03 10 

Apollo theatre 11,02 11,03 7 

Travis Street 11,05 11,05 10 

Minshull Street 11,07 11,07 7 

Piccadilly 11,00 

Tab. 3.4c. Data collected on-board (Run 17,48 : Manchester-Hazel Grove) 


Stop 


Piccadilly (Paton street) 17,48 17,48 20 

Fairfield Street 17,50 17,50 20 


Ardwick Green 17,52 17,53 10 

Apollo Theatre 17,54 17,54 10 

Ardwick Post Office 17,54 17,55 10 


Plymouth Grove W. 17,56 17,57 7 

Plymouth Grove 17,57 17,57 10 

Longsight S.Centre 17,59 17,59 15 

Slade Lane 18,01 18,02 20 

Matthews Lane 18,03 18,03 7 

Mayfield Road 18,04 18,05 10 


Albert Road 18,07 18,07 7 

Delamere Road 18,08 18,08 7 

McVities 18,11 18,11 7 

Manchester Road 18,12 18,12 7 

Heaton Moor Road 18,14 18,14 10 

Terminal 

Tab. 3.4d. Data collected on-board (Run 18,27 : Hazel Grove-Manchester) 


Stop 


Mersey square 18,27 

Belmont way 18,29 18,29 10 

Belmont bridge 18,29 18,29 10 

Brackley road 18,32 18,32 7 

Heaton Moor road 18,33 18,33 15 

Manchester Road 18,34 18,34 10 

Milwain drive 18,35 18,35 25 

Lloyd road 18,37 18,37 25 

Broom lane 18,38 18,38 15 

Crayfield road 18,39 18,39 25 


Albert road 18,40 18,41 15 


Woodford Avenue 18,44 18,44 10 

Matthews lane 18,45 18,45 7 

East road 18,46 18,46 15 

Slade lane 18,47 18,47 20 

Longhsit health centre 18,49 18,49 30 

Plymouth grove 18,51 18,51 7 

Plymouth grove west 18,52 18,52 15 

Winterford avenue 18,53 18,53 10 


Covanagh Close 18,54 18,54 15 

Apollo theatre 18,55 18,56 40 

Grosvenor Street 18,57 18,57 10 


Minshull Street 19,00 19,00 7 

Piccadilly 19,03 

Fig.3.4 – Comparison between average delay at bus stop and data collected 

(Run 10,20 : Hazel Grove-Manchester) 


Fig.3.5 – Comparison between average delay at bus stop and data collected 

(Run 17,48 : Manchester – Hazel grove) 

From the diagram in Fig. 3.4 and Fig. 3.5 it is possible to observe as in the run analyzed in 

direction Manchester (AM Peak) that the values collected of the dwell times are very large 

versus the average in some stops, especially in the mains. While in the run of the afternoon 

the values are still below the average. 

An analysis is developed also considering the database furnished by the GMPTE (gives 

related to the period 29/09/2008-10/10/2008 and to the AM Peak period time in direction 

Manchester starts at 7,30 until the 9,30 and PM Peak in direction Hazel Grove that it has 

gone since 16,30 to 18,30 o'clock) on the delays that the line 192 accumulate during the 

travel; these are due to the numerous intersections along the line. In the table 3.5 are listed 

the intersections and the stops along the line and the relative average delays. 


Table. 3.5. Average junction delay on route 192 – Towards Manchester AM Peak 

Timing 

Point 


Junction 

Av Delay 

(s) 

A523 Macclesfield Road (Bus 

1 Layby) Traffic Signals A523 Macclesfield Road 

40,30 

2 A523 Macclesfield Road Traffic Signals A6 London Road 3,03 

3 A6 London Road Bus Stop SG4010 Norbury Church (Stop B) 7,23 

4 A6 London Road Traffic Signals A627 Torkington Road 12,70 

5 A6 London Road Traffic Signals Brook Street (McDonalds) 3,07 

6 A6 London Road Bus Stop SG4011 Torkington Road 14,27 

7 A6 London Road Signalised Pedestrian Grundy Street (Queens Road) 8,27 


9 A6 London Road Signalised Pedestrian Hatherlow Lane (Chapel St) 2,93 

10 A6 London Road Signalised Pedestrian Hope Street (Vine St) 36,77 



13 A6 London Road Signalised Pedestrian Brewers Green (Vernon St) 15,23 

14 A6 London Road Bus Stop SG0908 Brewers Green 9,80 

15 A6 London Road Traffic Signals Mill Street 24,17 

16 A6 London Road Traffic Signals New Moor Lane (Sainsbury's) 0,00 

17 A6 Buxton Road Bus Stop SG4004 Sainsbury's 16,57 

18 A6 Buxton Road Traffic Signals Poplar Grove (Dialstone Ln) 24,27 

19 A6 Buxton Road Signalised Pedestrian Dialstone Lane (Bonis Crs) 1,80 

20 A6 Buxton Road Bus Stop SG4002 Dialstone Lane (Stop A) (OTP) 23,57 

21 A6 Buxton Road Signalised Pedestrian Norwood Road (Cherry Tree Lane) 14,70 

22 A6 Buxton Road Bus Stop SG4003 Cherry Tree Lane 19,97 

23 A6 Buxton Road Signalised Pedestrian Woodsmoor Lane (Lake St) 31,60 

24 A6 Buxton Road Bus Stop SG4005 Woodsmoor Lane 16,73 

25 A6 Buxton Road Signalised Pedestrian Mile End Lane 29,73 

26 A6 Buxton Road Bus Stop SG3996 Corbar Road 5,70 

27 A6 Buxton Road Traffic Signals Kennerley Road 61,37 

28 A6 Buxton Road Bus Stop SG3998 Kennerley Road 30,60 

29 A6 Buxton Road Signalised Pedestrian Heaviley Grove (Regent Rd) 10,87 

30 A6 Buxton Road Bus Stop SG3999 Heaviley Post Office (OTP) 8,13 

31 A6 Buxton Road Traffic Signals B6171 Nangreave Road 35,60 

32 A6 Buxton Road Bus Stop SG4000 Nangreave Road 66,23 

33 A6 Buxton Road Bus Stop SG0864 Bramhall Lane 4,03 

34 A6 Buxton Road Traffic Signals A5102 Bramhall Lane 45,60 

35 A6 Wellington Road South Bus Stop SG3985 Wellington Grove (A) 15,90 

36 A6 Wellington Road South Signalised Pedestrian Wellington Grove (Daisy St) 5,83 

37 A6 Wellington Road South Traffic Signals B5465 Longshut Lane 43,67 

38 A6 Wellington Road South Bus Stop SG3986 Longshut Lane 20,67 

39 A6 Wellington Road South Signalised Pedestrian Charlesworth Street (Brentnall St) 5,43 

40 A6 Wellington Road South Signalised Pedestrian Stockport College 0,00 

41 A6 Wellington Road South Bus Stop SG3987 Stockport College (Stop AC) 22,73 

42 A6 Wellington Road South Signalised Pedestrian Ratcliffe Street 2,97 

Stockport Town Hall (Greek Street) (1st 

43 A6 Wellington Road South Traffic Signals Set) 

12,07 

Traffic Signals With 

44 A6 Wellington Road South Pedestrian Facilities Stockport Town Hall (2nd Set) 

0,13 

45 A6 Wellington Road South Traffic Signals Railway Road (John St) 2,03 

46 A6 Wellington Road South Bus Stop SG1627 Grand Central (Stop WW) 38,63 

47 A6 Wellington Road South Traffic Signals Grand Central Complex (Station Road) 26,70 

48 A6 Wellington Road South Traffic Signals Exchange Street (St Petersgate) 3,17 

49 A6 Wellington Road South Traffic Signals Heaton Lane 3,23 

50 A6 Wellington Road North Bus Stop SG0926 Mersey Square (Stop AA) (OTP) 84,30 

51 A6 Wellington Road North Signalised Pedestrian Wellesley House 0,50 

52 A6 Wellington Road North Bus Stop SG1664 Aspley House 1,77 

53 A6 Wellington Road North Traffic Signals George's Road 9,27 

54 A6 Wellington Road North Bus Stop SG3991 Belmont Way 4,27 

55 A6 Wellington Road North Traffic Signals Belmont Way 9,03 

56 A6 Wellington Road North Bus Stop SG3992 Belmont Bridge 8,17 

57 A6 Wellington Road North Traffic Signals Heaton Road 12,37 

58 A6 Wellington Road North Bus Stop SG3993 Heaton Road 11,53 

59 A6 Wellington Road North Signalised Pedestrian Warwick Road (Glenfield Rd) 0,30 

60 A6 Wellington Road North Bus Stop SG1052 Warwick Road (OTP) 8,00 

61 A6 Wellington Road North Signalised Pedestrian Langford Road (Brackley Rd) 0,63 


62 A6 Wellington Road North Bus Stop SG1267 Brackley Road 8,57 

63 A6 Wellington Road North Traffic Signals B5169 Heaton Moor Road (School Lane) 18,70 

64 A6 Wellington Road North Bus Stop SG0596 Heaton Moor Road (Stop A) 17,50 

65 A6 Wellington Road North Traffic Signals A626 Manchester Road 13,10 

66 A6 Wellington Road North Bus Stop SG0593 Manchester Road 14,60 

67 A6 Wellington Road North Signalised Pedestrian Milwain Drive 1,07 

68 A6 Wellington Road North Bus Stop SG0594 Milwain Drive 4,70 

69 A6 Wellington Rd North Signalised Pedestrian Weybrook Road 0,63 

70 A6 Wellington Rd North Bus Stop SG0595 McVities 16,80 

71 A6 Wellington Road North Traffic Signals Crossley Road 26,80 

72 A6 Wellington Road North Traffic Signals Lloyd Road 0,00 

73 A6 Stockport Road Bus Stop EB0366 Lloyd Road (OTP) 14,70 

74 A6 Stockport Road Signalised Pedestrian Cringle Road 13,57 

75 A6 Stockport Road Traffic Signals B6178 Broom Lane 14,10 

76 A6 Stockport Road Signalised Pedestrian Hume St (Darnforth Gr) 25,80 

77 A6 Stockport Road Bus Stop EB0365 Broom Lane 19,10 

78 A6 Stockport Road Signalised Pedestrian Crayfield Road 48,27 

79 A6 Stockport Road Bus Stop EB0362 Crayfield Road 16,27 

80 A6 Stockport Road Traffic Signals Alma Road 86,40 

81 A6 Stockport Road Bus Stop EB0361 Albert Road 13,27 

82 A6 Stockport Road Traffic Signals B5093 Albert Road 57,87 

83 A6 Stockport Road Signalised Pedestrian Cromwell Grove 3,10 

84 A6 Stockport Road Bus Stop EB0359 Carrill Grove 66,67 

85 A6 Stockport Road Signalised Pedestrian Woodford Avenue (Mayford Ave) 5,40 

86 A6 Stockport Road Bus Stop EB0357 Woodford Avenue 13,57 

87 A6 Stockport Road Traffic Signals Matthews Lane 4,57 

88 A6 Stockport Road Bus Stop EB0355 Matthews Lane 18,57 

89 A6 Stockport Road Traffic Signals Crowcroft Road 1,60 

90 A6 Stockport Road Bus Stop EB0449 East Road 18,83 

91 A6 Stockport Road Bus Stop EB0446 Slade Lane (OTP) 33,20 

92 A6 Stockport Road Traffic Signals A5079 Slade Lane 66,60 

93 A6 Stockport Road Traffic Signals A6010 Dickenson Road 12,37 

94 A6 Stockport Road Bus Stop EB0614 Longsight Health Centre (Stop A) 57,30 

95 A6 Stockport Road Signalised Pedestrian Longsight District Centre 7,10 

96 A6 Stockport Road Traffic Signals A6010 Kirkmanshulme Lane 24,07 

97 A6 Stockport Road Traffic Signals A5184 Plymouth Grove 5,57 

98 A6 Stockport Road Bus Stop EB0617 Plymouth Grove 22,33 

99 A6 Stockport Road Bus Stop EB0618 Longsight Police Station 9,93 

100 A6 Stockport Road Signalised Pedestrian Plymouth Grove West 2,63 

101 A6 Stockport Road Bus Stop EB0619 Plymouth Grove West 8,40 

102 A6 Stockport Road Bus Stop EB0620 Winterford Avenue 8,87 

103 A6 Stockport Road Signalised Pedestrian Winterford Avenue 2,47 

104 A6 Stockport Road Signalised Pedestrian Grove Village 0,80 

105 A6 Stockport Road Bus Stop EB0621 Devonshire Street 14,97 

106 A6 Stockport Road Traffic Signals A665 Devonshire Street 14,60 

107 A6 Stockport Road Bus Stop EB0624 Cavanagh Close 20,57 

108 A6 Stockport Road Bus Stop EB0623 Apollo Theatre (OTP) 13,17 

109 A6 Stockport Road Signalised Pedestrian Apollo Theatre 1,93 

110 A6 Stockport Road Roundabout Entry A6 Ardwick Green South 15,00 

111 A6 Ardwick Green South Signalised Pedestrian Apollo Roundabout 0,30 

112 A6 Ardwick Green South Bus Stop EB3420 Ardwick Green 6,73 

113 A6 Downing Street Bus Stop EB3417 Grosvenor Street 6,03 

114 A6 Downing Street Traffic Signals Grosvenor Street 7,60 

115 A6 Downing Street Traffic Signals A57(m) Mancunian Way 8,87 

116 A6 London Road Bus Stop EB0116 Travis Street 12,83 

117 A6 London Road Traffic Signals B6469 Farfield Street 26,37 

118 A6 London Road Traffic Signals A6 Whitworth Street 3,30 

119 A6 Whitworth Street Bus Stop EB0255 Fairfield Street 12,93 

120 A6 Whitworth Street Traffic Signals A6 Aytoun Street 2,43 

121 A6 Aytoun Street Bus Stop A523 Macclesfield Road 8,93 

122 A6 Aytoun Street Traffic Signals A6 London Road 0,37 

123 A6 Aytoun Street Traffic Signals SG4010 Norbury Church (Stop B) 41,20 

124 A5103 Portland Street Bus Stop A627 Torkington Road 0,00 

From these data, it results that in direction Manchester the service during the journey 

accumulates in average 1151,7 seconds (19,2 minutes) on the intersections and 989,3 

seconds (16,48 minutes) on the stops. 


In table 3.6 the average delays accumulated by the service in direction Hazel Grove are 

presented. 

Timing 

Point 

Table. 3.6. Average junction delay on route 192 – Towards Hazel Grove PM Peak 


Av 

Junction 

Delay (s) 

1 A6 Piccadilly Signalised Pedestrian Paton Street 11,80 

2 A6 Piccadilly Traffic Signals Ducie Street 23,20 

3 A6 London Road Traffic Signals Store Street (Metrolink Crossing) 29,70 

4 A6 London Road Bus Stop EB0120 Fairfield Street (Stop A) 25,17 

5 A6 London Road Traffic Signals B6469 Fairfield Street 32,80 

6 A6 London Road Bus Stop EB0118 Travis Street 7,80 

7 A6 London Road Traffic Signals A57(m) Mancunian Way 1,63 

8 A6 Downing Street Traffic Signals Grosvenor Street 0,00 

9 A6 Ardwick Green South Bus Stop EB3419 Ardwick Green 10,23 

10 A6 Ardwick Green South Signalised Pedestrian Apollo Roundabout 9,27 

11 A6 Ardwick Green South Roundabout Entry A6 Stockport Road 4,93 

12 A6 Stockport Road Signalised Pedestrian Apollo Theatre 1,20 

13 A6 Stockport Road Bus Stop EB0622 Apollo Theatre (OTP) 13,20 

14 A6 Stockport Road Bus Stop EB0625 Ardwick Post Office 19,00 

15 A6 Stockport Road Traffic Signals A665 Devonshire Street 35,07 

16 A6 Stockport Road Signalised Pedestrian Grove Village 2,80 

17 A6 Stockport Road Bus Stop EB0626 Devonshire Street 8,50 

18 A6 Stockport Road Signalised Pedestrian Winterford Avenue 0,27 

19 A6 Stockport Road Bus Stop EB0627 Winterford Avenue 9,50 

20 A6 Stockport Road Signalised Pedestrian Plymouth Grove West 1,50 

21 A6 Stockport Road Bus Stop EB0628 Plymouth Grove West 8,70 

22 A6 Stockport Road Bus Stop EB0629 Plymouth Grove 14,67 

23 A6 Stockport Road Traffic Signals A5184 Plymouth Grove 118,00 

24 A6 Stockport Road Traffic Signals A6010 Kirkmanshulme Lane 55,33 

25 A6 Stockport Road Signalised Pedestrian Longsight District Centre 7,77 

EB0631 Longsight Shopping Centre 

26 A6 Stockport Road Bus Stop 

(Stop B) 

35,47 

27 A6 Stockport Road Traffic Signals A6010 Dickenson Road 27,27 

28 A6 Stockport Road Traffic Signals A5079 Slade Lane 12,57 

29 A6 Stockport Road Bus Stop EB0447 Slade Lane (OTP) 24,80 

30 A6 Stockport Road Bus Stop EB0450 East Road 9,80 

31 A6 Stockport Road Traffic Signals Crowcroft Road 9,97 

32 A6 Stockport Road Bus Stop EB0356 Matthews Lane 19,00 

33 A6 Stockport Road Traffic Signals Matthews Lane 11,33 

34 A6 Stockport Road Signalised Pedestrian Mayford Avenue (Woodford Ave) 27,77 

35 A6 Stockport Road Bus Stop EB0358 Mayfield Road 11,13 

36 A6 Stockport Road Bus Stop EB0299 Carrill Grove 20,60 

37 A6 Stockport Road Signalised Pedestrian Cromwell Grove 49,57 

38 A6 Stockport Road Traffic Signals B5093 Albert Road (1st Set) 17,90 

Traffic Signals With 

39 A6 Stockport Road 

Pedestrian Facilities B5093 Albert Road (2nd Set) 

1,63 

40 A6 Stockport Road Bus Stop EB0360 Albert Road 15,13 

41 A6 Stockport Road Traffic Signals Alma Road 27,93 

42 A6 Stockport Road Bus Stop EB0301 Delamere Road 16,77 

43 A6 Stockport Road Signalised Pedestrian Crayfield Road 4,67 

44 A6 Stockport Road Bus Stop EB0363 Crayfield Road 7,50 

45 A6 Stockport Road Signalised Pedestrian Darnforth Grove (Hume St) 4,73 

46 A6 Stockport Road Bus Stop EB0364 Broom Lane 14,20 

47 A6 Stockport Road Traffic Signals B6178 Broom Lane 12,73 

48 A6 Stockport Road Signalised Pedestrian Cringle Road 1,77 

49 A6 Stockport Road Traffic Signals Lloyd Road 23,60 

50 A6 Wellington Road North Traffic Signals Crossley Road 1,03 

51 A6 Wellington Road North Bus Stop SG1282 McVities 9,90 

52 A6 Wellington Road North Signalised Pedestrian Weybrook Road 1,00 

53 A6 Wellington Road North Bus Stop SG0023 Lloyd Road (OTP) 1,63 

54 A6 Wellington Road North Signalised Pedestrian Millwain Drive 3,00 

55 A6 Wellington Road North Bus Stop SG4008 Milwain Drive 4,87 

56 A6 Wellington Road North Traffic Signals A626 Manchester Road 14,03 

57 A6 Wellington Road North Bus Stop SG4189 Manchester Road 9,57 

58 A6 Wellington Road North Traffic Signals B5169 School Lane (Heaton Moor Lane) 37,57 


(1st Set) 

Traffic Signals With B5169 School Lane (Heaton Moor Lane) 

59 A6 Wellington Road North Pedestrian Facilities (2nd Set) 

0,00 

60 A6 Wellington Road North Bus Stop SG4192 Heaton Moor Road (Stop D) 11,97 

61 A6 Wellington Rd N Signalised Pedestrian Brackley Road (Langford Rd) 0,37 

62 A6 Wellington Rd North Bus Stop SG4190 Brackley Road 9,47 

63 A6 Wellington Rd North Signalised Pedestrian Glenfield Road (Warwick Rd) 0,27 

64 A6 Wellington Rd North Bus Stop SG4193 Warwick Road 3,37 

65 A6 Wellington Rd North Traffic Signals Heaton Road 8,37 

66 A6 Wellington Rd North Bus Stop SG4191 Heaton Road 6,43 

67 A6 Wellington Rd North Bus Stop SG4194 Belmont Bridge 4,53 

68 A6 Wellington Rd North Traffic Signals Belmont Way 16,63 

69 A6 Wellington Rd North Bus Stop SG4195 Belmont Way 7,10 

70 A6 Wellington Road North Traffic Signals George's Road 7,77 

71 A6 Wellington Road North Signalised Pedestrian Wellesley House 1,90 

72 A6 Wellington Road North Bus Stop SG4197 Wellesley House 2,50 

73 A6 Wellington Road North Traffic Signals Heaton Lane 5,97 

74 A6 Wellington Road South Bus Stop SG1552 Mersey Square (Stop BB) (OTP) 74,53 

75 A6 Wellington Road South Traffic Signals St Petersgate (Exchange St) 40,47 

76 A6 Wellington Road South Traffic Signals Grand Central Complex (Wellington St.) 1,23 

77 A6 Wellington Road South Bus Stop SG1486 Grand Central (Stop RR) 37,13 

78 A6 Wellington Road South Traffic Signals John Street (Railway Rd) 6,43 

79 A6 Wellington Road South Traffic Signals Stockport Town Hall (Edward Street) 7,47 

80 A6 Wellington Road South Bus Stop SG4199 Stockport College (Stop YY) 22,27 

81 A6 Wellington Road South Signalised Pedestrian Ratcliffe Street 2,53 

82 A6 Wellington Road South Signalised Pedestrian Stockport College 0,37 

83 A6 Wellington Road South Signalised Pedestrian Brentnall Street (Charlesworth St) 2,20 

84 A6 Wellington Road South Bus Stop SG1085 Brentnall Street 6,37 

85 A6 Wellington Road South Traffic Signals B5465 Longshut Lane 23,30 

86 A6 Wellington Road South Bus Stop SG4052 Longshut Lane 10,23 

87 A6 Wellington Road South Signalised Pedestrian Daisy Street (Wellington Gr) 3,23 

88 A6 Wellington Road South Traffic Signals Higher Hillgate 50,10 

89 A6 Buxton Road Bus Stop SG4053 Bramhall Lane (Stop B) 6,70 

90 A6 Buxton Road Traffic Signals B6171 Nangreave Road 16,23 

91 A6 Buxton Road Bus Stop SG4054 Nangreave Road (OTP) 15,43 

92 A6 Buxton Road Signalised Pedestrian Regent Road (Heaviley Grove) 3,80 

93 A6 Buxton Road Bus Stop SG4055 Kennerley Road 12,07 

94 A6 Buxton Road Traffic Signals Kennerley Road 15,93 

95 A6 Buxton Road Bus Stop SG4056 Corbar Road 6,50 

96 A6 Buxton Road Signalised Pedestrian Mile End Lane 4,30 

97 A6 Buxton Road Signalised Pedestrian Lake Street (Woodsmoor Ln) 11,97 

98 A6 Buxton Road Bus Stop SG4057 Woodsmoor Lane 5,57 

99 A6 Buxton Road Signalised Pedestrian Cherry Tree Lane (Norwood Rd) 18,27 

100 A6 Buxton Road Bus Stop SG4059 Cherry Tree Lane 9,93 

101 A6 Buxton Road Bus Stop SG4060 Dialstone Lane (Stop B) (OTP) 15,10 

102 A6 Buxton Road Signalised Pedestrian Bonis Crescent (Dialstone Ln) 31,23 

103 A6 Buxton Road Traffic Signals Dialstone Lane (Poplar Grove) 20,83 

104 A6 London Road Traffic Signals Sainsbury's (New Moor Lane) 30,23 

105 A6 London Road Bus Stop SG4061 Sainsbury's 17,87 

106 A6 London Road Traffic Signals Mill Street 5,17 

107 A6 London Road Signalised Pedestrian Vernon Street (Brewers Grn) 5,53 

108 A6 London Road Bus Stop SG4062 Brewers Green 7,83 



111 A6 London Road Signalised Pedestrian Vine Street (Hope St) 1,30 

112 A6 London Road Signalised Pedestrian Chapel Street (Hatherlow Lane) 12,33 


114 A6 London Rd Signalised Pedestrian Queens Road (Grundey St) 7,63 

115 A6 London Rd Bus Stop SG0944 Norbury Post Office 3,83 

116 A6 London Rd Traffic Signals Brook Street (McDonalds) 16,37 

117 A6 London Rd Traffic Signals A627 Torkington Road 11,13 

118 A6 London Rd Bus Stop SG4009 Torkington Road (Stop A) 6,53 

119 A6 London Rd Traffic Signals A523 Macclesfield Road 40,97 

120 A523 Macc. Road (Bus Layby) Bus Stop SG4302 Rising Sun (Stop D) (OTP) 0,00 

In direction Hazel Grove the service during the journey accumulates in average 1069,7 

second (17,8 minutes) on the intersections and 634,8 seconds (10,6 minutes) on the stops. 


From these results it is possible to notice as for around the 60% of the time of general 

journey a middle vehicle is stationary along the line. It’s easy to understand as an 

improvement of the infrastructural characteristics (increasing of length of reserved lane) 

and of the intersections (priority to the bus) can make even more efficient and more 

reliable. the service on the 192 line. 

3.3. Reliability Indicators Valuation 

In this chapter are calculated some reliability indicators in relationship to the data collected 

during the Short Mission. The obtained indicators are founded on elaborations of data 

observed on one average day furnished by the GMPTE, therefore are obtained average 

values of service and not punctual on the single runs. In this specific case the indicators of 

reliability are calculated with an approach to frequency. 

The main indicators of reliability that it is possible to obtain considering the data collected 

are the Frequency Regularity and the % runs that respect the scheduled frequency. 

The indicator Frequency Regularity is calculated considering a parameter of base as the 

Average Frequency defined in the temporal slot in which has been developed the detection 

data by the GMPTE (rush hours): 

Average Frequency : AF = Runs/Time; 

The two indicators of reliability are so defined: 

Frequency Regularity (FR): standard deviation of the frequency from the average 

frequency; 

FR=[∑ i=1,..,n (x i –AF) 2 /n] 1/2 

where: 

n = number of passages; 

x i = punctual frequency; 

AF = Average frequency. 


RELIABILITY, % of runs that respect the scheduled frequency: 

RELIABILITY = 1 - R F /R Tot ; 

where: 

R F = Runs that failed the scheduled frequency; 

R Tot = Total runs. 

Some data related to the main stop of the line (Mersey Square) have been obtained, that is 

having available the instants in which the service passes from the stop during the day (see 

Tab.3.7), is been possible to develop some considerations and to obtain some average 

values of reliability of the service during the line 192 in the considered average day for this 

specific stop (May 21st 2008). The application appears interesting however in terms of 

methodological approach and could be wide improved on other stops of line. 

Tab.3.7. Data of main stop of route 192 (example) 

Date Stop Description Service 

Actual 

Time 

Destination 

Time 

Period 

Time 

difference 

1-May-08 Mersey Square 192 07:30 PICCADILLY AM Peak 

21-May-08 Mersey Square 192 07:33 PICCADILLY AM Peak 3 


















…….. ………………. …….. ……….. …………….. ………. ………… 


The parameter Time Differences is the headway between two successive buses at the stop. 

Considering the data registered during the analyzed day is possible to calculate the average 

value of the frequency really developed for each direction. These values refer to the 

different peak hours, that are AM PEAK (7,30 -9,30), INTER PEAK (13,00-15,00), PM 

PEAK (16,00-18,30): 

Towards Manchester: 

AM PEAK - AF = Average of time differences = 1 bus every 2,34 minutes 

INTER PEAK - AF = Average of time differences = 1 bus every 2,55 minutes 

PM PEAK - AF = Average of time differences = 1 bus every 2,41 minutes 

Towards Hazel Grove: 

AM PEAK - AF = Average of time differences = 1 bus every 3,54 minutes 

INTER PEAK - AF = Average of time differences = 1 bus every 3,25 minutes 

PM PEAK - AF = Average of time differences = 1 bus every 3,50 minutes 

The regularity (irregularity) some frequency can be calculated in terms of standard 

deviation from the value of average frequency: 


AM PEAK - FR = Standard Deviation = 1,17 minutes 

INTER PEAK - FR = Standard Deviation = 1,33 minutes 

PM PEAK - FR = Standard Deviation = 1,97 minutes 


AM PEAK - FR = Standard Deviation = 2,51 minutes 

INTER PEAK -FR = Standard Deviation = 2,74 minutes 

PM PEAK - FR = Standard Deviation = 3,37 minutes 


Fig. 3.6. Standard deviation (Towards Manchester) 

Fig. 3.7. Standard deviation (Towards Hazel Grove) 

The percentage of the runs that don't respect the scheduled frequency (condition of low 

service), is defined by the relationship among the runs that pass on the considered stop 

after a greater temporal period of the value of the scheduled frequency and the total 

number of runs in the considered slot time. More lower it is this percentage, more higher it 

results the reliability of the service. 

Dealing with this analysis it is possible to consider the scheduled frequency (case a, which 

in this case is 1 bus every 10 minutes) or, alternatively, the average frequency obtained by 

field observations (case b). Hence on 192 line of Manchester the observed supply, in terms 


of frequency, is largely more consistent than the one initially set or established in theory. 

In this second case it is possible to detect major differences in terms of service efficiency, 

also due to the fact that the term of comparison is sensibly lower (around 3 minutes instead 

of 10). 

However the index RELIABILITY (% runs that respect the scheduled frequency) assumes 

the following values: 

Case a(freq. 10 min) 


AM PEAK - RELIABILITY = 1 - Failed Runs/Total Runs = 100% 

INTER PEAK - RELIABILITY =1 - Failed Runs/Total Runs = 100% 

PM PEAK - RELIABILITY = 1 - Failed Runs/Total Runs = 100% 



INTER PEAK - RELIABILITY = 1 - Failed Runs/Total Runs = 97,3% 

PM PEAK - RELIABILITY = 1 - Failed Runs/Total Runs = 95,2% 

Case b (freq. 3min) 



INTER PEAK - RELIABILITY = 1 - Failed Runs/Total Runs = 47% 




INTER PEAK - RELIABILITY = 1 - Failed Runs/Total Runs = 60% 


It is possible to see how the indicators assume values remarkably higher in the second 

instance. 

A further analysis can be developed considering the average wait time on the stops that can 

be calculated expressed as: 

Tw = β / AF; 

in which β is a coefficient that is equal to 1 if the line is to perfectly regulate, or equal to 

0,5 if the line is completely casual. In this case the service is completely random. 



AM PEAK – Average wait time = Tw = β / AF = 0,5 / AF = 1,17 minutes 

INTER PEAK - Average wait time = Tw = β / AF = 0,5 / AF = 1,27 minutes 

PM PEAK - Average wait time = Tw = β / AF = 0,5 / AF = 1,20 minutes 


AM PEAK - Average wait time = Tw = β / AF = 0,5 / AF = 1,77 minutes 

INTER PEAK - Average wait time = Tw = β / AF = 0,5 / AF = 1,62 minutes 

PM PEAK - Average wait time = Tw = β / AF = 0,5 / AF = 1,75 minutes 

It is possible to deduce that with average waiting times around this measure (around 1,5 

minutes) the users perceive however the service as a quality service. 

3.4. Overview and conclusions 

The obtained results suggest an elevated frequency on the e 192 line (1 bus every 2,5 

minutes in direction Manchester, 1 bus every 3,5 minutes in direction Hazel Grove). The 

average waiting time on the stop considering the service as “random” is variable from 1,2 

minutes to 1,7 minutes; these values are limited and therefore give to the users a perception 

of reliable service. 

Considering the regularity (irregularity) indicator it is possible to notice as the regularity of 

the service changes according to the direction; in fact the service on the direction 

Manchester is more regular (standard deviation is lower). Finally, fixing the attention on 

the last indicator “RELIABILITY” that give as output the percentage of the runs that 

respect the scheduled frequency it is evident that in direction Manchester the frequency is 

respected on the 100% of the runs (in the considered peak hours) while in direction Hazel 

Grove the percentage is not 100% but is however high. 

From the data concerning the average delays on the different intersections along the route 

it results clear as an improvement of the facilities, first among the whole increasing of the 

kms of reserved lane, will increase the service in terms of efficiency and reliability. 


Special thanks go to François Rambaud, Domenico Gattuso, Claire Blanchard, Pascal Lasagne which made 

possible my "short mission". 

Thanks also to all who have helped me in gathering data for research: Nick Vaughan (Department Manager 

– Project Development GMPTE), Melanie Watson (Department Manager – Transport Services GMPTE), 

Celia Hunt (Assistant to Melanie Watson), Steve Gilholme (Service Account Manager – Bus, Transport 

Services GMPTE), Brian Young (Senior Project Manager – Quality Bus Corridor (QBC),Transport Services 

GMPTE),Paul Chandler (Senior Project Manager – Quality Bus Corridor (QBC), Transport Services 

GMPTE), Neil Guy (Team Leader – Bus Operator Analyst, Transport Services GMPTE), Jack Ripley 

(Service Account Manager – Bus, Transport Services GMPTE) and all those I met on my visit in Manchester. 

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Siti Web 

[1.]www.bhls.eu 

[2.] www.dft.gov.uk/stellent/groups/dft_mobility 

[3.] www.fco.gov.uk 

[4.]www.tfl.gov.uk/tube/using/useful-info/safet 

[5.]www.academie-qualitè.com 

[6.] www.federtrasporti.it

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