Index
Safe Mobility: Challenges, Methodology and Solutions
ISBN: 978-1-78635-224-8, eISBN: 978-1-78635-223-1
ISSN: 2044-9941
Publication date: 18 April 2018
This content is currently only available as a PDF
Citation
(2018), "Index", Lord, D. and Washington, S. (Ed.) Safe Mobility: Challenges, Methodology and Solutions (Transport and Sustainability, Vol. 11), Emerald Publishing Limited, Leeds, pp. 459-478. https://doi.org/10.1108/S2044-994120180000011025
Publisher
:Emerald Publishing Limited
Copyright © 2018 Emerald Publishing Limited
INDEX
Index
Note: Page numbers followed by “f” and “t” refer to figures and tables.
AAAFTS survey
, 39
AADT.
, See Average annual daily traffic (AADT)
AASHTO Roadside Design Guide,
, 219
Attentional ‘pool’ theory
, 61
Abbreviated injury scale (AIS)
, 328
Access features
, 91–92
Access management
, 96–97
Accidents
property-damage-only
, 433f
time to accident (TTA)
, 391
transport
, 287
Actibump
, 219
ADT.
, See Average daily traffic (ADT)
Advertising billboards
, 64
Aetiology of traffic conflicts
, 388–390, 389f
Age
crash severity
, 330t
driver licensing
, 15
and driving experience
, 65–66
Aggressive behaviour, driver
, 38
Aggressive driver
, 40, 50
Aggressive driving
, 38, 41
behaviours
, 51
defined
, 39–40
domain of avoiding
, 48
enforcement programs
, 50–51
intentionally
, 40
and managing speed
, 47–51
moderating
, 47
AIC.
, See Akaike Information Criterion (AIC)
Airbags
, 5
Airproxes
, 290–293, 291f
Airspace safety, GLARMA models application to
, 289–293, 291f
AIS.
, See Abbreviated injury scale (AIS)
Akaike Information Criterion (AIC)
, 341, 342t
Alcohol
, 4
drinking
, 17
use, crash severity
, 330t
Alternate discrete variable model
, 342
Ancestry method
, 429
Annual average daily traffic (AADT), Sweden
, 213
Anti-aggressive driving strategy applications
, 50–51
Antidepressant drugs
, 428f, 437f, 437t, 438, 438f, 440, 441f, 442f
Anti-lock brakes
, 5
ARCH.
, See Autoregressive Conditional Heterskedasticity (ARCH)
ARIMA models
, 282, 283
time-series model
, 282
Arterial road segments
, 88
Artificial intelligence (AI) field
, 188
ASE.
, See Automated speed enforcement (ASE)
Attention
driver-cursory
, 60
driver-diverted
, 60
driver-misprioritised
, 60
driver-neglected
, 60
driver-restricted
, 60
visual
, 71
Auditory–vocal vs. visual–manual
, 67
Australia
crash rate
, 41–42
intersection crashes in
, 128
Authority, transport
, 234
Automated enforcement technology
, 49
Automated speed enforcement (ASE)
cameras
, 44
strategy
, 44
supporters
, 44
Automated vehicles, driver distraction
, 72–74
Automatic traffic detection system
, 177
Automatic vehicle identification (AVI)
, 179
Autoregressive Conditional Heterskedasticity (ARCH)
, 286
Autoregressive integrated moving average (ARIMA)
, 281, 288
Average annual daily traffic (AADT)
, 360
Average daily traffic (ADT)
, 90
AVI.
, See Automatic vehicle identification (AVI)
Awareness, situational
, 73
BAC.
, See Blood-alcohol-content (BAC)
Bayesian analysis
, 329, 367
Bayesian approach
, 357
Bayesian belief network (BBN)
, 188
Bayesian estimation
, 363, 364
Bayesian Information Criterion (BIC)
, 341, 342t
Bayesian method
, 367
Bayesian model
, 186, 367
Bayes’ theorem
, 363
BBN.
, See Bayesian belief network (BBN)
Before–after evaluations, robustness of
assessing similarity
in characteristics
, 421
in trends
, 420–421
reference/comparison group sample
, 420
separating treatment and reference/comparison sites
, 421–423
treatment group sample
, 419–420
Before–after study
, 411
FB approach to
, 418
observational
, 418
SPFs in EB
, 418
Behaviour
aggressive driving
, 51
based surrogate measures of safety
, 401
Behavioural measurement
, 397–399
as surrogate measures of safety
, 398f
Benzodiazepines
, 440f
Bernoulli trials
, 302
BIC.
, See Bayesian Information Criterion (BIC)
Bicycling, infrastructure for
, 231
Bicyclists
, 4, 5, 7, 8
directional signage for
, 242–243, 243f, 244f
hierarchy of options in providing for
, 233–234
Bikeshare programs
, 245–247
Billboards, driver distraction from
, 63–65
Blackspot
, 354–356
Blackspot identification (BSI)
, 353–354, 356
accounting for unobserved spatial effects
, 369–370
approach
, 356–360, 359f
continuous risk profile approach
, 370–371
empirical Bayesian approach
, 365–367
evaluation criteria
, 371–372
false identification test
, 372–373
method consistency test
, 373
Poisson mean differences test
, 374
site consistency test
, 373
total rank differences test
, 374
future directions
, 375–378
Naïve classical approach
, 360–361
safety performance functions
, 361–364
severity-based approach
, 368–369
Blood-alcohol-content (BAC) level
, 46, 47
Bluetooth
, 179
Braking capability
, 331t
BSI.
, See Blackspot identification (BSI)
Bumper height
, 331t
Camera radar
, 49
Checkpoints program, in United States
, 19
Clustering techniques
, 376
CMF Development Guidebook
, 410, 411, 418
CMFs.
, See Crash modification factors (CMFs)
Cochrane collaboration
, 429–430
CO2 emissions
, 230
Colorado
state patrol
, 51
Two Seconds for Safety campaign,
, 51
Co-mingling of mobility modes
, 5
Computer simulation of safety
, 399–400
Conflict–collision relationship
, 394–397, 395t
Connected vehicles
, 49
Context
before–after evaluations in
, 411
purpose of before–after evaluations
, 411
Continuous risk profile (CRP) approach
, 356–358, 370, 371f
Conway–Maxwell–Poisson model
, 261
Count-data models
, 261, 262, 266, 267
Crash(es).
, See also specific types of crash
classification
, 301–302
estimation methodology
, 94
in freeways
, 119
high-severity
, 115
with less severe injuries
, 274
likelihood of
, 258–259
precursor events
, 6, 454
prediction
model, Europe
, 123
real-time
, 6, 454
proximity measurement
, 390–392
rear-end and sideswipe
, 137
risk on urban and suburban arterials, measurement
, 88–89
road
, (see Road crash)
on road segments
, 88
severity
, 9
traffic conflicts and
, 388–390
under-reporting of
, 304, 339
in United States
, 38, 128
Crash-contributing factor
, 89, 101, 188, 355
Crash data
, 179–180, 180f, 384
characteristics
, 300–301
cross-sectional, explicitly addressing temporal considerations in
, 270–271
time-series methods for assessing
, 9
Crash frequency
data
analysis
, 259–263
continuous and duration approach
, 262–263
and severity
, 95
speed and
, 92
Crash-injury severity data analysis
, 264–265
Crash likelihood
, 186, 189, 194–196
Crash modification factors (CMFs)
, 113, 116, 117, 122, 411, 414
Crash modification function (CMFunction)
, 411
Crash-prone conditions
, 188
Crash rates
, 262
for males and females
, 46
Crash risk
, 355, 453, 457
in-vehicle
, 456
Crash severity
, 88, 95, 327
abbreviated injury scale
, 328
analysis
, 267
factors associated with
environmental and road factors
, 332, 332t
Haddon Matrix
, 329, 330t
human factors
, 329–330, 330t
vehicle/equipment factors
, 331–332, 331t
KABCO scale
, 327
Markov-switching multinomial logit model of
, 271
modelling
alternative model formulations
, 337–339
examples
, 339–345, 340t, 341f, 343t, 344t, 346t
nominal outcome models
, 335–337
ordered outcome models
, 333–335
ordered versus un-ordered severity outcomes
, 333
partial PO model for
, 339–342
prediction modelling
, 347
road
, 346
vehicle damage
, 328–329
Cross-sectional crash data
explicitly addressing temporal considerations in
, 270–271
spatial and temporal considerations in
, 269–270
Cross-sectional modelling methodology
, 258, 259
Crosswalks, pedestrians
, 209, 215–217, 220f, 221f, 222f, 224, 226
Cycling
, 230, See also Off-road cycling infrastructure; On-road cycling infrastructure
on footpath
, 241–242, 241f
participation rates
, 232–233
recreational
, 232, 248
transport
, 248
Cyclists
, 4, 5, 7, 8, 241f
categories
, 232
end-of-trip facilities for
, 243–245, 246f, 247f
facilities for
, 170
recreational
, 232, 243
traffic safety of
, 98–99
transport
, 232
utility
, 232
Data
aggregation and combination
, 181–182
collection stations
, 182f
crash data
, 179–180, 180f
geometric and weather data
, 181
real-time traffic data
, 178–179, 181
Data mining
, 186, 376
Daylight
, 135
Death, injuries and
, 457
DeKalb County study
, 23
Detectors
in-roadway
, 178
loop
, 178
Deviance information criterion (DIC)
, 316
Directional signage, for bicyclists
, 242–243, 243f, 244f
Discrete-modelling frameworks
, 265
Discrete outcome models
, 264
Distraction
driver
, (see Driver distraction)
visual
, 69
Double-roundabouts
, 159–160, 160f
Drinking alcohol
, 17
Driver(s).
, See also specific types of driver
aggressive
, 38, 40
behaviour
, 6–7, 19–20, 453, 457
characteristics
, 65–66
drunk
, 46–47
errors
, 38
expectations
, 112
hands-free mobile phone devices usage
, 18
hazard perception test
, 20–21
monotonous for
, 73
night-driving restrictions
, 17
novice
, 19, 22, 25
older
, 18
provisional
, 21
to reduce stress
, 48
risk perception
, 398
secondary task demand
, 67
self-regulation
, 67–68
speeding behaviour
, 43
time reduction and
, 22
visual behaviour
, 64
young
, 15, 16, 18, 44
Driver-cursory attention
, 60
Driver distraction
, 7
activities and associated ORs
, 70t
from billboards and roadside advertising
, 63–65
countermeasures and mitigation of
, 74–76
defined
, 59
vs. driver inattention,
, 61
driving performance and safety
, 68–72
education and training
, 74–75
in highly automated vehicles
, 72–74
human factors
, 74
human–machine interface
, 75–76
moderators of
, 65–68
sources of
, 62–65
theories of
, 61–62
Driver-diverted attention
, 60
driving-related
, 60
non-driving-related
, 60
Driver education
, 14, 22–25, 47–48
future challenge for
, 28–29
hazard perception skills training and education
, 25
insight training
, 25
post-licence education
, 24
pre-licence training
, 23
procedural skills training
, 24–25
resilience training
, 23–24
school-based driver training
, 23
Driver Fatigue and Distraction Monitoring and Warning System
, 120
Driver inattention
, 74
defined
, 59
vs. driver distraction
, 61
mechanisms of
, 60
taxonomy of
, 59–60
theories of
, 61–62
Driverless vehicles
, 456
Driver licensing
, 14–15, 29
age
, 15
changes on unlicensed driving
, 21
compliance and enforcement
, 19–20
driver testing
, 20–21
graduated
, (see Graduated driver licensing (GDL))
learner licence
, 16–17
monitoring the impact of
, 21
novice
, 15
provisional/intermediate licence
, 17–18
role of parents
, 18–19
Driver-misprioritised attention
, 60
Driver-neglected attention
, 60
Driver-restricted attention
, 60
Driver safety
, 398
vs. security
, 4–5
Driver testing
, 20–21
Driver training
, 22
future challenge for
, 28–29
hazard perception skills training and education
, 25
insight training
, 25
part-task training
, 25
pre-licence training
, 23
procedural skills training
, 24–25
resilience training
, 23–24
school-based
, 23
Driver workload, reduction in
, 72–73
Driving.
, See also specific types of driving
aggressive
, (see Aggressive driving)
contexts
, 42–44
experience, age
, 65–66
instructors
, 26, 27
night-driving restrictions
, 17
performance and safety
, 68–72
professional
, 16
rural
, 43
speed
, 331t
supervised
, 16
Driving simulators
, 25–26
driving testing
, 28
in education
, 26–28
Driving task
complexity of
, 3–4
demand
, 66–67
Driving testing
, 28
Driving under the influence (DUI)
, 40, 46–47
arrests and safety messages
, 51
Drugs
, 4
antidepressant
, 428f, 437f, 437t, 438, 438f, 440, 441f, 442f
Drunk drivers
, 46–47
DUI.
, See Driving under the influence (DUI)
Duration-model approach
, 263
Dynamic stability control
, 5
EB.
, See Empirical Bayes (EB)
Education, driver.
, See Driver education
Electronic billboards
, 65
Empirical Bayes (EB)
approach
, 356, 357, 365, 372
before–after evaluation
, 412
mathematics essentials
, 412–415
estimator
, 365, 366
methodology
, 412, 417
Empirical Bayesian approach
, 365–367
End-of-trip facilities, for cyclists
, 243–245, 246f, 247f
Endogeneity
, 273–274
Engineering
roadway and vehicle design
, 48–49
transport system for humans
, 4
Environmental factors, crash severity
, 332, 332t
EPDO.
, See Equivalent property damage only (EPDO)
Equivalent property damage only (EPDO)
, 357, 368, 369, 374
EUROCONTROL
, 289, 292, 293
European countries, speed limit strategy
, 47
European crash prediction model
, 123
European Directive on road infrastructure safety management
, 109–112
European trans-national model
, 124
Excess zero responses
, 301–303
effects of
, 305–308
important omitted variables
, 305
sites characterised by low exposure and high risk
, 304–305, 305t
spatial and time scales
, 303–304, 304f
under-reporting of crashes
, 304
Explanatory variables, urban and suburban arterials
, 89, 93, 94
Exploratory meta-analysis
, 431–434
Expressways, in urban and rural areas
, 176
False identification test
, 372–373
False negatives (FNs)
, 372
False positives (FPs)
, 372
Fastest drivers
, 44
Fatality
, 328, 341
risk on motorways
, 108
safety impacts on
, 122, 123f
Federal Highway Administration (FHWA)
, 86–87, 215
Federal Motor Carrier Safety Administration (FMCSA), United States
, 120
Females, crash rates for
, 46
FHWA.
, See Federal Highway Administration (FHWA)
Fidelity
, 26
Field-of-view axiom/rule
, 118, 119f
First-order volatility model
, 286
FOCAL program.
, See Forward Concentration and Attention Learning (FOCAL) program
Footpath, cycling on
, 241–242, 241f
Forgiving roads
, 100
Forward Concentration and Attention Learning (FOCAL) program
, 27
France, splitter islands
, 155
Freeway
crashes in
, 119
design and speed consistency on
, 112–115
grade-separated interchange
, 110f
improve safety on existing
, 118–120
risk trends in Italy from 2001 to 2014
, 111f
vs. roads risk for different countries
, 108, 110f
section control signs in Italy
, 115f
in urban and rural areas
, 176
Freeway networks
, 108
safety assessment of
, 122–124
safety issue for
, 115
Freeway safety
, 113, 198
future research directions in
, 124
ITS and
, 120–122
Freeway segment
, 109f
highway safety manual model for
, 113, 117
Full Bayes (FB) approach
, 418–419
GADGET matrix
, 22
Gaussian distribution
, 282, 283
GDL.
, See Graduated driver licensing (GDL)
GDP.
, See Gross domestic product (GDP)
Gender role, speed
, 44–46
Generalised linear model (GLM)
, 287, 310, 313
Generalised ordered logit (GOL)
, 337–338, 344
Geographic information system (GIS) tools
, 357
Geometric data
, 181
Geometric design
central island
, 160–161
circulatory roadway width
, 163
entry angle
, 162–163
entry radius
, 162
entry width
, 161–162
exit radius
, 164
exit width
, 163
Germany, human factors design mistake and crashes
, 120t
GLARMA models
, 286–289, 294
application to airspace safety
, 289–293, 291f
GLM.
, See Generalised linear model (GLM)
Global positioning system (GPS)
, 47, 179
warnings
, 44
Global society, health burden on
, 3
Goals for Driver Education framework
, 22
GOL.
, See Generalised ordered logit (GOL)
Governors Highway Safety Association
, 111
GPS.
, See Global positioning system (GPS)
Graduated driver licensing (GDL)
, 15, 17, 22
effectiveness of
, 21
laws
, 20
parental involvement in
, 18–19
programs
, 7
Great Britain’s Automobile Association (1995)
, 39
Green Book
, 214, 215
Gross domestic product (GDP)
, 2
Haddon Matrix
, 329, 330t
Handbook of road safety measures,
, 99
Hands-free mobile phone devices, usage for drivers
, 18
Hauer’s method
, 419
Hazard-based models
, 263
Hazard perception
, 26
skills
, 26
training and education
, 25
test, driver
, 20–21
training
, 25, 26
Head rotation-monitoring system
, 76
Health burden, on global societies
, 3
Heterogeneity
, 442
unobserved
, 265–268
High-fidelity simulators
, 26
High-friction wearing course
, 117, 117f
Highly automated vehicles, driver distraction in
, 72–74
Highly dispersed data
, 299, 306, 308, 316
High-risk crash locations detection
, 354
High-severity crashes
, 115
High-speed highways
, 4
High speed roads, speed limit on
, 42, 42t
Highway Capacity Manual (HCM)
, 151
Highway, high-speed
, 4
Highway–railway crossings
, 339
Highway Safety Manual (HSM)
, 95–96, 116, 120, 123
model for freeway segments
, 113, 117
Hotspots
, 353, 354, 358, 368
How to Live Dangerously (Cairns),
, 211
HSM.
, See Highway Safety Manual (HSM)
Human, engineering transport system for
, 4
Human errors
, 100
Human factors
, 74
crash severity
, 329–330, 330t
design mistakes, Germany
, 120t
driver distraction
, 74
improve safety on existing freeways
, 118–120
related crashes
, 118
Human–machine interface, ergonomically designed
, 75–76
ICD.
, See Inscribed circle diameter (ICD)
Illegal drugs
, 4
Inattention.
, See Driver inattention
Injury
and deaths
, 457
reducing
, 3
Injury severity
models
, 267, 345
multinomial logit model of
, 268
Injury Severity Score (ISS)
, 328
In-roadway detectors
, 178
In-roadway sensor
, 178
Inscribed circle diameter (ICD)
, 153
Integer-valued autoregressive (INAR) Poisson models
, 283
Intelligent transportation system (ITS)
, 125, 177
and freeway safety
, 120–122
traffic detection system
, 178
Intermediate licence
, 17–18
Intersection crash
, 128, 140–141
analysis
, 129–130
frequency
, 131t
likelihood and frequency
, 130–135
rural
, 133–135, 134t
urban
, 131–133, 132t
safety of
, 129
severity
, 135–137
rural
, 138t, 139
urban
, 137–139, 138t
Intersection density
, 91–92
Intersection safety, roundabouts improvement
, 148
In-vehicle crash risk
, 456
In-vehicle method
, 393
Inverse-variance
meta-analysis
, 435
technique
, 430
ISS.
, See Injury Severity Score (ISS)
Italy
freeway risk trends in Italy from 2001 to 2014
, 111
freeway section control signs in
, 115f
freeway system
, 114
speed diagram
, 112, 113
ITS.
, See Intelligent transportation system (ITS)
Just-in-time crash prediction
, 375
KABCO
scale
, 327
severity
, 327
Kernel density estimation
, 357, 369
Lane Departure Warning system
, 124
Lane width
, 93–94
Latent class models
, 268
Learner licence
, 16–17
Licensing, driver.
, See Driver licensing
Lidar detector
, 49
Likelihood ratio test
, 269
Lindley distribution
, 311
Linear regression
, 333
Local environment factor
, 129
Logic axiom/rule
, 118
Logistic models
matched case-control
, 186
regression models
, 184
Loop detectors
, 178
Macro-environmental factors
, 129, 141
MAIS.
, See Maximum AIS (MAIS)
MAIS scale
, 346
Males
crash rates for
, 46
testosterone levels
, 46
Markov Chain Monte Carlo (MCMC) sampling
, 363, 364
Markov-switching model
, 270, 271
Matched case-control logistic model
, 186
Maximum AIS (MAIS)
, 328
Maximum likelihood estimation (MLE)
, 363
MCMC.
, See Markov Chain Monte Carlo (MCMC) sampling
Mean Absolute Deviance (MAD)
, 316
Mean Predicted Square Error (MPSE)
, 316
Meta-analysis
, 426
controversies in
, 441–442
exploratory
, 431–434
inverse-variance
, 435
main analysis
, 434–438
methods
, 10
performing
, 427–428
pitfalls and research needs
, 441–445
preparing for
, 428–431
sensitivity analysis
, 439–441
Microsimulation tools
, 152
Mini-roundabouts
, 153, 154t
Mitigation strategy
, 75
Mixed generalised ordered logit (MGOL)
, 344, 345
Mixed-logit model
, 267
Mixed-model formulations
, 336
Mixed multinomial logit model (MMNL)
, 344, 345
MLE.
, See Maximum likelihood estimation (MLE)
MNL.
, See Multinomial logit model (MNL)
MNP.
, See Multinomial probit model (MNP)
Mobile phone
, 179
ban
, 18
Mobility
in developing countries
, 458
modes, co-mingling
, 5
Model estimation concerns
, 271
correlation of observations
, 272
irrelevant variables
, 272–273
methodological approach
, 274–275
multicollinearity
, 273
non-linearities
, 273
omitted variables
, 272
selectivity-bias/endogeneity
, 273–274
under-reporting of crashes with less severe injuries
, 274
Modelling methods
, 184–188
Monotonous, for drivers
, 73
Motorcyclists
, 5
Motorised societies
, 14
Motorist
, 38, 49, 148, 176, 217–218, 220
Motor skills
, 16
Motor vehicle crashes
, 353
Motorway, fatality risk on
, 108
MRT.
, See Multiple Resource Theory (MRT)
Multicollinearity
, 273
Multi-lane roundabouts
, 157, 158t
Multilayer perceptron architecture
, 186–187
Multinomial logit model (MNL)
, 336, 344
of injury severities
, 268
Multinomial model
, 341, 342
Multinomial probability model
, 336–337
formulation
, 335
Multinomial probit model (MNP)
, 336
Multi-parameter analysis tools
, 318
Multi-parameter models
, 308–310, 318
application
comparing distributions
, 315
comparing models
, 316, 316t
negative binomial-crack model
, 313–315
negative binomial–generalised exponential model
, 312–313
negative binomial–Lindley model
, 310–312
Multiple Resource Theory (MRT)
, 61, 62
Naïve classical approach
, 360–361
National Cooperative Highway Research Program (NCHRP)
, 42, 315
National Road Safety Strategy
, 111
Naturalistic driving
, 394
experiments and data
, 457
study
, 58–59, 69–70
NB.
, See Negative binomial (NB)
NB-CR model.
, See Negative binomial-crack (NB-CR) model
NB-GE model.
, See Negative binomial–generalised exponential (NB-GE) model
NBINGARCH model
, 285, 289
NB-L model.
, See Negative Binomial–Lindley (NB-L) model
NCHRP Project
intersections
, 89–90
road segments
, 89
Near-crash events
, 387
Negative binomial (NB)
distribution
, 306, 306t
model
, 299, 303, 306
Negative binomial-crack (NB-CR) model
, 313–315
Negative binomial–generalised exponential (NB-GE) model
, 312–313
Negative Binomial–Lindley (NB-L) model
, 310–312
Nested logit (NL)
, 344
Network screening.
, See Blackspot identification (BSI)
Neural network models
, 186
Newton–Raphson algorithm
, 285
Newton’s laws of motion
, 92
NHTSA
, 49–50
aggressive driving defined by
, 39–40
safety statistics and survey
, 45
Night-driving restrictions
, 17
Nominal outcome model, crash severity
, 335–337
Non-crash case selection
, 182–184
Non-linearity
, 273
Non-linear optimisation technique
, 285
Non-renewable petroleum products
, 230
Non-visible injury
, 327
Norwegian drivers
, 16
Novice driver
, 19, 22, 25
licensing
, 15
training programmes for
, 75
Observation-driven model
, 287
Odds ratios (ORs)
, 70, 70t, 432
Off-road cycling infrastructure
, 237–239, 237f
cycling on footpath
, 241–242, 241f
shared bicycle paths
, 239–241, 240f
Off-roadway detection technology
, 178
Older driver
, 18
On-board technology
, 120
On-road cycling infrastructure
, 234
intersections: careful planning
, 236
marked bicycle lanes
, 235–236, 235f
On-road driving tests
, 20
Optical density
, 118
Ordered generalised extreme value logit (OGEV)
, 344
Ordered logit (OL) model
, 334
Ordered probability models
, 264
ORs.
, See Odds ratios (ORs)
Over-dispersion
, 301–303
Over-roadway sensor
, 179
Parameter-driven model
, 286
Parental involvement, in graduated driver licensing
, 18–19
PAR model.
, See Poisson autoregressive (PAR) model
Partial proportional odds (PPO)
, 342t, 343t, 344t
model
, 337–339
for crash severity
, 339–342, 340t, 341f
Pedestrian(s)
, 2, 4, 5, 7, 8, 453–456
absurdity of
, 216
crash severity
, 330t
crosswalks
, 209, 215–217, 220f, 221f, 222f, 224, 226
encouraging
, 217
fatalities
, 209
measurement of safety
, 211–212
safety for
, 208, 217
traffic safety
, 98–99, 209, 211
user groups
, 212
walking, benefits
, 210–211
Pedestrian facilities
, 169–170
across roadways
, 215–225, 216f
achieve low speeds
, 218–222, 219f, 220f, 221f, 222f
making pedestrians noticed
, 224, 224f
prioritising pedestrians
, 225
speeds and safety
, 222–223
along roadways
, 212–215, 215f
Performance check
deviation angle
, 166
entry path radius
, 165–166, 167f
radius of deflection
, 164–165
sight distance
, 168–169
speed control
, 164
PET.
, See Post-encroachment time (PET)
PFI.
, See Potential for improvement (PFI)
PIARC Guide
, 118, 119
Platooning vehicles
, 124
Poisson- and Poisson-Gamma-based GLARMA model estimation
, 291, 292t
Poisson autoregressive (PAR) model
, 284–285
Poisson distribution
, 283, 291, 306, 306t
Poisson-Gamma-based GLARMA models
, 290
Poisson-Gamma conditional distribution
, 291
Poisson-Gamma model
, 287
Poisson INAR model
, 283
Poisson mean differences test
, 374
Poisson model
, 261, 275, 283–284, 303
integer-valued autoregressive
, 283
Poisson regression
, 261
model
, 260
Post-encroachment time (PET)
, 390–392, 392f
Potential for improvement (PFI)
, 365–366
P-plates
, 18
PPO.
, See Partial proportional odds (PPO)
Precipitating events
, 387
Predictability of roads
, 100
Predictive variables, urban and suburban arterials
, 91, 94
Pre-driver
licensing curriculum
, 23
licensing group
, 23
Probe vehicle
, 179
Professional driving
, 16
Property-damage-only (PDO)
accidents
, 433f
crashes
, 301
Proportional odds (PO) assumption
, 335
Provisional drivers
, 21
Provisional licence
, 17–18
Psychological theory
, 61
Publication bias
, 439
Public bicycle hire programs
, 245
Pursuing robust model
, 364
Radar detector
, 49
Radio-connected vehicles
, 52
Random-effects model
, 435–436
Random-parameter models
, 267
Random-parameter multinomial logit model
, 274
Rate quality control (RQC)
, 356
Real-time crash-contributing factors
, 188
Real-time crash prediction
, 6, 179, 182, 188, 454
Real-time crash risk evaluation model
, 180
Real-time data, from crash, non-crash cases and pre-crash traffic conditions
, 184
Real-time traffic safety
, 189
analysis
, 184
and corresponding findings
, 188–189, 190t–190t
data
, 178–179, 181
applications
, 197–199
future studies
, 199–200
management
, 198
operation
, 197f
Rear-end collisions
, 88
Rear-end crashes
, 137
Recreational cycling
, 232, 248
Recreational cyclists
, 232, 243
Recreational riders
, 233
Recreational riding
, 248
Reduced Vertical Separation Minima (RVSM)
, 289, 290, 292
Regression-to-the-mean (RTM)
, 412, 417
effect
, 357, 361, 365, 371
Reshaping of cities
, 457–458
Restraint use, crash severity
, 330t
Riders
recreational
, 233
utilitarian
, 242
Riding, recreational
, 248
Rising congestion
, 38
Risk management
, 9
Risky events
, 388–391, 400
Road
classification in United Kingdom
, 87
design and conditions
, 129
factors, crash severity
, 332, 332t
forgiving
, 100
infrastructure, safety management
, 109–112
predictability of
, 100
self-explaining
, 100
surfaces, porous
, 443f
urban and suburban arterial
, 86
users
, 129, 453–454
Road crash
, 2, 98, 452–453
challenges in reducing
, 3
challenges in evaluating road safety
, 5–6
co-mingling of mobility modes
, 5
complexity of driving task
, 3–4
driver safety and security
, 4–5
engineering transport systems for humans
, 4
severity
, 346
on urban and suburban arterials
, 89–94
Road diet
, 97
Road rage
, 43
situations
, 39
Road safety
, 63, 64, 71, 76, 453, 454
challenges in evaluating
, 5–6
freeway
, 111–112
improving
, 3
managers
, 455
surrogate measures of
, 455–456
Road segments
, 89
arterial
, 88
crashes on
, 88
Roadside advertising, driver distraction from
, 63–65
Roadside Design Guide
, 215
Roadside observation techniques
, 394
Roadside safety
, 115–118
Roadway
characteristics and intersection crash frequency
, 131t, 132t–133t, 138t
design
, 48–49
factors
, 140
pedestrian facilities along
, 212–215
Roundabouts
, 148–149
classification
double-roundabouts
, 159–160, 160f
mini-roundabouts
, 153, 154t
multi-lane roundabouts
, 157, 158t
single-lane roundabouts
, 153–155, 155f, 156t, 157
turbo-roundabouts
, 157, 159
design process
, 150–153, 151f
warrant criteria
, 149–150
RQC.
, See Rate quality control (RQC)
RTM.
, See Regression-to-the-mean (RTM)
Rumble strips
, 117
Run-off-road crash severity
, 116
Rural areas
expressways in
, 176
freeways in
, 176
Rural driving
, 43
Rural intersection crash likelihood and frequency
, 133–135, 134t
RVSM.
, See Reduced Vertical Separation Minima (RVSM)
Safe driving
, 58
Safe mobility application
, 282–284
Safe Performance Curriculum
, 23
Safer Man–Road Interface
, 118
Safety.
, See also specific types of safety
analysis in developing countries
, 458
assessment of freeway networks
, 122–124
computer simulation of
, 399–400
concerns
, 86
countermeasures
, 95–96, 98–99
critical events
, 70–71, 74
effects, associated with 10 mph (16 km/hr)
, 42, 42t
expenditures, transport network
, 455
impacts on fatalities
, 122, 123f
measurement
, 211–212
restraints work
, 5
road
, (see Road safety)
speed and
, 92
surrogate measures of
, 9
transport system
, 455
tutor system
, 114
Safety managers
, 355
Safety performance functions (SPFs)
, 355–357, 361–364, 366, 368, 369, 412, 413
SAS SURVEYSE LECT procedure
, 342
SAVeRS project
, 124
SAVeRS tool.
, See Selection of Appropriate Vehicle Restraint Systems (SAVeRS) tool
School-based driver training
, 23
Seating position, crash severity
, 330t
Secondary task demand, driver
, 67
Security vs. driver safety
, 4–5
Segmentation, of transport networks
, 377
Selection of Appropriate Vehicle Restraint Systems (SAVeRS) tool
, 116–117
Selectivity-bias
, 273–274
Self-driving (autonomous) vehicles
, 52
Self-explaining roads
, 100
Self-regulation, driver
, 67–68
Sensitivity analysis
, 439–441
Sensor
automatic vehicle identification
, 179
in-roadway
, 178
over-roadway
, 179
Serial correlation
, 283, 291
SHRP2 program
, 394
Sichel (SI)
models
, 306, 307
simulation
, 308f, 309t
Sideswipe crashes
, 137
Sideswipe same direction collisions
, 88
Sidewalk
, 8, 213, 213f, 215
Sight distance
, 168–169
Simulation-based maximum likelihood method
, 267
Simulators
, 29
driving
, (see Driving simulators)
Single-lane roundabouts
, 153–155, 155f, 156t, 157
Single-vehicle fatal crash
, 315t
Site consistency test
, 373
Situational awareness
, 73
The 6-seconds axiom/rule
, 118
Snowfall effect
, 266
Societal impacts
and injury crashes
, 88
of road crashes
, 3
Societal risk
, 2, 9, 456, 457
Spatial and time scales
, 303–304, 304f
Speed
, 41–42, 51, 113
aggressive driving and managing
, 47–51
behaviour
, 43
cameras
, 49
consistency on freeways
, 112–115
control
, 152, 154, 160, 162, 164
and crash frequency
, 92
diagram, Italian design standard
, 112, 113f
drivers in fatal crashes by age and gender
, 45, 45f
humps
, 97
radio and laser detection
, 49
reduction programs
, 97
role of gender
, 44–46
and safety
, 92
pedestrians
, 222–223
selection
, 397–399
ties to demographic attributes and driving contexts
, 42–44
vehicle
, 92–93
of vehicles
, 49
Speed enforcement
, 113
at crosswalk
, 220, 221f
principle
, 114f
Speed governors
, 47
‘Speed Kills’
, 41
Speed limit
, 40, 87
European countries
, 47
on high speed roads
, 42, 42t
Speed limiter
, 44
Speedometers
, 44
Speed–safety relationship
, 398
Speed violation rates, United States
, 44
SPFs.
, See Safety performance functions (SPFs)
Splitter islands
, 154, 155
State-of-the-art
methodology
, 410
model
, 364
State-of-the-practice modelling of crash risk model
, 354
State-space model, for time-series
, 286
Stress, drivers to reduce
, 48
Suburban arterials
, 87
crash risk on
factors known to influence
, 89–94
measurement
, 88–89
design traits of
, 101
explanatory variables
, 89, 93, 94
facilities
, 88
predictive variables
, 91, 94
road
, 86
network
, 100–101
road safety on
methodological approaches used to eval uate
, 94–95
strategies for improving
, 95–100
traffic safety of pedestrians and cyclists on
, 98–99
Supervised driving
, 16
Support vector machine (SVM)
, 188
Surrogate measures of safety
, 385, 386
behavioural measurement as
, 398f
behaviour-based
, 401
road
, 455–456
Sustainable Mobility Project
, 327
Sustainable safety
, 99–100, 101–102
Sustainable transport
, 233, 239, 245, 246, 248
Sweden
annual average daily traffic (AADT)
, 213
crash rate
, 41–42
rural roads
, 212–213
Task demand
driving
, 66–67
secondary
, 67
Temporal transferability
, 269
TERN.
, See Trans European Road Network (TERN)
Testosterone levels
, 46, 52
Time- and weather-related factors
, 189
Time reduction, driver
, 22
Time-related factors
, 189
Time-series
datasets
disaggregated
, 293
highly aggregated
, 293
highly disaggregated
, 294
methods for assessing crash data
, 9
regression models
, 281
applications in safe mobility
, 282–284
GLARMA models
, 286–289
NBINGARCH models
, 285
Poisson autoregressive model
, 284–285
state-space model for
, 286
statistical model
, 281
Times to collision (TTC)
, 387, 389–391, 393, 400
Time to accident (TTA)
, 391
Tobit model
, 262
TomTom Go.
, 29
TomTom Sat Nav in Europe
, 29
Total rank differences test
, 374
Traditional crash-based method
, 385
Traditional models
, 299
Traditional non-count statistical method
, 262
Traditional police-reported crash data
, 269
Traditional regression models
, 308
Traditional safety analysis
, 177
Traffic
calming strategies
, 97, 101
congestion
, 38
control devices
, 170–171
factors
, 189
flow
, 149
parameters
, 179
law enforcement
, 49
truck
, 133–134
unsafety
, 88, 89
Traffic conflicts
aetiology of
, 388–390, 389f
and crashes
, 388–390
historical perspective of
, 386–388
observing
, 392–394
Traffic safety
, 77
analyses
, 129–130
of cyclists
, 98–99
of pedestrians
, 98–99
strategy
, 95
Traffic Safety Facts
, 176
Traffic volume
, 90–91
effect of , in crash severity
, 137–138
estimates of coefficients for
, 445t
Trans European Road Network (TERN) infrastructures
, 109–112
Transferability
, 269
Transport accidents
, 287
Transport authority
, 234
Transport cycling
, 248
Transport cyclists
, 232
Transport engineering, for humans
, 4
Transport network
, 454–456
management
, 452–453
safety-related expenditures
, 455
segmentation of
, 377
Transport system
, 7
locations
, 353
managers
, 354
safety
, 455
Truck apron
, 155, 163
Truck traffic
, 133–134
TTA.
, See Time to accident (TTA)
TTC.
, See Times to collision (TTC)
Two Seconds for Safety campaign,
, 51
United Kingdom (UK), roads classification in
, 87
United States (US)
checkpoints program in
, 19
crashes in
, 38
Federal Motor Carrier Safety Administration
, 120
intersection crashes in
, 128
Manual on Uniform Traffic Control Devices
, 220
Motor Vehicle Occupant Safety Surveys
, 45
road crashes
, 2
speed violation rates
, 44
Unlicensed driving
, 21
Unobserved heterogeneity
, 265–268
Urban areas
expressways in
, 176
freeways in
, 176
Urban arterials
crash risk on
factors known to influence
, 89–94
measurement
, 88–89
defined
, 86–87
design traits of
, 101
explanatory variables
, 89, 93, 94
facilities
, 88
predictive variables
, 91, 94
road
, 86
network
, 100–101
road safety on
, 94–95
methodological approach
, 94–95
strategies for improving
, 95–100
traffic safety of pedestrians and cyclists on
, 98–99
Urban intersection crash likelihood and frequency
, 131–133, 132t
Urban intersection crash severity
, 137–139, 138t
User groups, pedestrian
, 212
Utilitarian riders
, 242
Utility cyclists
, 232
Variable importance measure (VIM)
, 187
Variable speed limits (VSL) algorithm
, 198–199
‘Variance Kills’ theory
, 41
Vehicle(s).
, See also specific types of vehicle
connected
, 49
and crash factors
, 331–332, 331t
damage
, 328–329
design
, 48–49
driverless
, 456
failure
, 456
power restrictions
, 18
radio-connected
, 52
self-driving (autonomous)
, 52
speed of
, 49, 92–93
and traffic conditions
, 129
Vehicle crash
Haddon Matrix for
, 330t
research
, 258
Vehicle-to-infrastructure (V2I) interaction
, 120–121, 121f
Vehicle-to-vehicle (V2V)
functions
, 122
interaction
, 120–121
VIM.
, See Variable importance measure (VIM)
VISSIM
, 399
Visual attention
, 71
Visual behaviour, of drivers
, 64
Visual distraction
, 69
Visual–manual (VM)
vs. auditory–vocal
, 67
phone task
, 68
Visual scanning
, 26
VM.
, See Visual–manual (VM)
Volatility model, first-order
, 286
VSL.
, See Variable speed limits (VSL)
Vulnerable road-user group
, 8
Wald test of PO
, 340
Walking, benefits of
, 210–211
Warrant criteria
, 149–150
Weather conditions, effects of
, 196
Weather data
, 181
Weather-related factors
, 189
Wet pavements
, 196
Wet road surface
, 135
World Business Council for Sustainable Development (WBC)
, 327
You Hold the Key program,
, 24
Young driver
, 15, 16, 18, 44
Zhu’s model
, 285
- Prelims
- Chapter 1. Introduction
- Driver Behaviour: Challenges and Solutions
- Chapter 2. Driver Education and Licensing Programs
- Chapter 3. Aggressive Driving and Speeding
- Chapter 4. Driver Distraction and Inattention
- Transport Network: Challenges and Solutions
- Chapter 5. Urban and Suburban Arterials
- Chapter 6. Controlled Access Facilities (Freeways)
- Chapter 7. Rural and Urban Intersections
- Chapter 8. Roundabouts
- Chapter 9. Real-Time Traffic Safety and Operation
- Vulnerable Road Users: Challenges and Solutions
- Chapter 10. Providing for Pedestrians
- Chapter 11. Providing for Bicyclists
- Methods for Understanding and Predicting Safety Performance
- Chapter 12. Cross-Sectional Modelling
- Chapter 13. Time-Series Regression Models for Analysing Transport Safety Data
- Chapter 14. Safety Prediction with Datasets Characterised with Excess Zero Responses and Long Tails
- Chapter 15. Crash Severity Methods
- Chapter 16. Detecting High-Risk Accident Locations
- Chapter 17. Surrogate Measures of Safety
- Methods for Evaluating Safety Impacts of Countermeasures
- Chapter 18. Before–After Evaluations
- Chapter 19. Meta-Analytic Methods
- Summary and Conclusions
- Chapter 20. Conclusions and Future Directions
- Index