Masters Dissertation Posters 2015

1. Introduction and Background
• Driver performance can be influenced by surrounding vehicle. “It is well known that
the surrounding roads and traffic environment influences driver’s behaviour; for
example, the road environment (surrounding landscape, road characteristics), traffic
composition (cars and heavy vehicles) affects driver’s desired speed, lane changing
behaviour, lateral positioning, and overtaking behaviour” (Antonson, H., 2009;
Olstam, J. 2009; Moridpour, S et al., 2010).
• There is also substantial research about other influencing factors such as distraction,
fatigue, and personality on driving performance, but could something as simple as the
lane position of another vehicle influence your performance.
1.1. Aims & Objectives
AIM: To investigate the interaction between surrounding driver behaviours and driving
controls.
OBJECTIVES: are to determine:
1. The extent to which a lead driver’s behaviour influences driving performance and
vehicle control of a following driver on (Rural roads)
2. Which lead vehicle type has greater influence on drivers’ performance and vehicle
control? (Car vs HGV)
3. Who is likely to be more affected by lead vehicle aggressive driving behaviour? (Male
driver vs female driver)
4. Research Methodology
Simulator Validity
• Ideally this study will require the simulator validity to be closely related to real
world driving in order to consider the simulator as an adequate tool.
• Selection of simulator is based on trade-off between (validity and controllability)
Participant Sample
• Findings show that young drivers aged 17-25 are particularly prone to have
relatively more accidents than other driver (Clarke, D et al., 2006). The
characteristics of young driver accidents includes: accidents on single carriageway
rural roads; loss of control; excess speeding; accident during darkness (Clarke, D et
al., 2006).
• Male drivers have more accidents compared to their female counterpart (Clarke, D
et al., 2006; Jiménez-Mejías, E et al., 2014).
• 20 young drivers (10 males and 10 females) will be recruited for this study. This
sample size was informed by a similar driving simulator study on the comparison of
driving styles (Pampel, S. M., et al., 2015).
3. Literature Review
The idea behind this study is connected to earlier road safety paradigm and research
carried out between 1950 and 1970 which tried to establish the cause of accidents
as being “Road user, or the vehicle, or the road” (Hagenzieker, M.P et al., 2014).
References
 Antonson, H., Mårdh, S., Wiklund, M., & Blomqvist, G. (2009). Effect of surrounding landscape on driving behaviour: A driving simulator study. Journal of Environmental
Psychology, 29(4), 493-502.
 Bella, F. (2005). Validation of a driving simulator for work zone design. Transportation Research Record: Journal of the Transportation Research Board, 1937(1), 136-144.
 Clarke, D. D., Ward, P., Bartle, C., & Truman, W. (2006). Young driver accidents in the UK: The influence of age, experience, and time of day. Accident Analysis & Prevention,
38(5), 871-878.
 Hagenzieker, M. P., Commandeur, J. J., & Bijleveld, F. D. (2014). The history of road safety research: A quantitative approach. Transportation research part F: traffic
psychology and behaviour, 25, 150-162.
 Jiménez-Mejías, E., Prieto, C. A., Martínez-Ruiz, V., del Castillo, J. D. D. L., Lardelli-Claret, P., & Jimenez-Moleon, J. J. (2014). Gender-related differences in distances travelled,
driving behaviour and traffic accidents among university students. Transportation research part F: traffic psychology and behaviour, 27, 81-89.
 Moridpour, S., Rose, G., & Sarvi, M. (2010). Effect of surrounding traffic characteristics on lane changing behavior. Journal of Transportation Engineering, 136(11), 973-985.
 Olstam, J. (2009). Simulation of surrounding vehicles in driving simulators.
 Pampel, S. M., Jamson, S. L., Hibberd, D. L., & Barnard, Y. (2015). How I reduce fuel consumption: An experimental study on mental models of eco-driving. Transportation
Research Part C: Emerging Technologies.
IS VEHICLE CONTROL AFFECTED BY SURROUNDING VEHICLES? (A DRIVER SAFETY PERSPECTIVE)
Name: Adesina AdelusiName: Adesina Adelusi
MSc (Eng) Transport Planning & Engineering
Email: ts14aoa@leeds. ac.uk
Supervisor: Dr Daryl Hibberd
Road type Lead vehicle type Following vehicle driver
Rural road Car Male
Heavy vehicle Female
2. Experiment Design
• The desktop driving simulator experiment design as described in Table 2 includes a
road type, traffic composition and a series of traffic events being presented to the
participants.
• There are two main scenario where the traffic events will be presented to the
participants . Each scenario should last about 20 minutes including a 5-10 minutes
familiarization time.
• A distraction event is also being considered.
Simulator drive Scenario car vs car Scenario car vs HGV Scenario Events
Participants will drive
on a Rural road
Base line (normal
drive) and
treatment drive
(events drive)
Base line (normal
drive) and treatment
drive (events drive)
Aggressive driving
behaviour and violation
including:
• Speeding & overtaking,
• Weaving (drink & drive)
• Running the stop sign.
*Distraction sub task?
5. Conclusion
• The outcome of this study is expected to follow similar trends as in previous studies
on the effects of driving behaviour on other road users.
• It will be interesting to observe the pattern of the data collected.
• Male drivers are expected to react differently to female drivers while heavy vehicles
are expected to have more effect on participants driving performance.
• Aggressive
behaviour and
• violation
• Rural roads
“accounts for 2/3
of road deaths in
the UK” (RRCGB,
2013)
• Cars
• Heavy Vehicles
• Longitudinal
control
(Headway)
• Lateral Control
(Lane change/
positioning)
Vehicle
Control
Surrounding
Vehicles
Driver
behaviour
Road type
Figure 5, Factors contributing to young drivers accident (RRCGB, 2011). Figure 6, Accident involving young car drivers aged 17-24 in 2012 per million
population (RRCGB, 2012)
Figure 3, Interaction contributing to accident cause (Lai, 2014). Figure 4, Comparison of available experiment methods (Lai, 2014).
Figure 2, Desktop driving simulator and its capabilities
Figure 1, Typical driving situation on a rural road in the UK (Riley, 2014).
Table 1: The fundamental basis for this research
Table 2: Experiment design to be implemented in the driving simulator
Experiment
Design
Participant
Recruitment
Simulator
Data
Collection
Data
Analysis

Understanding Choice of Departure Airport and its Relation to Surface Access
A Case Study of London Gatwick
and London Stansted Airports
Problem:
Currently, airport surface access in
the UK is heavily reliant on trips by
private car, which has resulted in
congestion on local road networks
and raised levels of pollution from
vehicle emissions.
57.2%
42.6%
Mode Share to London Gatwick Airport
Private Transport Public Transport
48.3%51.5%
Mode Share to London Stansted Airport
Private Transport Public Transport
 Both airports are the artery for short haul and
point to point flights across Europe which may
have similar travel pattern.
 Majority of the catchment area of both airports
are from South East of England.
 Both airports have a good score in public
transport mode share!
 To understand what is most important to air
passengers when making their travel decisions.
 To understand how the current surface access to
London Gatwick and London Stansted airports
influence passengers on selecting departure airport.
 To understand the relationship between
demographics of airport passengers and their choice
of departure airport with their preferred mode of
transportation.
 To model the current car parking charges and public
transport fares at both airports and evaluate the
effects on mode shares.
Research Objectives
Methodology
 Structured interviews to be performed on individuals
particularly flown from either two of the survey airports to
collect demographic information such as age, car ownership etc
with their respective transportation mode to airport. Besides
that, comments from respondents to gain insight into the current
issues related to surface access to airport that are not known to
the researchers.
 Data can be collected either in the departure lounge of airport
or in the train (provided with access permission), or from streets
of both airports catchment area if access to the restricted area
is denied. Sampling methods are carefully evaluated to avoid
sampling bias.
 Passengers Survey and Catchment Analysis data from UK Civil
Aviation Authority (CAA) could be used as Revealed Preference
(RP) data to provide deeper understanding regarding the
preference of departure airports.
 Fares information such as airport parking charges and public
transportation fares can also be collected through related
authority and online.London Gatwick and London
Stansted Airports?
Supervisor: Bryan MatthewsVincent Chan
Best P.T. Mode
Share to Airport
in the UK!
What makes you buy a
particular air ticket?
Airports
locations?
Cheapest Ticket
from A to B?
Quickest way? Most
convenient?Airlines?
 Choice of destination and airfare are the most important
drivers of airport choice.
 Access costs and time are the least important.
Key findings from previous research:
References
 Budd, T. et al. 2011. Airport surface access in the UK: A management
perspective. Research in Transportation Business & Management. 1(1),
pp.109-117.
 Johnson, D. et al. 2014. Understanding air travellers' trade-offs between
connecting flights and surface access characteristics. Journal of Air
Transport Management. 34, pp.70-77.

The Impact of High Speed Rail on Tourism
− A Case Study of Shanghai
Figure 1: Long-term trend line of Shanghai domestic tourist volume in the past 14 years
0
5000
10000
15000
20000
25000
30000
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Poster: YIFAN WANG (ml13y3w@leeds.ac.uk)
Programme of Study: Msc Transport Planning
Supervisor: BRYAN MATTHEWS
Figure 2: High Speed Rail in Shanghai
Background
Most researches about the impact of High Speed Rail (HSR) on
tourism have focused on Europe (e.g. France and Spain), and the
major direction of these studies explores whether the HSR service
can be a key factor to influence the choice of the destination for
tourism (Francesca et al., 2015; Marie et al., 2014). However, the
study area of the impact of HSR on actual tourist volumes and some
specific tourist travel behaviour is rarely discussed.
HSR is developing rapidly in China, especially in several mega cities,
such as Shanghai, Beijing, etc., however, there are only a few
studies that refer to this topic, and most of them are just based on
theoretical descriptions. Therefore, my research will mainly
concentrate on whether HSR can affect the tourist travel behaviour
and actual tourist volume in the Chinese tourism market, and how
to make the service better to improve the tourist industry with a
case study of Shanghai.
Objectives
1) Discuss the relationship between HSR and tourism based on a
review of literature.
2) Two sub objectives based on the case of Shanghai:
 Examine the travel behaviour of domestic tourists influenced
by HSR through an online survey.
 Examine the impact of HSR on domestic tourist volume in
Shanghai through the Tourism Background Trend Line (TBTL)
model.
3) Put forward some recommendations to make HSR serve the
tourism market better in China.
Methodology
Proposed scope: The data being used in this case will be
domestic data. According to Francesca et al. (2015) and Marie
et al. (2014), the impact of HSR is mainly to influence domestic
tourists, and this effect will be more significant in China
because there is almost no international HSR lines so far. In
addition, the TBTL model is mostly widely used on domestic
tourism (Li, 2009; Liu et al., 2012; Zhang et al., 2013).
1) Online survey
 Targeted group: people who don't live in but have travelled
to Shanghai at least once in the previous 2 years;
 Proposed key data to be collected (relate to questions):
travel purpose, origin, route choice, transport mode choice,
personal information (e.g. age, income, education, etc.),
travel frequency, travel scope and duration time.
2) TBTL Model
This model is most widely used in domestic tourist market
research in China, which was put forward by Gennian Sun in
1998. The key data we need in this case is the number of
domestic tourist travel to Shanghai every year, which can be
accessed from Shanghai Statistical Yearbook (2000-2014).
The Anticipated Result
According to the references, in most cases, HSR does influence the
destination choice of tourism, therefore, the result of this study is
expected that HSR will have an impact on both tourist travel
behaviour and domestic tourist volume in Chinese tourism market to
some extent.
Main References:
Francesca, P. et al. (2015). High Speed Rail and the Tourism Market: Evidence from the Madrid Case
Study. Transport Policy. 37, pp.187-194.
Marie, D. et al. (2014). Can High Speed Rail Foster the Choice of Destination for Tourism Purpose?
Procedia – Social and Behavioral Science. 111. pp. 166-175.
Liu, C., Wang, L. and Yang, A. (2012). Research on Inbound Tourist Market of Liaoning Province Based
on Tourism Background Trend Line. ICICA 2012, Part 1, CCIS 307, pp. 783-788.
Zhang, W. et al. (2013). Study on the Impact of High Speed Railway on Urban Tourism – Taking Nanjing
as an Example. Economic Geography. 33(7), pp.163-168.
Li, Z. (2009). A Research on the Foundation and Application of the Background Trend Line of Domestic
Tourism in China. Statistics and Information Forum. 24(1), pp.62-65.

Research on Capacity Reduced by Taxi
Picking Up on Curb Parking Facilities
Presenter: Yihang Liu Email: ml13y5l@leeds.ac.uk Msc (Eng) Transport Planning and Engineering Supervisor: Dr. Haibo Chen
Background
According to DFT
(2013), there were
an estimated 78
thousand taxis in
England and Wales
at end March 2013
and the grow ing
rapidly from 1985
(see figure right).
In most major cities, the taxi is a more convenient
mode due to its speediness, door‐to‐door attribute,
privacy, comfort, long‐time operation and lack of
parking fees.
The layout of harbor‐shaped taxi stop has negative
impact on the road capacity, as the limited number of
parking space leading the other taxis should occurs
queuing frequently and block one lanes of the urban road
(see figure), which causes extra delay and the congestion
on the links. So that, this work is going to model the
probability of the queue happened and the road capacity
reduced. Furthermore, calibration of the formula is
obtained with the survey data, and validation is
comparison between the micro‐simulation software
results and the calculated results.
Objective
This work aims to evaluate the harbor‐shaped taxi stop
impact on the capacity reduction in urban area and
obtain a formula to express the rule of actual flow.
Data collection
Time: afternoon peak period
Facility: video camera
Data category：Spot speed, Arrival flow, Arrival taxi flow,
Taxi stop time, Taxi stop layout
Methodology
Data Analysis &
Expected Results
The Gamma function should suit for the arrival taxi
rate and service rate to obtain the variable for the
next queuing theory.
The probability of with and without queuing should
be stable, acting as the weight for capacity
derivation.
After derivation process, the results calculated by
capacity formula should be close to the micro‐
simulation results.

Acomparative study of Transport InvestmentAppraisal Tools and
their implications on project selection
Yvonne M Keinembabazi (MA Transport Economics) | Dr James Laird (Supervisor) | Dr Astrid Gühnemann (2nd Reader)
4. DATA
5. METHODOLOGY
7. Key Reference
0
5
10
15
20
25
30
35
40
45
50
Engineering
Scores
Local
Consult
Scores
Economic
Scores
Composite
Scores
Quantity
Ranking System
Top Ranked Projects Selected with a $5 Billion Funding
Pool
No. of Projects Selected
Aggregate Jobs Added
(000)
Aggregate GDP Added
(Billion Dollars)
Total Wider Benefit
(Billion Dollars)
r = 1 −
6∗ 𝑑2
𝑛 𝑛2−1
To compare the rankings, the sign of the Spearman correlation will determine
the direction of association between the CBA rankings and GRP+B
rankings.(determining whether they are in agreement or not)
Spearman’s rank correlation coefficient
WEISBROD, G. Incorporating economic impact metrics in transportation project
ranking and selection processes. Annual Conference of the Transportation
Research Board, 2011.
To investigate whether there is a significant difference between
project rankings recommended by BCA and GRP/$
 Are projects with a more inclusive and environmental focus likely to
be neglected when GRP/$ prioritization method is the basis of
investment decisions?
 Does GRP/$ prioritization overlook a substantial proportion of
benefits provided by projects?
 Is GRP/$ prioritization equivalent to Benefit-Cost Analysis?
There is a range of techniques to prioritize transport projects..
Cost- Benefit Analysis (CBA) has been the most commonly used
appraisal tool in Europe, Australia and some states in USA (Benefit-
Cost Analysis). Frameworks differ by country.
CBA challenges; Rule of a half does not measure all economy impacts from projects
Alternative appraisal techniques
 Multi-Criteria Analysis
 Composite rating schemes e.g. Kansas (Engineering, Local consult, Economic)
 Cost effectiveness e.g. ranking based on GVA/£ e.g. England City Deals (Fully
devolved local transport funds);Urban Dynamic Model in West Yorkshire
 Each Appraisal tool has different factor weights which may affect project
selection (Weisbrod, 2011)
Overall
Economic
Impact
Change in
Transport
user
benefits
(CS)
Change in
systems
operating
costs
(PS)
Change in
costs of
externalities
Investment
costs
(Including
mitigation
measures)
3. CASE STUDY: KANSAS, USA
6. COMPARING CBA AND GRP+B RANKNGS
Data from Kansas Department of
Transportation
Systems
operating cost
Investment
Costs
Estimation of
externality costs
Estimation of
user benefits
California Life-Cycle Benefit-Cost Analysis Model
Estimation of costs and benefits over
the appraisal period (20 years)
Apply Discount
rate
(CalTrans=4.0)
Calculation of NPV, BCR and IRR
Presentation of CBA rankings
Presentation of rankings based on
economic impact score (Kansas DOT)
Compare CBA rankings and GRP+B
rankings
• Data on 121
highway
expansion
projects provided
by Kansas DOT
Data Set includes;
 Traffic data
 Highway design
(Speed, length, lanes)
 Highway accident
data
 Project costs
1.MOTIVATION
Kansas Composite Rating Scheme
Local Consult
Score
Economic ScoreEngineering
Score
Based on project
impact on traffic flow
Based on feedback
heard at local
consultation meetings
Impact on state-wide
Gross Regional Product
(GRP) plus value of
personal time and safety
benefits
2. OBJECTIVE AND RESEARCH QUESTIONS

VEHICLE HANDLING WITH SHARED HAPTIC CONTROL
Xianshuchang Wu
Supervisor: Hamish Jamson; Andrew Tomlinson
Institute for Transport Studies, University of Leeds, Leeds, U.K.
E-mail: ts14xw@leeds.ac.uk
WHAT IS SHARED HAPTIC CONTROL? WHY SHARED HAPTIC CONTROL?
Task
Automation
Response
Automation
Haptic
Interface
How does it work?
Hpi
From Pedal Feedback to Steering Feedback
Figure 1. A schematic, symmetric representation of SHC
(adapted from Mulder et al., 2012)
Progress towards Haptic Shared Control
MAIN FOCUS OF THIS WORK
Limitation of Previous Work
METHOD / PATHWAY
Hypothesis
Figure 3. Brief illustration for the main experimental process
Mainly Estimated Dependent Measures
Figure 2. University of Leeds Driving Simulator

Incorporating Transport Network Resilience with Building Information Modelling
Background
What is BIM?
Building Information Modeling (BIM) is a digital
representation of physical and functional
characteristics of a facility. A BIM is a shared
knowledge resource for information about a
facility forming a reliable basis for decisions
during its life-cycle; defined as existing from
earliest conception to demolition. In general, it
is a graphic tool to make projects virtualized
though the whole life-cycle. (e.g. Autodesk Civil
3D and Bently)
What is traffic resilience
1. Resilience of system is a measure of the
speed of its return to equilibrium.
2. The perturbation can be absorbed before
the system converges on another
equilibrium state
 Select an appropriate transport project
which is disrupt by nature– for example dual
carriageway destroyed by flood.
 Using the BIM software to simulate the loss
on a infrastructure caused by a perturbation.
 To Analyze not only the cost on the
infrastructure itself but also the direct and
indirect economic cost for road users in the
whole traffic network cased by perturbation.
 Mainly focus on the transport infrastructure
damage caused by nature perturbation without
casualties. And it can be restructured in short
term.
 Existing infrastructure built with BIM software
participated in before.
Proposed Scope
Methodology
Aims and objectives
BIM software
Cost of
rebuild and
the materials
Xian Wu Msc Transport Planning & Engineering Supervisor: Haibo Chen Second Reader: Daryl Hibberd
Transport
Software
Road users
delay and the
detour
distance
Total Impact
 BIM software can provide the materials needed during the restructured then
calculate the cost for this restructured
 After perturbation the traffic network will be influence continuously influenced
until it is totally repaired. All of the impact by perturbation can be simulated by
transport software. Such as the cost of extra time and longer distane on
passengers and some kind of environmental emissions caused by detour
Institute of Transport Study

What can we know about changing
multi-modal travel behaviour?
—Xiaojun Shao, MSc(Eng) Transport Planning and Engineering
Supervisors: Caroline Mullen, Giulio Mattioli
Background
In National Travel Survey (NTS) 2012, an index chart shows that between
1995/97 and 2012 the average distance of car/van driver trips and passenger
trips has fallen by 7% and 12% respectively. This decline in per capita car
travel has attracted people’s attentions. For instance, a roundtable meeting
organised by the New Zealand Ministry of Transport on this topic was
convened in London on 20 May 2014. They believe that the demand for car
travel is reaching its saturation level, any further growth will give little benefits
for travellers (Lyons and Goodwin, 2014). Therefore, a development of other
modes of transport is necessary in supporting the benefits of travellers.
Meanwhile, although there is a saturation in car use, the traffic congestion
problems still exist. One of the solutions transport policy is seeking for is to
encourage the use of alternative modes of transport, such as cycling and
walking (Ogilvie et al, 2004). For example, some policies such as car sharing
and bike sharing are now influencing people’s travel behaviour by
encouraging people to travel on multi-modes.
For its definition, there are different understandings. Nobis (2006) describes
that all persons who within 1 week use at least two different transport modes
are defined to be multimodal; Kuhnimhof (2006) believes that it is a property of
travel demand. No matter how many definitions exist, the importance of
multimodal travel is to make people rely less on private cars. Therefore, it can
be explained as a characteristic that people use modes other than just the car
across their travel patterns.
But what exactly is multimodal travel?
To help governments and local authorities shed lights on multimodal travel, an
understanding of how people are travelling these days and whether they are
using only one mode are necessary.
Furthermore, two key questions need to be answered:
• Does the NTS provide this understanding?
• How can the NTS or other surveys be improved to give a better
understanding?
Objectives
In realistic, multimodal travel may include every available transport mode, but
in this dissertation, only the choices between three groups will be used, they
are driving a car, using public transport (excluding airlines and ferries),
walking and cycling. Because these are the most common modes people use
to travel inside a city.
Scope
Methodology
The primary methods used to investigate the trend of multimodal travel are
literature survey and questionnaire. The scope of literature survey includes
papers that link multimodal travel to congestion management. For
questionnaire method, there are three steps could be taken in order to fulfil
the investigation:
• Identify the gap and limitation of multi-modal travel in the questionnaire
used in National Travel Survey;
• Determine what questions should be included and provide options for
participants to choose;
• Decide the sample size of the survey and provide the questionnaires online
for students and staff in ITS and other departments.
For the sample size, Peter et al. (2011) had a study on European multimodal
journey, they designed a questionnaire contains 18 questions and put it
online for people to participate. In the end, they have 200 responses in total
which provides an effective result. Therefore, a roughly 200 participants are
expected when doing the dissertation.
The analysis will be done with data mainly from National Travel Survey.
Data
Expected Findings
UNIVERSITY OF LEEDS
Institute for Transport Studies
• The NTS is an established series of
household surveys of personal travel and it
has been running continuously since 1988.
This study will mainly use the data between
2002 and 2012 to analyse the trends.
• NTS data is collected via two main sources -
interviews with people in their homes, and a
diary that they keep for a week to record their
travel. It covers travel by all age groups,
including children.
An example of how British
people travelled in 2012
From literature and data analysis, these are the results I expect to see:
• Develop a method to determine whether people are becoming more
multimodal.
• Multimodal travel can relief traffic congestion to some extent.
• The newly designed questionnaire can more capture people’s mode
choice of travel than the travel diary used in NTS.

Night-time Driving and Distraction
Xue Ding. MSC Transport Planning. Supervisor: Georgios Kountouriotis
E-mail Address: ml13x2d@leeds.ac.uk.
 Night – time driving expose to higher risk to
accident than day time. Number of miles driven
decreases substantially at night compared with
daytime, yet more than half of all traffic deaths
occur after dark.
 Is driving distraction contribute to this increase
in accident?
 This research uses driving simulator to collect the
driving performance data and then compare the
influence of different factors to driving
performance.
Prediction
 Comparing with day-time driving, eye-
movements (PRC) of night-time might rise due to
the dark view.
 Steering wheel reversal rate in bend road is easily
affected by distraction than straight road
 Visual distraction produced by in-vehicle
information system has more significant
influence on SDLP than visual distractionn on
road centre.
References
 Plainis, S., Murray, I. J., & Pallikaris, I. G. (2006).
Road traffic casualties: understanding the night-
time death toll. Injury Prevention, 12(2), 125-138.
 Pettitt, M., Burnett, G. E., & Stevens, A. (2005).
Defining driver distraction. In12th World
Congress on Intelligent Transport Systems.
 Stutts, J., Feaganes, J., Reinfurt, D., Rodgman, E.,
Hamlett, C., Gish, K., & Staplin, L. (2005).
Driver's exposure to distractions in their natural
driving environment. Accident Analysis &
Prevention, 37(6), 1093-1101.
 Merat, N., & Jamson, A. H. (2008). The effect of
stimulus modality on signal detection:
Implications for assessing the safety of in-vehicle
technology.Human Factors: The Journal of the
Human Factors and Ergonomics Society,50(1),
145-158.
Time
Road
Task
Day-time
Night-time
Straight road
Bend road
Visual (Center)
Visual (IVIS)
Count back
Baseline (No Task)
Distraction source % of drivers
Outside person, object. events 29.4
Adjusting radio, cassette, CD 11.4
Other occupant in vehicle 10.9
Moving object ahead 4.3
Other device/object brought into vehicle 2.9
Adjusting vehicle/climate control 2.8
Eating or drinking 1.7
Using/dialing mobile phone 1.5
Smoking related 0.9
Other distraction 25.6
Unknown distraction 8.6
Percentage of driver who cited each distraction
source as contributing to crashed
Total number of
participant
20
Age 20-30
Gender 10 male & 10 female
Driving experience Over 2 years
Preparation before
experiment
Provided with written
instructions about the
experiment
Driving time in
experiment
30 minutes
Methods
University of Leeds driving simulator will be employed to mimic
driving with different factors
Fig. 1. The University of Leeds Driving Simulator
Fig.2. night-time view
in driving simulator
(urban & rural)
• Steering wheel reversal rate
• Standard deviation lateral position (SDLP)
• Percentage of road centre (PRC)
• Data analysis tool: SPSS
• Data analysis method: Repeated Measures
ANOVA
Introduction
 Distraction is “attention given to a non-driving-
related activity. Typically to the detriment of
driving performance”
 Driver distraction plays an important role in
crash

Simulate
SATURN
Scenario 3
Adjusted Capacity
Network
2009 Existing Leeds
OD Matrix
Optimal Signal Plan
from LINSIG
Scenario 1
(Base Scenario)
2009 Existing Leeds
Network
2009 Existing Leeds
OD Matrix
2009 Existing Leeds
Signal Plan
Scenario 2
Adjusted Capacity
Network
2009 Existing Leeds
OD Matrix
2009 Existing Leeds
Signal Plan
Find Optimal
Signal Plan
using LINSIG
Simulate
DRACULA
SATPIG SPATULA
Detailed
Public Transport
Modelling of Bus
Frequencies, Bus
Stop Locations etc.
Adjust the Road
Supply
Condition/Capacity
due to Road Work
in Network.dat
Comparative
analysis
of outputs from
Scenario Runs
SATURN LINSIGDRACULA
2. Data
University of Leeds and Leeds City Council provided:
The SATURN model and data files have been constructed according to
WebTAG recommendations and validated against DMRB guidelines).
6. Scope and Data Analysis
Win Thi Ha , MSc (Eng) Transport Planning & Engineering
Supervisor : Dr Chandra Balijepalli
1. Background and Motivations
• Private and Public Transport Road Users suffer from delays, congestion
and unreliable journey times due to regular road closure to maintain and
improve old infrastructures and road system in the UK to meet the
increasing travel demand.
• More frequently digging up the roads by utility companies (Gas, Water)
• Government recently announced 55 major road schemes and local
transport projects with a further 15 billions spending between 2015-16
and 2020-21.
• Part of proposed 14.8km NGT
(Trolley Bus) route - Otley Road
(A660) section from the Ring
Road (A6120) Roundabout to the
junction of North Lane/Wood
Lane in Leeds, West Yorkshire.
A “quasi” dynamic element will be introduced into runs of SATURN by
modelling three successive AM time periods to include the effect of the
departure time choice.
Literature
Review
• Evaluation of Traffic diversion plans
• Traffic modelling softwares
• Monetary cost of congestion and delay due to road works
Implement
different
scenarios
• Link and Convert output route flows to facilitate interface with DRACULA from
SATURN Assignment O-D route flows using SATPIG and SPATULA programs.
• Adjust Road Capacity on planned road work routes according to diversion plan
• Develop LINSIG model to optimise and coordinate signals within study cordon
area.
Simulation
results and
data
analysis
• Comparative analysis of Modelling Scenarios Results on the effects of the road
work on private vehicles and public transport buses primarily at Micro level.
• Analysis of Measure of Effectiveness on worst congested junctions/ links/ nodes
at Macro level across Leeds Network in general.
Evaluating traffic diversion plan due to road works and assessing the
impact on private vehicles and public transport buses
Image © Copyright Descry and licensed for reuse under a Creative Commons Attribution-ShareAlike 2.0
Generic (CC BY-SA 2.0)
In Leeds Area alone during 2012-2013:
• 6,279 road works with average of
4.98 days
• 31,269 days of disruption
Source: Mitchell, 2014
(Leeds City Council Report)
• 830 Zones, 3034 Nodes.2009 Leeds Network
• 467,630 Total Flow, Three AM time periods
(7-8 , 8-9 and 9-10 AM).
2009 Leeds Trip Matrix
• Route , Traffic volume count, Speed, Distance.2009 Validation Count
References:
Goodwin, P. 2005. Utilities’ street works and the cost of traffic congestion. Research Report February,p.37. Centre for Transport &
Society, University of the West of England, Bristol.
Mitchell, P. 2014. Leeds Permit Scheme for Road Works and Street Works. Annual Report 2012-13.
Zhou, H. 2008. Evaluation of Route Diversion Strategies Using Computer Simulation. Journal of Transportation Systems Engineering
and Information Technology. 8(1),pp.61–67.
Cordon Network
Number of Zones 34
Number of Nodes 88
Simulation Links 192
Number of Signal Stages 30
Number of Roundabouts 3
Priority Junctions 52
Traffic Signals 9
Total Traffic Flow (Actual) 3357
4. Objectives
• To Minimise the impact and effect on private vehicles and public
transport buses due to road work.
• To Optimise signals of roundabouts and junctions within study
cordon area.
• To Understand positive/negative impacts of optimised signals by
analysing computer traffic simulation softwares outputs
• To Evaluate the traffic diversion plan and the effect on private and
public transport buses at Micro, Meso/Macro Levels.
5. Methodology
• Methodology itself is generic and widely used in local, regional &
national Traffic Management Centers.
• Implementing 3 different scenarios based on 2009 Leeds Network,
Signal Plan and Trip Matrix data.
3. Study Cordon Area
.
Figure 1: Cordoned off Leeds Network (Maps created using ArcGIS® software by Esri)
Email: ts13wth@leeds.ac.uk
In the UK:
• 7 millions days of disruption
• Valued at £1bn – £4.3bn
(Reports & Studies widely quoted)
• 5-10% of total congestion
Source: Goodwin, 2005
Special
events /other
5%
Bottlenecks
40%
Road works
10%
Traffic Incidents
25% Poor traffic
signal
timing
5%
Bad weather
15%
Source: www.ops.fhwa.dot.gov

What Safety Policies Should Accompany the Goal of Achieving More
Sustainable Urban Mobility: An Examination of Problems and
Policies in Europe
Taner Ulug, (MSc) Transport Planning and Engineering
Supervisor: Prof Oliver Carsten
UNIVERSITY OF LEEDS
Background
•European Union plans to achieve an overall
sustainable transport system in order to decrease
pollution and congestion.
•Sustainable urban mobility is a vital part of this
plan.
•About 40% of all road accident fatalities in the EU
occur in urban roads.
•11,000 deaths in 2012 on EU urban roads.
•65% of all urban road fatalities in the EU are
Vulnerable Road User (VRU) fatalities.
•A large proportion of serious road injuries occur
in urban areas and and involve VRUs.
•VRUs: Pedestrians + Pedal Cyclists +
Motorcyclists&Moped Users
•VRU safety needs to be improved in order to
achieve sustainable urban mobility.
United Kingdom‐Urban Source: CARE Database
Objectives
•To determine best performing three EU member
countries in terms of VRU safety on urban roads since
year 2000.
•To determine for which three main VRU modes these
countries have performed beter.
•To discuss the VRU safety policies which have possibly
contributed to the good performance of these
countries.
Data Collection
•Secondary data will be acquired for years since 2000.
•Community Road Accident Database(CARE) will be
utilized for this purpose.
Methodology
1. Analysis of annual changes in fatalities as reported
by transport mode in EU countries on urban roads,
rural roads, and motorways.
Analysis of annual changes in VRU fatalities by age
groups and gender.
2. Determination of best performing three member
countries in terms of VRU safety with a focus on
urban roads.
3. Determination of how these countries has
performed when other parametres such as age
groups, gender and VRU transport modes are
considered in order to understand the exact issues
these countries have tackled well.
4. Investigation of VRU safety policies implemented
by these countries particularly before the years
when there have been significant achievements
regarding the issues mentioned above.
Expected Outcome
The best performing three EU countries are expected
to be the SUN(Sweden‐United Kingdom‐Netherlands)
countries, but Denmark may replace the Netherlands.
Successful policies are possibly developed under the
following VRU safety issues;
•Investing in safer urban infrastructure
•Use of modern technology for enhanced urban road
safety
•Traffic rule enforcement and road safety education
Photograph Sources: Road Safety in the European Union, Vademecum_2015

As a consequence of the arid conditions, PM dispersion from the
region is hindered and secondary process such as wind driven
resuspension dominate.
This means that while gas-phase species associate with their primary
sources (e,g. traffic levels), PM does not.
In 2010 air pollution was estimated to
have caused over 400,000 premature
deaths in Europe.
Ambient air pollution was estimated to
cause 3.7 million premature deaths
worldwide in 2012.
2. MECCA
Mecca is a major centre for tourist and
religious pilgrimage in Saudi Arabia.
As in many cities, local air pollution is
affected by multiple inputs, including
emissions from traffic, construction work,
industrial practices, etc.
However, arid conditions make it
especially sensitive to particulate matter
(PM) pollution.
3. PROJECT DATA
In this project Air Quality data (including
CO, NO/NO2, and PM10) and PM
compositional data (anions, cations,
and metals) collected by Professor Turki
Habeebullah and colleagues at Umm
Al-Qura University, Makkah, will be
analysed with the intention of extending
understanding of local air quality in the
region.
4. OBJECTIVES/METHODS
The study will proceed as follows:
i) Use R and R package openair to characterise local air
quality data, and
ii) Use specialist software, including US EPA UNIMIX , to conduct
the first source apportionment of the dataset.
Trophius Kufanga. Msc Transport Planning & the Environment. ts13tk@leeds.ac.uk
References:
5. RESULTS
6. NEXT STEP: SOURCE APPORTIONMENT
0
1
2 w s
3
4
5
6
W
S
N
E
mean
PM10
500
1000
1500
2000
2500
3000
3500
0
1
2 w s
3
4
5
6
W
S
N
E
mean
NO2
10
20
30
40
50
60
Improved Air Quality Management for Makkah Al-Mukarramah (Mecca),
Source Apportionment of Air Quality and Particulate Composition Data
Supervisor: Dr. Karl Ropkins
2nd reader: Dr. Haibo Chen
Some Preliminary Findings:
The Saudi Arabian PM10 standard 340 ug.m-3 daily average,
not to be exceeded more than 24 times a year. In 2012,
this was exceeded 32 times.
However, unlike in UK, where PM10 standards are also regularly
exceeded, this was not associated with NO2 exceedances,
highlighting the different nature of the air quality problems in
Makkah.
0
50
100
150
200
250
Source#1
Cl
SO4
NO3
NO2
PO4
NH4
Br
F
PM
10
Source compositions for run # 2 - Linear Scale.
0
10
20
30
Source#2
Cl
SO4
NO3
NO2
PO4
NH4
Br
F
PM
10
0
0.5
1
1.5
2
Source#1
Source Contributions for run # 2
09/15/2012
09/27/2012
10/09/2012
10/27/2012
11/09/2012
12/03/2012
12/22/2012
01/26/2013
02/07/2013
02/19/2013
03/09/2013
05/20/2013
08/06/2013
0
2
4
6
8
10
Source#2
09/15/2012
09/27/2012
10/09/2012
10/27/2012
11/09/2012
12/03/2012
12/22/2012
01/26/2013
02/07/2013
02/19/2013
03/09/2013
05/20/2013
08/06/2013
UNMIX source
apportionment
of PM
composition
trends, which
are not affected
by resuspension
will help us to
identify PM
sources.
By contrast, PM10 associates
with higher wind speeds, in
particular from the South East
Many gas phase species, like
NO2,associates with low wind
speeds, an indication of local
stagnant air related sources
Hitchcock, G., et al. (2014) Air Quality and Road Transport. Impacts and solutions. RAC
Foundation. London, United Kingdom.
WHO (2014) Ambient (outdoor) air quality & health
High Volume
Systems
(HVS PM Samplers)
Ion Chromatography
Anions and Cations
1. GENERAL BACKGROUND

・Categorize questioners
→social economics
(gender, age and employment state)
→general impression of PTP
(how does PTP make you feel)
→interest for PTP/level of satisfaction of PTP
(how are people satisfied with PTP)
→modal changes
(how do people change into use of public
transport)
→interest for sustainability
(continuous of new travel behavior)
・Using regression analysis
→how is effectiveness of PTP related with
questioners?
→For example, how much effectiveness of PTP is
linked with age or gender? Is there any difference
in the effectiveness between women and men?
・To know who changes travel behavior
・To know how they change travel behavior
・To know why they change travel behavior
・To know how the impact of PTP can be measured
・ Follow up survey to determine the influence of PTP on travel behavior
・10 different cities in the UK from 2009 to 2014
・4786 data of PTP in those areas
・7-15% decrease in car trips can be expected
・12% reduction in the mean distance travelled by car
・increases in walking, cycling and public transport trips of between 14% and 33%
・effectiveness of PTP would last about 3 years
Because of increase in cars…
→environmental problems (increase in CO2)
→health problems (effect on respiratory)
→traffic problems (congestion)
Introduction of PTP
What is PTP ?
・PTP is one of the methods of soft measures
・Through one to one conversation with trained field officers
・Officers encourage and motivate people to change their travel behavior by giving
provision of information on how to travel sustainably
・Useful information and good are given such as time table for each person or free
trial public bus tickets
Who changes travel behavior and why ?
Tomoko Amahori : MSc Transport Planning and the Environment Supervisor: Jeremy Shires
Backgrounds
Effectiveness of PTP
Data of PTP
Objectives
Methodology

Can Development on the Green Belt be Sustainable?
BACKGROUND
Green belt is open space used for forestry and agriculture.
In spite, its importance for environment, some local
authorities change the land use for construction of
residential, industrial and other projects. One of the most
common reason for changing land use is to facilitate the
economic growth of the region and meet increasing
demand for affordable houses among people at the
expense of the Green belt. This study will attempt to
measure Sustainability of the Development on the Green
belt and assess Transport impact. The housing development
of 4020 dwellings on the North of Clifton Moor and A1237
will be considered for assessment. It will be located on 330
of acres of Greenbelt land.
AIM
To investigate whether development on the Green belt can be
Sustainable.
OBJECTIVES
• To assess Sustainability of the Development on the Green
belt
• To assess the Transport Impact Assessment on New
Housing proposal on the North of York on the Green belt.
METHODOLOGY
• Review of the polices, guidelines and planning
documents related to Transport Assessment and
Sustainability Assessment.
• Define criteria and alternatives in MCA .
• Define appropriate technique of MCA
• Multi criteria analysis of Sustainability.
• Analysis of findings from MCA.
• Analysis of existing SATURN road network of York
City.
• Estimation of new trip projected values for trip rates
with the use of TRICS, TRIPS and TEMPRo software.
• Updating SATURN OD matrix and network files.
• Assessment of public transport accessibility.
• Traffic Impact Assessment of the Proposed
Development with SATURN software.
• Development of recommendations for mitigation
from impacts.
EXPECTED RESULTS
• Identification of impact from Transport.
• Sustainability appraisal of the development on the Green
belt.
Supervisor: Dr. Chandra Balijepali Student: Talgat Abdrakhmanov Email: ts14ta@leeds.ac.uk
Preparation of
Transport
Assessment
Final
Transport
Assessment
Reducing the
need to travel
Maximizing
Sustainable
accessibility
Dealing with
Residual trips
Mitigation
measures
References: 1. Multi‐criteria analysis: a manual. DCLG, 2009. 2. Guidance on Transport Assessment. TfL, 2007.
Policy context
Existing Site function
Proposed Development definition
Identification of Impacts and mitigation measures
NATA Assessment
Capacity Assessment
Identify problems
Preliminary design of mitigation measures
Scoping study
Initial appraisal consultation form
Scoping study
Agreement of methodology
Background data
Existing travel patterns by mode
Accident history
Environmental base case
Passenger transport services
Committed development
Committed transport network
charges
Parking availability
Refinement step 2
Where appropriate
Additional support
Alterations to ITB measures
Refinement 1
(where appropriate)
Seek to reduce residual trips
Review:
Development mix
Scale of development
phasing
Measures to influence Travel behavior
Parking availability and Management
Improvements to non‐car model
Travel plan initiatives
Capacity Management
Network alterations
Assessment
Trip generation by mode
Accessibility Assessment
Assignment of trips
Source: Transport Assessment Guidance. TfL, 2007.

5. Expected Outcomes4. Preliminary Results
 Global travel demand contributes to the increase of fuel
consumption in airlines.
 U.S. airlines are the main contributors (18 billion gallons).
 No alternate energy, so policy-making to manage the fuel
demand is important.
Decomposition Analysis of Aviation Fuel Demand of U.S. Airlines
Shan-Che Wu | Institute for Transport Studies | Transport Planning and Engineering | Supervisor Zia Wadud
1. Background
Year Passenger (million) Freight (million tons)
1991 461.2 9.0
2013 748.5 12.3
Growth 62% 37%
(Airlines in the U.S.)
2. Objectives
 To find some components linking the travel with fuel
consumption
 To decompose the fuel demand into various components
with decomposition model
 To initiate analyzing the freight-related factors
 To set a freight forecast demand model
Multiplicative decomposition
-
5
10
15
20
25
1991 1994 1997 2000 2003 2006 2009 2012
Fuel(billiongallons)
Fuel consumption of airlines in the U.S.
Total Passenger in Passenger aircraft
Belly freight Freight in freight aircraft
3. Index Decomposition Analysis
 Fuel = Population(POP) × REV.ton.miles per capita ÷ Load factor × Efficiency
𝐹𝑢𝑒𝑙 = 𝑃𝑂𝑃 ×
𝑅𝑇𝑀𝑃 𝑃
𝑃𝑂𝑃
×
𝐴𝑇𝑀𝑃 𝑃
𝑅𝑇𝑀𝑃 𝑃
×
𝐹𝑢𝑒𝑙(𝑃𝑃)
𝐴𝑇𝑀𝑃 𝑃
--- passenger in passenger aircraft
+𝑃𝑂𝑃 ×
𝑅𝑇𝑀𝐹 𝑃
𝑃𝑂𝑃
×
𝐴𝑇𝑀𝐹 𝑃
𝑅𝑇𝑀𝐹 𝑃
×
𝐹𝑢𝑒𝑙 𝐹𝑃
𝐴𝑇𝑀𝐹 𝑃
--- freight in passenger aircraft
+𝑃𝑂𝑃 ×
𝑅𝑇𝑀𝐹(𝐹)
𝑃𝑂𝑃
×
𝐴𝑇𝑀𝐹(𝐹)
𝑅𝑇𝑀𝐹(𝐹)
×
𝐹𝑢𝑒𝑙(𝐹𝐹)
𝐴𝑇𝑀𝐹(𝐹)
--- freight in freight aircraft
 Logarithmic Mean Divisia Index (LMDI) is of better performance
Additive decomposition
and∆𝐹𝑢𝑒𝑙 = 𝐹𝑢𝑒𝑙𝑡 − 𝐹𝑢𝑒𝑙0
𝐹𝑢𝑒𝑙 𝑡
𝐹𝑢𝑒𝑙0
=
𝑃𝑂𝑃𝑡
𝑃𝑂𝑃0
×
𝑅𝐸𝑉. 𝑡𝑜𝑛. 𝑚𝑖𝑙𝑒𝑠 𝑝𝑒𝑟 𝑐𝑎𝑝𝑖𝑡𝑎 𝑡
𝑅𝐸𝑉. 𝑡𝑜𝑛. 𝑚𝑖𝑙𝑒𝑠 𝑝𝑒𝑟 𝑐𝑎𝑝𝑖𝑡𝑎0
÷
𝐿𝑜𝑎𝑑 𝑓𝑎𝑐𝑡𝑜𝑟𝑡
𝐿𝑜𝑎𝑑 𝑓𝑎𝑐𝑡𝑜𝑟0
×
𝐸𝑓𝑓𝑖𝑐𝑖𝑒𝑛𝑐𝑦𝑡
𝐸𝑓𝑓𝑖𝑐𝑖𝑒𝑛𝑐𝑦0
∆𝐹𝑢𝑒𝑙 = ∆𝐹𝑢𝑒𝑙 𝑃𝑂𝑃 + ∆𝐹𝑢𝑒𝑙 𝑅𝐸𝑉.𝑡𝑜𝑛.𝑚𝑖𝑙 𝑝𝑒𝑟 𝑐𝑎𝑝𝑖𝑡𝑎 + ∆𝐹𝑢𝑒𝑙1/𝐿𝑜𝑎𝑑 𝑓𝑎𝑐𝑡𝑜𝑟 + ∆𝐹𝑢𝑒𝑙 𝐸𝑓𝑓𝑖𝑐𝑖𝑒𝑛𝑐𝑦
∆𝐹𝑢𝑒𝑙 𝑝𝑜𝑝 =
𝐹𝑢𝑒𝑙𝑡 − 𝐹𝑢𝑒𝑙0
𝑙𝑛𝐹𝑢𝑒𝑙 𝑡 − 𝑙𝑛𝐹𝑢𝑒𝑙0
× (𝑙𝑛𝑃𝑜𝑝𝑡 − 𝑙𝑛𝑃𝑜𝑝0)
 Revenue ton miles per capita is the most key factor.
 Efficiency has been gradually improved to save fuel
because of management and technology
 Hope to link the aircraft freight demand with
economic factors
 Fare, journey time, and income might be the most
influential parameters in demand model.
Decomposition analysis summary
1. Revenue ton mile per capita always increasing except 2000-2002 (911 terrorist attack) and 2006-2008 (economic recession).
2. Load factor and fuel efficiency slow the growth rate of fuel use.
3. Most of the changes in fuel consumption due to changes in revenue ton mile per capita.
-6
-3
0
3
6
Changeinfuelconsumption(billion
gallons)
POP RTM/POP 1/Load factor Fuel/ATM
Additive and Multiplicative
decomposition in 3-year
band: 1991-2011
0.8
1
1.2
POP
RTM/POP
1/Load factor
Fuel/ATM
1991-1993 1994-1996 1997-1999 2000-2002
2003-2005 2006-2008 2009-2011
Data sources: Bureau of
Transportation Statistics,
Department of
Transportation in U.S.
Evolution of fuel consumption and its components: 1991-2013; 1991=1.0
0.0
0.5
1.0
1.5
2.0
2.5
3.0
1991 1994 1997 2000 2003 2006 2009 2012
Index(1991=1.0baseyear)
POP RTMP(P)/POP RTMF(P)/POP RTMF(F)/POP RTMP(P)/ATMP(P)
RTMF(P)/ATMF(P) RTMF(F)/ATMF(F) Fuel(PP)/ASM(P) Fuel(FP)/ATMF(P) Fuel(FF)/ATMF(F)
Fuel (PP) Fuel (FP) Fuel (FF)

Causative Factors of Accidents on Curve Negotiations: A Case Study of Malaysia
Seri Ashikin Binti Sofian, MSc.Eng Transport Planning & Engineering Supervisor: Dr. Samantha Jamson Co-Supervisor: Dr. Frank Lai
• Traffic accidents rank fifth among the leading cause
of deaths in Malaysia.
• It is estimated that, one quarter of all accidents
happen in Malaysia occur while driving around
curves and in most cases contribute to fatal
accidents. Therefore, it is vital to understand the
factors lead to an accident that occurs on a curve.
• IRTAD report 2014, based on willingness-to-pay
estimation, road accident accounted for
approximately 1.6% of Malaysia national GDP.
• The accident rates in road curves are about 1.5 to 4
times higher than in straight roads
(Zegeer, Stewart, F. M. Council, Reinfurt, &
Hamilton, 1992).
• The accident severity of curve related crashes is
higher than those occurring in straight roads
(Glennon, Neuman, & Leisch, 1985).
• Accidents are not uniformly distributed on the road
network, high accident locations are a clear
indication that, besides human factor, there exist
other influencing parameters that are characterized
by the road (Lamm et.al, 2007).
• The curve's location chooses for this study are
identified from the 186 blackspot locations treated
under the ‘Rehabilitation Works Programme’ done
by the Public Works Department of Malaysia
(PWDs) from year 2009 to 2014.
• Seven (7) locations of curve are identified from the
blackspot locations and data collected from this
location are gathered through the POL form obtain
from the Royal Malaysian Police (Traffic
Department).
Background of Study Determine the factors that contribute to the accident
occurrence in a curve
Identify the characteristics to the cause of the
accidents occurrence on a curve
Recommendation for road accident on curve
treatment
Objectives
Research Questions ?
“What are the factors that have influenced
for accidents to happen on a curve”
“Is there a relationship between
demographic and road factors which
contribute to an accident on curve”
Theoretical Framework
Demographic
• Age
• Gender
Road
• Length of
curve
• Radius of
curve
Numbers of
fatal accident
Methodology
Null Hypothesis
• Road factors contribute to an event of an
accident on a curve
• Demographic factors influence the driving
behaviour and the occurrence of the
accidents on the curve
• Both, demographic and road is contributory
factors in an accident on a curve
Alternative Hypothesis
• Road factors does not bring impact to
the occurrence of an accident on a
curve
• Demographic factors do not influence
the driving behaviour
• Both factors fail to demonstrate
relationship their behaviour towards an
event of an accident on the curve
Statistical Analysis
All accidents data obtained from the Public Works Department of Malaysia (PWD Malaysia) and POL Form from
Royal Malaysian Police will be put through a data cleansing to check its validity and reliability. This is also done in
order to find the demographic information such as age and gender of the driver of the vehicle. This analysis will
use the SPSS package in order to look into the relationship between the variables by using the regression
models. The variables of road factors will be studied from seven (7) curve’s location from the blackspot lists,
whereas for the demographic factors, 2 locations from this will be analysed.
Data Cleansing
• To check on the
reliability and
validity of the
data
Information
Analysis
• Seek demographic
information from
the POL form.
• Geometry of the
location (length
and radius)
Factor analysis
• Correlation
between factors
• Linear Regression
(Binary Logistic)
Results
• Significant level
of the hypothesis
testing
Expected Outcome
• It is expected that the demographic and road factors, will be the factor in an accident on
curve negotiation. Other than that, a significant relationship can be seen from both factor and
relate to the accident occurrence on a curve.
• The findings from this study is yet to be used in the future in order to rectify the accident
problem that mostly occurs on a curve. On the other hand, this study can suggest for the
treatment and countermeasure to be taken in the road safety enhancement with a focus on a
curve negotiation.
Kuala Lumpur – Karak Highway

D e v e l o p i n g A c c e l e r a t i o n M o d e l s
C o m b i n i n g M u l t i p l e D a t a
Stavros Papadimitriou (Author); Charisma F. Choudhury (Supervisor); Daryl Hibberd (2nd Reader)
B A C K G R O U N D
I-80 Study Area Schematic
and Camera Coverage
Ø Driver behavior data from an artificial scenario in a controlled
environment may not resemble driver behavior that is displayed
in a comparable real world situation (Carsten et al., 2011)
Ø Calibration and validation in driving simulators generally
performed at a macroscopic level (Sakia & Hoogendoorn, 2008) and
studies mainly generate macroscopic outputs, (Olstam, 2005)
ignoring driver specific information.
1 M E T H O D O L O G Y
d a t a
Driving Simulator
Schematic of Road Section
ü X and Y coordinates every
1/10th sec for acceleration
decisions of drivers;
ü over a stretch of 1/2 km for
an hour (between 16:15
17:15);
ü similar traffic density
(roughly 1600-2400 vph);
ü 40 subject drivers are
recorded;
m o d e l l i n g a p p r o a c h
E X P E C T E D R E S U L T S
c a s e s t u d y
3.2
3
4
NGSIM Driving Simulator
C r o s s – C l a s s i f i c a t i o n A n a l y s i s
S t a t i s t i c a l A n a l y s i s
Maximum Likelihood Method (MLM)
Models format
Responsen (t)= Sensitivityn (t-Tn) x Stimulusn (t- Tn)
Where,
-  t = time of observation,
-  Tn = reaction time for driver n,
-  Responsen (t) = acceleration applied at time t
STATA
Estimation method
Statistical software
Models performance
& comparison
Tests of statistical significance (e.g. t-statistics)
3.1
Ø Real-life trajectory data are really important so far for calibration
and validation of microscopic models. However, most studies
focus on the investigation of lane changing (Thiemann et al., 2008;
Ahmed, 1999)
2
Simulation Environment
Physically Driving
Two data sources will be used in this research:
(1)  The real-life traffic detailed trajectory data collected
from Interstate 80, CA, US (NGSIM 2005);
(2)  The experimental data collected from the University
of Leeds Driving Simulator (UoLDS).
Microscopic data collected from,
(i)  Real trajectory data from physically driving;
(ii)  Driving simulator data from a simulated
environment using a driving simulator.
•  Leader speed
•  Time headway
•  Type of vehicle
•  Reaction time etc.
•  Leader speed
•  Gender, Age
•  Type of vehicle
•  Reaction time etc.
§  Statistical comparison of the models will indicate significant
differences in common model parameters (e.g. leader speed,
headway, subject vehicle type);
§  The combined model will better replicate the traffic compared to
models developed using single data sources.
The objective of this dissertation is to develop and compare the
performance of the acceleration models using two sources
microscopic data, as well as testing a combined model using both
data sources. Models will take into account network topography and
traffic conditions.
•  Model 1 uses only traffic video data;
•  Model 2 uses only driving simulator data;
•  Model 3 uses both.
1000m1000m
2000m
503m(1650feet)
Study Area
7 video
cameras
O B J E C T I V E S

EMERGENCY TRANSPORT PLANNING FOR MATERNAL HEALTH IN RURAL GHANA
MAHAMA SEINU SEIDU, MSc TRANSPORT PLANNING AND THE ENVIRONMENT          SUPERVISOR: JEFFREY TURNER    2ND READER: FRANCES HODGSON
BACKGROUND
REFERRAL SYSTEM
AIM AND OBJECTIVES
METHODOLOGY
EXPECTED OUTCOME
REFERENCES
Thaddeus and Maine,1994
The aim of the study is to assess the impact/effect of Ambulance
services in maternal health
OBJECTIVES:
The study is to focus on understanding and assessing the role of
ambulance services in emergency maternal health in Ghana. This is
intended to be achieved through :
 Assessment of the role and impact of Ambulance services in
maternal health delivery in rural areas .
 Whether or not Ambulance services have any significant
contribution to reduction of maternal mortality.
 How efficient and effective transport can improve emergency
maternal health intervention in rural Ghana
Millennium Development Goal (MDG 5),maternal mortality is
identifies by the United Nations(UN) as a serious concern for the
welfare of women across the world particularly a pandemic in
developing countries and specifically an “unfortunate tragedy in sub
sahara Africa as the region records the highest maternal mortality
ratio” (Ganyaglo & Hill, 2012)
 About 350,000 women die annually from pregnancy related causes
and child birth complications .
 Utilization and access to health facilities for maternal services in
these settings is hindered by several factors including lack of
transport and high cost –(4) .Referral intervention aim to address
these problems and one such intervention is the provision of
emergency ambulance referral transport services.
 In most developing countries such National ambulance services
have not been sustained effectively, providing very limited, or no
service. As a result, many segments of the population, particularly
in rural or peri‐urban areas are not covered and this poses serious
challenges to reach the appropriate health facility in case of an
emergency.
 In Ghana ,the maternal mortality ratio (MMR) is currently 350 in
every 100,000 live births .It is estimated that 75 percent of the
women who die in the course of childbirth do so as a result of
inadequate emergency transport‐(1).
 Transport is critical in the provision of health delivery and access to
services, and in the Overall effectiveness of the referral process.
 As have been identified by Thaddeus and Maine(1994), poor access
and lack of reliable transport also explain why families delay in
seeking care in an emergency situation or arrive too late at health
facilities for effective treatment as well as poor service utilization.
 Emergency transport interventions could save an estimated 75
percent of pregnant women each year, which could further save
nearly 14,500 births if functional referral systems are put in place.
The study will  be  conducted in the  Millennium Village  project
communities  in the Ashanti Region of Ghana. A literature review
will be done. Data on ambulance utilisation for maternal
emergency referral in the health facilities in this communities
will be accessed. Other case  received without intervention of
the ambulance services within  the same period will also be
collected .The response times and cost will be determined as
well as the outcomes of the different scenarios. Analysis will
then be done to assess the impacts.
 Lack of ambulances and absence of other means of transport
in remote areas (Shehu et al. 1997) and high transport costs
represent a major constraint for women and their families
who need to access health facilities for both preventive and
emergency care. A key solution therefore is to improve
transport access in a way that is both affordable and
sustainable for these two levels of care.
 It should be possible to reduce maternal deaths in rural Ghana
by effective and efficient emergency (ambulance) referral
transport planning .
1. Babinard,J. and Roberts,P.,2006  Maternal and Child Mortality Development Goals:
What Can the Transport Sector Do? The World Bank Group Washington, D.C.
http://www.worldbank.org/transport/
2. Thaddeus S, Maine D (1994) Too far to walk: maternal mortality in context. Soc Sc
Med 38(8): 1091–1110.
3. Lungu K, Kamfose V, Hussein J, Ashwood‐Smith H (2001) Are bicycle ambulances and
community transport plans effective in strengthening obstetric referral systems in
Southern Malawi. Malawi Med J 13: 16–18.
4. Maxwell Ayindenaba Dalaba,et al.,2015 Cost to households in treating maternal
complications in northern Ghana: a cross sectional study. BMC Health Services
Research 2015, 15:34  doi:10.1186/s12913‐014‐0659‐1
5. Murray SF, Pearson SC (2006) Maternity referral systems in developing countries:
current knowledge and future research needs. Soc Sc Med 62: 2205–2215.
6. WHO | Maternal mortality [http://www.who.int/mediacentre/factsheets/fs348/en/]
Without intervention
With intervention
UNIVERSITY OF LEEDS

`
Utilizing Real Time Bus Information Technology
To Encourage Bus Travel
Student: Steven Lightfoot (email: ts12sdl@leeds.ac.uk), Supervisors: Jeremy Toner and Mark Wardman
Background
• Metro Tracker survey 2014, Vector research
• Mishalani, Rabi G., Sungjoon Lee, and Mark R. McCord. 2000. "Evaluating real-time bus arrival information
systems." Transportation Research Record: Journal of the Transportation Research Board 1731.1: 81-87.
• Moss S 2015. The Guardian website. Available from: http://www.theguardian.com/cities/2015/apr/28/end-of-
the-car-age-how-cities-outgrew-the-automobile
• Tang, Lei, and Piyushimita Vonu Thakuriah. 2012 "Ridership effects of real-time bus information system: A
case study in the City of Chicago." Transportation Research Part C: Emerging Technologies 22: 146-161.
• Transportation Research Part A: Policy and Practice, Volume 45, Issue 8. 2011, Pages 839–848
• Transportation Research Part C: Emerging Technologies. Volume 53. 2015, Pages 59–75
• TLP Projects – Monitoring Report 2009 to 2013, Metro 2013
• Traveline. 2015. (online). Available from: http://dashboard.mxdata.co.uk/traveline/Account/login.aspx
Objectives
• New technologies enabling the provision of real time bus information and the
growth in smartphone use have the potential to transform the way people
view bus travel options.
• Utilize real time information to improve the way bus information is presented to the
public.
• Set out best way of displaying real time information to public on stop displays,
computers and mobile phones.
• Maximize public access to, awareness and usage of real time information.
• Set out best practice and future developments that will show how real time
information can be utilized by bus operators and traffic control centers to improve
reliability and speed whilst reducing operating costs.
Data and Scope
• Real time systems and literature from across the world will be reviewed.
• Data sources include: transport press, West Yorkshire bus user survey,
public usage of real time outputs in Yorkshire, real time user groups etc.
• Focus for recommendations will be Yorkshire, however they will be able to
be adapted for other areas.
• Recommendations will aim to retain existing bus users and attract new
users.
• Recommendations will focus on existing bus regulation system in Yorkshire,
but will consider different regulation models.
• Risks include:
• Difficulty accessing commercially sensitive formulas used to generate real time
predictions.
• Lack of regulation meaning there is no central body able to ensure recommendations
are implemented.
Methodology
• Result 1
• Result 2
• Result 3
Initial Findings
References
• Provision of real time bus information can increase bus usage.
• Can reduce both actual wait time and perceived wait time
• ‘Digital information is the fuel of mobility’,
• ‘Information about mobility is 50% of mobility’
• Large increase in real time mobile apps availability and usage facilitated by
open data provision.
• First and Google apps dominate Yorkshire market with 88% market share.
• 290% increase in real time mobile app usage in last 6 months in West Yorkshire.
• More modest increase in internet usage and a fall in text usage.
• Awareness of real time mobile internet and apps still relatively low at 27% in West
Yorkshire.
OBJECTIVE 1 – PRESENTATION
OBJECTIVE 2 – ACCESS AND USAGE
OJECTIVE 3 – SPEED, RELIABILITY AND COST
• Real time bus information utilizes satellites to track bus locations. This
enables accurate arrival times bus to be shown to the travelling public,
instead of just timetable information.
• Real time bus systems have been introduced in major transport areas across the
world.
• Difficulty accessing and using bus information has historically been a significant
barrier to encouraging sustainable travel behaviour.
• Real time information can be shown on mobile phones. Mobile phone usage is
increasing across the world. The proportion of people in West Yorkshire with a mobile
phone has increased from 90.3% in 2012 to 93% in 2014.
• Bus usage is falling in West Yorkshire. The proportion of people using a bus monthly
has fallen from 57.1% in 2011 to 52.4% in 2014.
• Technological advances have improved the practicality and reduced the cost
of real time bus information systems.
• Real time bus technologies present new opportunities for improving bus
reliability through linked technology.
• Including Traffic light bus priority and improved scheduling.
• The output from real time can be used to improve bus services.
• Operators in Yorkshire analyze past performance to improve scheduling. This can
increase reliability and reduce operator costs.
• Link to Yorkshire traffic control centers can give traffic light priority to buses. This can
increase reliability and reduce journey time and operator costs.
• Introduction of bus traffic light priority to 200 junctions in West Yorkshire was shown to
have a Benefit:cost ratio of 8.

Evaluation of the Influence on Driving Behaviour by Music Tempo
Data Collection
• Free driving task
1. Average, maximum, minimum driving speeds
2. Average, maximum lateral deviations
• Overtaking task
1. Maximum speeds
2. Minimum headway distances before and after
overtaking
• Approaching signlised junction task
1. Decision making
2. Violation frequency
3. Passing speeds
• Stopping task
1. Reaction time
Objectives
The study will be approached through driving
simulator. Four questions are aiming to be
answered in this research about lisening slow/fast
tempo music during driving:
1. How much degree of influences on driving
performance under free driving condition?
2. Does the music induce more dangerous driving
in overtaking process?
3. Will the drivers be more aggressive towards a
signalised junction?
4. Is there any deterioration in reaction time for an
emergency stop?
Background
Dibben and Williamson (2007) conducts a survey
and finds that 75% young drivers listen music
during driving. However, the young drivers, who
preferred no music driving environment, are less
involved in road accidents.
The study in Brodsky(2001) selects some fast
tempo music to test the driving performance.
Higher driving speed, and more frequent traffic
violations are shown. Fast-paced music is proved
to deteriorate the driving behaviour.
In most of the previous studies ,drivers are tested
by driving in a city through driving simulator, but
not in some specific critical conditions. In current
study, some specific scenarios will be set up in
order to thoroughly investigate the driving
influence on these conditions, for example,
overtaking, dilemma in signalised junction, and
emergency stop.
Waterhouse et al., (2010) mentions that apart from
tempo, lyrics, melody, loudness and other
particular circumstance can also affect the musical
taste. To reduce the variables, same set of music
tracks, which differed in tempo, are used in this
study.
Tasks in a testExperimental Designs
20 driving licence owners, who age from 20-30
years old, will be invited to parcitipate the
experiment, because they are the most frequent
group of listening music, as well as the highest
risk group of getting involved in accidents.
Experimental flow is below:
Briefing (15mins)
• Introduce about the experiment, including all the
tasks they will meet in the test.
• Explain the manipulation of driving simulator.
• Provide free driving section for familiarisation.
Testing (55mins)
• Without music, fast tempo and slow tempo
scenario tests will be finished by participants
respectively in random order.
Surveying (10mins)
• Complete a self-reflection questionnaire
• Personal information: age, gender, driving
experience, etc.
• Personal perception in slow and fast tempo
music for each individual task
• Any mistake has taken in the test.
Driving Simulator
Overtaking
Approaching
signalised
junction
Stop
immediately
and restart
Overtaking
Start to play
slow/fast tempo
music
Approaching
signalised junction
Stop immediately
and finish
Free Driving
for 10 minutes
at 60mph
Free Driving
for 10 minutes
at 60 mph
2 mins 2 mins
2 mins2 mins
Data Analysis and Expected Results
Three sets of dependent variable data comparisons
will be analysed:
• Without music VS Slow tempo music
• Without music VS Fast tempo music
• Slow tempo music VS Fast tempo music
The results from the fast tempo music are expected
to show:
• higher free driving speeds,
• dangerous overtaking behaviour, with higher
speeds and shorter headway distances
• tending to pass the signalised junction with higher
speed rather than decide to stop in dilemma
situation,
• and a longer reaction time.
Li Shaotang, Alvis Email: ml13l6s@leeds.au.uk Msc (Eng) Transport Planning and Engineering Supervisor: Dr. Daryl Hibberd

Motorcyclists’ Acceptance of Automated
Road Transport Systems in Taiwan
Shu-Cheng, Hsieh (ml13sch@leeds.ac.uk)
MSc (Eng) Transport Planning & Engineering
Supervisor: Dr Natasha Merat, Tyron Louw
 Motorcycles in Taiwan
 Large density and amount of registered motorcycles
 Motorcycles : Other vehicles = 1.8 : 1
 Public Transport in Taiwan
 Projects promoting public transport
by Taiwanese government since 2010
 Involving buying new buses, improving
service quality, providing real-time and
subsiding rural routes
2. Background
Year Car Bus &
Coach
LGV HGV Subtotal Motorcycle
2013 6,236,879 31,960 875,544 162,122 7,367,522 14,195,123
2014 6,405,778 32,928 890,703 163,446 7,554,319 13,735,994
 Road user interactions
 Conflicts between
motorcycles and buses
(Particularly at bus
stops)
Public Transport
 Little changes on usage
 Financial difficulties for
operators
 Lack of drivers
3. Research Problems
 An example: City Mobil2
 An EU project
assessing ARTS
 Deliver ARTS in several
European cities
 Investigate road users acceptance
(focus on pedestrian)
 Aims:
1) Evaluate what ARTS could provide to sustainable
transport
2) Examine and improve interactions between ARTS and
other road users
How about in Taiwanese
transport environment?
4. Research Motivation
 Literature review, technology approach and integration
 Questionnaire
 Sample: Motorcyclists in Taiwan
 Asking acceptance in two sections
 Data Analysis and discussion
5. Methodology
Section 1
• Applying Drive Behaviour Questionnaire
• Initial acceptance by introducing ARTS
Section 2
• Scenario with safety systems on ARTS
• Scenario with road infrastructure for ARTS
 Understand the factors that influence
motorcyclist’s acceptance of ARTS
 Motorcyclist–centred design recommendation
fro ARTS in Taiwan
6. Expected Outcomes
 Public transport systems based on the use of a fleet of
communication-enabled cybercars – road vehicles with
automated driving capabilities.
 Advantages
 Provide “Last-mile connections” for individuals
 Low personnel costs (No drivers)
 Sustainable urban transport
 Existing Cases
1. What is Automated Road Transport
Systems (ARTS)?
ARTS in the West Region of
Lausanne, Switzerland
ARTS in La Rochelle, France
Key References
CityMobil (2015), http://www.citymobil-project.eu/. CityMobil2 (2015), http://www.citymobil2.eu/
Directorate General of Highways, Ministry of Transportation and Communications, Taiwan (R.O.C.) (2014), Annual Report for Motor Vehicle Administration.
Rockall, Wil, 2014, Can driverless car see off cyber attacks? [Online] London, United Kingdom. http://goo.gl/oFQZNg
Reason, Manstead, Stradling, Baxter & Campbell (1990), Errors and violations on the roads: a real distinction? http://goo.gl/ZMzgVX
 Understand motorcyclists’ initial acceptance of ARTS in
Taiwan
 Find out what will increase motorcyclists’ acceptance and
confidence of ARTS when assessing them, in:
 Safety systems on ARTS
 Road infrastructure
5. Objectives
Can ARTS be a solution?

ROLE OF PRIVATE FINANCE IN AIRPORT DEVELOPMENT
NAME: SAMUEL APPIAH ADJEI
EMAIL: ts14saa@leeds.ac.uk INDEX: 200872578
SUPERVISOR: PROF. NIGEL SMITH
BACKGROUND AIM METHODOLOGY
1. The fundamental change in the airport industry
occurred after the 1986 Airports Act which was to
introduce the privatization and commercialization
into the aviation sector
2. There exist different ownership models after
the introduction of Airport Act
3. Most airports in the UK has experienced
different ownership types over the years
4. Some of the ownership types include purely
public airport, public private partnership and
purely private ownership
5. Research would undertake time series analysis
of effects of ownership change on airports
passenger trends
Subhead
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ex estie vent ad molesto diat.
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ex.
This research primarily examines the impact
of airport ownership type on airport
efficiency
1. Analyse airport passenger trends
between 2000 and 2014
2. Analyse airport freight trends between
2000 and 2014
3.Identify impact of airport ownership type
on passenger trends
4. Identify measures to improving airport
passenger and freight growth
Leeds Bradford Airport
FURTHER WORK
1. Study effects of various airport services
on passenger numbers
2. Evaluate private finance on airport
development
1. The fundamental change in the airport
industry occurred after the 1986 Airports Act
which was to introduce the privatization and
commercialization into the aviation sector
2. There exist different ownership models after
the introduction of Airport Act
3. Most airports in the UK has experienced
different ownership types over the years
4. Some of the ownership types include purely
public airport, public private partnership and
purely private ownership
5. Research would undertake time series analysis
of effects of ownership change on airports
passenger trends
UK AIRPORT UK OWNERSHIP
PRIVATIZED
AIRPORTS
PUBLIC
PRIVATE
PARTNERSHIP
PUBLIC
AIRPORTS
OBJECTIVES
CASE STUDY
TIME SERIES ANALYSIS
PASSENGER TRENDS FREIGHT TRENDS
DATA COLLECTION
AIRPORT ANNUAL REPORT CIVIL AVIATION AUTHORITY
CASE STUDY APPROACH
LEEDS BRADFORD AIRPORT
Public
Airport
2000-2007
Privatized
2007 to
Date
REFERENCES
Butcher L. (2014), Aviation: Regional Airports House of Commons,
House of Commons Library
Oxford Economics (2011) Economic benefits of air transport in the UK
Yin, R. K. (2014) Case Study Research. 5th Edition. California. Sage
Publications Inc.

Traffic flows thresholds for Shared Space in Leeds
Transport Planning and Engineering. Student: Russell Oakes Supervisor: Dr James Tate
Introduction
Shared Space is a concept where streets are re-engineered to reduce the
dominance of motor vehicles (DfT, 2014) Street signage is limited and kerb heights
are reduced or removed completely in some cases.
The focus for this project will be in Headingley, North West Leeds. Pedestrian
desire lines vary due to the mixture of retail and leisure activities this district has to
offer; therefore providing an ideal location to test the theory.
Literature
The dissertation will be educated by various sources of literature, including...
Manual for Streets (1 & 2), Liverpool City Centre Plan (1961), Living Streets
Policy, Local Authority Policy (for example Leeds City Council Supplementary
Planning Documents), University of the West of England Research, Written
interview with the late Hans Monderman and scheme studies.
Objectives
To ascertain the potential for bringing Shared Space to Headingley by:
Understanding previous comparable Shared Space Schemes
Compiling a resource containing pedestrian and vehicular data
Applying the data to a Micro-simulation Package (Aimsun & Legion) with
sensitivity tests
Analysing the Aimsun & Legion outputs
Determining applicability to Headingley and wider Leeds
These objectives will act as milestones throughout the dissertation with the
expectation that each objective will be a development on its predecessor.
Methodology
The project will require site visits to various
contrasting examples, compilation of pedestrian
data from Leeds City Council and a suitable
model simulation running to satisfy the scope of
the project.
Anticipated issues include the inability to
compile pedestrian data for the Headingley
area, therefore flexibility with pilot site locations
may be required.
Two preliminary pilot sites of contrasting traffic
density will be used in order to determine the
relative scales of operation for a Shared Space
scheme. Currently, these sites are North Lane/
Otley Road and St Michaels Road outside the
Church.
Coventry Top: Before. Source: Oakes, R (2010) Bottom: After. Source: Oakes, R (2015)
Preston
De-cluttering of street furniture including
the removal of traffic lights
Narrowing of Fishergate providing wider
pavements
Provision of informal pedestrian crossings
Top: Before. Source: Oakes, R (2013) Bottom: After. Source:
Oakes, R (2015)
UrbanCaseStudies
Top: Before. Source: Oakes, R (2010) Bottom: After. Source:
Oakes, R (2015)
Downgraded routes complimented by
extensive landscaping
Closure of through routes and
implementation of UKs largest 20mph zone
(Coventry City Council, 2010)
Mixture of zebra and informal crossings
Coventry
Top: St Michaels Road. Source: Oakes, R (2015)
Bottom: Otley Road/North Lane. Source: Oakes, R (2015)
Sources used in the dissertation will include:
Early Indications and
Potential Outcomes
No Shared Space scheme is identical, as
demonstrated with the case studies. Therefore, the
site visits will assist in the appreciation of the issues
apparent in Headingley.
An understanding of which environments would
best suit a Shared Space scheme with the potential
to apply the key findings of this project to policy
making within Leeds City Council.
Communities are aware of the Shared Space
concept and have approached Leeds City Council
requesting that this is investigated.
If the timescales fit, efforts will be made to draw
comparisons where relevant to other Shared Space
schemes. This may lead to good practice workings
with other Local Authorities subject to interest.
Sources of Information
The dissertation will call upon quantitative and qualitative sources in order to provide a
robust analysis. This could include:
Quantitative
Leeds City Council Transport Monitoring Database
Primary data collection (where required)
Scheme monitoring reports
(where available)
Qualitative
City and County Borough of Liverpool 1965, Liverpool City Centre Plan,
Liverpool, City and County Borough of Liverpool
Moody, S. and Melia, S. (2014) Shared space: Research, policy and
problems. Proceedings of the Institution of Civil Engineers - Transport, [Online]
Available at: http://www.icevirtuallibrary.com/content/article/10.1680/
tran.12.00047 (Accessed 23rd April 2015)

Meta-analysis of electric vehicles’ range prediction
EU in attempt to invest in innovation in Europe and also to improve the life quality of the
union’s citizens, introduced the programme “HORIZON 2020” for 2014-15; where one of the
main goals is “smart, green and integrated transport”. A key topic of this programme is the
improvement of “green” electric vehicles’ technology and charging infrastructure; in an
attempt to make electric vehicles (EV) prevail in the vehicle market, as a “cleaner” technology,
improving urban air-quality, and also to improve the driving experience of EV drivers.
According to the last, this report aim to investigate the prediction of the driving range of EV;
which is connected with the real-time information (digital support) for EV drivers for better
trip planning and access to charging facilities.
The main objective of this research is to
investigate the parameters that affect the driving
range of EV in real-life driving conditions, in
order to test and evaluate the accuracy of the
existing methods currently used for EV driving
range prediction. This aim to help drivers predict
the residual driving range of their vehicles in
order to improve their driving experience and
better estimate their trips.
(a) a smart grip giving information to the EV driver on when the next charge is required and the near available charging
facilities, through GPS positioning. This could be through a mobile application or on a pre-installed application on the
vehicle. (b) an example of application (“Next Charge”, android app) giving information to the driver about the available near
charging stations. (c) an application (“EV Range”, android app) for route planning by the driver; with inputs origin and
destination, vehicle model and passengers number, and outputs distance, time, consumption (Wh/km), percentage of the
battery capacity left (%), and driving range (km) for all possible routes.
• Develop the framework, the modelling of the motor’s required power based on travel ( i.e. distance, traffic conditions, slope, etc.), vehicle (i.e.
weight) and driver (i.e. aggressiveness, route choice etc.) related parameters and battery’s discharge rate validation based on the battery's
specifications: capacity, state of charge (SOC), current (I), voltage(V), etc.
• Investigate the applied and researched modelling methods (for both the motor and the battery) and related parameters
• Evaluate the validity and transferability of the methods and the findings regarding how the data where collected, by which conditions, the data
sample size, etc.
• Research transferable methodology from other studies that can be examine for EVs i.e. ICE vehicles fuel consumption and emissions factors
• Define the parameters into modelling factors and discuss limitations
• Make the a comparison of the methods and give the proposed method or combination and make proposals for improvements and further
research
M e t h o d o l o g y
Objective
Can driving range be predicted accurately? Which data are required? Is the
use of these models in real-life feasible?
P a r a m e t e r s
One of the most advanced features of an EV, compared to the conventional ICE vehicle is its ability to
regenerate electricity when decelerate through the regenerative braking system (RBS).
Power (KW)/ Acceleration (m/s2) Figure (c) and (d)
• For acceleration between -1.5 and 1.5 m/s2, the power proportionally increases with the increase of the
acceleration.
• For acceleration bellow -1.5 m/s2 or above 1.5 m/s2 the power remains almost the same and doesn’t change with
the acceleration.
• For both urban (in-city) driving and freeway driving, the power lies between -5 kW and 20 kW
• The lower bound is low because EV’s regeneration is limited by the battery pack’s ability to accept charge which is
controlled by the battery management system (BMS).
Power (KW)/ Roadway gradient (%) Figure (e) and (f) (Gradient information was collected from Google Earth)
• As the gradient is increasing the required power is increasing too.
• The change in power is significantly larger when the grade is positive
• For urban (in-city) driving, the change in power is 20 kW (5 - 25 kW) when the grade changes from 0 to 6%; but
when the grade changes from -6 to 0% the power increases only 5 kW (0 - 5 kW)
• For the freeway driving, the needed power changes from 12 to 32 kW (20 kW difference) when the grade changes
from 0 to 6%; but when the grade changes from -6 to 0% the power increases only 7 kW (5- 12 kW).
• For the same gradient the freeway driving requires more power than urban driving probable due to higher speeds.
The huge potential benefits of EVs have already attracted
significant interest and investment in EV technology. Since
2010 more than 20 manufactures introduced EVs.
(a) (b) (c)
Reference: Wu, X., Freese, D., Cabrera, A., & Kitch, W. (2015). Electric vehicles' energy consumption measurement and
estimation. Elsevier, Transport Research Part D, 52-67.
Collection of traffic condition
and road type data
Categorisation of road-
type and congestion level
collect vehicle response to traffic and road
conditions
Simulate vehicle response to
traffic and road conditions
Model development
1. Single vehicle driving
cycle
2. Multiple vehicles driving
cycle
1. Road type
2. Speed
3. Speed/stops-starts
4. Speed/ acceleration-
deceleration
5. LOS
1. Data logger on EV & GPS positioning
(road-information from interactive
maps)
2. Data logger on non-EV vehicle(s)
3. Data logger on non-EV vehicle(s) & GPS
positioning
4. Aggregate average data (pre-developed
driving cycle used)
1. Neural Network
2. Simple statistical analysis
1. Data analysis based algorithms
2. Data analysis based & physic based
approach algorithms
3. Physic based approach algorithms,
static model (use data for
validation)
3. Dynamometer driving
schedule
1. Speed
2. Speed/stops-starts
3. Speed/ acceleration-
deceleration
1. Data logger on EV
2. Data logger non-EV vehicle
3. Aggregate average data (pre-developed
driving cycle used)
1. Statistical analysis 1. Data analysis based algorithms
2. Physic based approach algorithms,
static model (use data for
validation)
4. Derive from traffic model 1. Road type-traffic model 1. Aggregate average data 1. Statistical analysis 1. Data analysis based & physic based
approach algorithms
F r a m e w o r k o f p u b l i s h e d E V r a n g e p r e d i c t i n g m e t h o d s

Who spend what on the High Street? A comparison of the importance of non-car access between city
centre and local shops areas. Institute for Transport Studies, University of Leeds, UK.
RESEARCH QUESTION
(sustrans, 2006)
55% 22% (4'.•"'10% (6cq13% (1 1 %)
Actual mode of customer travel
(Shopkeepers estimates in brackets)
Shoppers' choice of travel modes in Bristol study
rivers limit the range of
compact urban centre, flat
ervice.
One of the best Park and Ride
QUESTIONS & OBJECTIVES
Which are the accessibility patterns in the city centre and
local shops areas?
Have they an implication in shops turnover?
To determinate if retailers perception about their customer mode
of access is accurate, in order to promote a better understanding of
transport and land-use policies.
CITY OF YORK
Advantages for sustainable modes:
geography and good public transport s
Foot street historical and retail centre.
schemes in the UK.
Disadvantages: Historical walls and
interventions.
METHODOLOGY
1) Literature review of economic, planning and transport
approaches to High Streets in U.K. and previous academic and "grey"
studies.
2)Questionnaires designing based on previous studies and
amendments for accuracy to City of York
RISK
Data collection task may take more time than expected.
Get retailers answers while they are working.
Fail in achieving the proposed sample size.
Lack of support from York City Council
CONTEXT
"Local areas should implement free controlled parking schemes..."
"Cars are an intrinsic part of the way many people shop..."
Worths Report,2011,p.5 and p.271
"There is not such thing as "free" parking"
(Tyler et a1,2012,p.651
"The literature on parking and retail divides into two groups: those
suggesting that parking is important for retail activity and those arguing
that retailers have a wrong perception about the modal split of their
customer and usually overestimate car use for shopping"
IMingrado,2012,p1951
3)Data will be collected by different methods with the aim of
accumulating as many answers as possible: face to face, mail drop and
email questionnaires.
4. Analysis: data analysis, interpretations and comparison with other
results from UK and overseas.
1. Conclusion: Findings of the work. Answers to the research questions
and implication for the city of York.
REFERENCES
s,M. (2011). The Portas Review. An independent review into the future of our Highs Streets. [ONLINE].
[Accessed 29 February 2015]. Available from: https://www.gov.uk/government/uploads/system/up-
loadsiattachment_dataifile/6292/2081646.pdf Sustrans. (2006). Real and Perceived travel behaviour in
neighbourhood shopping areas in Bristol. Bristol: Sustrans.
Tyler, S., Semper, G., Guest, P., & Fieldhouse, B. (2012). The relevance of parking in the
success of urban centres, A review for London Councils.
UNIVERSITY OF LEEDS
DATA
Desirable sample size:
Consumers centre(n=200)
Consumer local( n= 100);
Retailers centre(n= 50)
Retailers local(n=25).
QUESTION EXAMPLES
"How often and by which means do
you shop"?
"How often and by which means
do you think your customers
shop?"
Poster Presentation: 01 May 2015. Student: Pedro Scarpinelli . Dissertation Tutor: Professor Greg Marsden. Institute for Transport Studies, University of Leeds

Evaluating the efficiency of Network Aggregation in providing accurate results, using SATURN
software. A case study of the Lendal bridge closure in York City.Panagiotis Anastasiadis
Dr. David Milne (Supervisor), Prof. David Watling (2nd reader)
I. Understand the patterns and unique characteristics of York’s
network
II. Investigate suitable approaches to network simplification
III. Define and describe step by step a network simplification
method, which best represents the effects of the traffic.
IV. Identify the ideal level of simplification to provide adequately
accurate results that help in evaluating transport policies.
3. Case study
Lendal bridge closure trial for cars, lorries and motorbikes (10:30-17:00).
Start date: 27 August 2013
End date: 26 February 2014
5. Methodology (Link extraction proposed methods)
4. Objectives
I)
II)

Masters Dissertation Posters 2015

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