Traffic Safety - Science topic

I am not aware of the study mentioned in the question. However, my answer is that it is somewhat relative to the age of the victim.

If victim is a child (studying in school), the directly affected people are parents, siblings, friends and relatives

If the victim is an adult earning person, the directly affected people are parents, wife, children, friends, colleagues and relatives

If the victim is an old person, the directly affected people are all family members (child and adult), victim's friends, and relatives

Here in Australia, I recommend you reach out to CarrsQ, part of the University of Technology Queensland. I am not aware of any studies, but we too are experiencing a higher that recent road toll, for not clear reason, and researchers may start testing for this. CarrsQ run a driver simulator, and may be planning to test people who have long covid's reaction times and cognitive abilities.

Surrogate safety measures (SSM) are helpful resources in safety evaluations since they serve as accident indications. Civil engineers are currently interested in creating intelligent cars without drivers to reduce human error. These cars have intelligent collision avoidance systems (CAS), which use safety signs as warning mechanisms. Surrogate safety measures (SSM) are helpful resources in safety evaluations since they serve as accident indications. Civil engineers are currently interested in creating intelligent cars without drivers to reduce human error. These cars have intelligent collision avoidance systems (CAS), which use safety signs as warning mechanisms.

A couple of things to remember here: in a prospectus assemble the following:

a. The research questions and summarize responses by data type

b. The potential tests of the hypotheses from a

c choose tests based on a and b

d choose sample sizes based on chosen tests and type I and Ii requirements

e conduct methods of d

f answer the research questions based on e

g check the assumptions required in e

h

Prepare summary report of results

Suggestions- 0 Proper Prior Planning Prevents Poor Performance

1 get a good book on research design

2 Study it

3 Follow the suggestions for each step

4 assemble the overall plan

5 collect data as in plan 4

6see f, g and h above

7 do not ever do what you did in this

question again

Good luck David Booth

if you need to study bus movement and bus stops characteristics look for Transport institutions and government policy in your country at the starting point

Dear Dr. Nelson Elias ,

I suggest you to have a look at the following, interesting reference:

- Motorcycle Safety

Available at: https://www.nhtsa.gov/road-safety/motorcycles

My best regards, Amir Beketov.

Dear Dr. Yang Ying ,

I suggest you to have a look at the following, interesting reference:

Available at: https://www.smartertransport.uk/smarter-cambridge-transport-urban-congestion-enquiry/

My best regards, Amir Beketov.

Dear Dr. Seyedehsan Dadvar ,

I suggest you to have a look at the following references:

- Road traffic injuries

Available at: https://www.who.int/news-room/fact-sheets/detail/road-traffic-injuries

- The Deadly Myth That Human Error Causes Most Car Crashes

Available at: https://www.theatlantic.com/ideas/archive/2021/11/deadly-myth-human-error-causes-most-car-crashes/620808/

- Road crashes are the biggest safety challenge for youths

Available at: https://blogs.worldbank.org/endpovertyinsouthasia/road-crashes-are-biggest-safety-challenge-youths

- Road crash deaths and injuries in the world's cities can be stopped. Here's how

Available at: https://www.weforum.org/agenda/2021/05/9-ways-cities-can-prevent-road-crash-deaths/

- Road accidents and safety statistics

Available at: https://www.gov.uk/government/collections/road-accidents-and-safety-statistics

My best regards, Amir Beketov.

Dear Dr. Shane Turner ,

I suggest you to have a look at the following, interesting reference:

My best regards, Amir Beketov.

both

The statistical tool depends on how your questionnaire was structured, the scale of measurement employed, and your hypothesis. Considering all these, you could use descriptive statistics, regression, correlation amongst others statistics. All these can be done on SPSS

There are some typical coefficients that could be used to predict AADT from Peak hour volume and vice versa. The general equation is:

DDHV = AADT*K*D where DDHV= directional design hour volume (your 15-minute count times 4 times)

K = proportion of daily traffic occurring during the peak hour

D= proportion of peak hour traffic traveling in the peak direction of flow

There are some recommended values for K and D depending on the type of road (rural, suburban, urban, etc.)

You can check "traffic engineering" book by Roess, Prassas, and McShane for these values.

Hi i have an eperimental study, i can share you my investigation,in this link:

Additional I add my methodology:

The experimental participatory method was used to visualize how people with disabilities acted within the physical environment of urban public transportation and their perception of information and communication technologies to access the service.

For this purpose, tests were coordinated with several users with various types of physical and sensorial disabilities (deaf and dumb individuals, blind, wheelchair users and disabled in lower extremities, which prove to be the most frequent users in the transport system); complying with the fundamental provision incurred by at least one with some type of disability different from the other, to test them from three scenarios in a sample of 10 participants. The first experiment consisted of asking the participants to go to Metrobus urban public transport from their homes to the final destination in an autonomous way. In the second experiment, participants were given a technological instrument of information and communication from two media: Mobile applications and internal information subsystems in transport to fulfill the same action. Finally, an experiment was proposed in which the participants inside the vehicle with the granted instruments, would find themselves with ergonomic spaces to their needs distributed for their particular comfort and safety; and they would not go down until they reached their various destinations.

The experiments were recorded using digital cameras on board the Metrovía and analyzed to determine the components of the task that caused difficulties. In particular; the time to complete the tasks, the number of disadvantages inside and outside the vehicle, the number of attempts recorded in each travel phase and finally the conditions measured by the weather factor. Having incurred the experimental component of the research, the participants were invited again to receive the activity completed in the three action scenarios. They then engaged in in-depth semi-structured surveys and interviews on issues related to their experience with the Metrobus urban public transport system. These data were recorded, transcribed and then synthesized using standard qualitative methods [5] [6]. The names of interviewees have been anonymous, using the pseudonyms of your choice. Qualitative research does not look for a statistically representative sample but seeks to explore in depth the experiences of people and the meanings associated with those experiences [7] [8].

They proceed with the structure of quantitative methodology from data collected in the experimental participatory method, by use of Mental Modeler. Studies of travel behavior are important for several reasons, for example, to reduce both energy consumption related to travel such as physical barriers and their representation in users with disabilities.

For decades, there have been several attempts to influence the behavior of unsustainable travel of people towards more sustainable ways. However, recently, it manifests how these studies can be implemented effectively and efficiently to develop and support the deeper understanding of the root causes of the trip indicates the reasons and inclinations of people, and complete information on the behavior of individuals, for that the use of ''Cognitive Fuzzi Maps'' [9] through the use of the Mental Modeler platform gives an answer in decision-making on transport policies in understanding the needs of people in a better way, consequently, will help them update different policy formulations and implementations.

At the end two scenarios will be obtained; understood by the reality and the estimation of statistical data that will help in the best development of the proposal through the analogy and its application in the technological ergonomic model to be proposed.

You may find the following one useful:

Hi, would be helpful if you highlight the conflicts with a dot or something similar and add the number which you have come up with in order to be able to compare. Also, sometimes more than two lines cross at almost the same spot. E.g. at intersection IM the line from A.H.Road to Rupkotha Road intersects the straight line from Court Road to A.H.Road at the same spot as the line from Rupkotha Road to Aurangzeb Road. For your purposes, do you want to count that as one conflict or two seperated conflicts? Maybe you have access to a program that helps you identify conflicts?

Mostafa H. Tawfeek

Thank you very much!

I noticed that some applicants have listed me as his/her reference. Please DO NOT list me as your reference when applying. The reference letters should be from those who know you. Thanks.

This question belongs to 3 years ago but I'd still like to add my comments based on my understandings for the prospective interested readers:

1) For the purpose of your research (and possibly any other aspect of human factors in microscopic level), the accuracy of the data in itself is very important. The NGSIM data is also shown to be riddled with systematic errors due to the rotation of camera and the associated image processing methods. Yet, these errors may not affect your research if you are mainly interested in macroscopic state variables or some aspects of car-following behaviour. But if you are trying to extract additional human factors, these data may not be a good source. the following papers presents more discussion on the accuracy of the NGSIM data:

i) On the assessment of vehicle trajectory data accuracy and application to the Next Generation SIMulation (NGSIM) program data

V Punzo, MT Borzacchiello, B Ciuffo

Transportation Research Part C: Emerging Technologies 19 (6), 1243-1262

ii) Trajectory data reconstruction and simulation-based validation against macroscopic traffic patterns

M Montanino, V Punzo

Transportation Research Part B: Methodological 80, 82-106

2) GPS-based Floating car data (FCD) may not again suit what you're looking as the spatial & temporal accuracy of these data may be below what you may need. Extended floating car data (XFCD), however, can compensate for the limitation of FCD as you have information of the leading vehicle. But this is helpful if at least the temporal resolution of the data is above your human reaction time...

3) If you are developing a new methodology, probably the best way (to my knowledge) is to test it on reconstructed trajecoty data by commercial softwares such as VISSIM & AIMSUN to minimise the effect of systematic error in the process of data collection. You should, however, be advised that whatever results you are getting with using these data are based on Viedemann (VISSIM) and Gipps car-following models (AIMSUN) and may not produce adequate insights about the actual human factors.

Good answer by Kundan.

I think through video for external and GPS

In this case (last ten years), the headway in group of lanes during off peak had been provided within 5 seconds. If a driver drove his car passing the virtual loop, it leased to extend the range of green times. Howeve, it was not over the maximum green times. In case of red times, there was no vehicle to pass the virtual loop.

Hi Urie.  Empirical and personal experience with this, overbanding (the smooth tar bands used to seal tarmac cracks) and Rainurages, especially on French concrete motorways l(ongitudinal grooving of the road surface for rainwater management) are notorious for their negative effects on the handling of motorcycles.   There are many data sets and accident analysis reports on road traffic accidents (RTAs) available, USA, Canada, UK, EU.  To take overbanding first.  The hazard is the reduced traction of the overbanding material compared to the road tarmac.  In wet conditions it gets slippery.  In dry hot conditions it melts.  It was a problem in the UK leading to litigation after RTAs.  The compounding of overbanding material was changed to include 2-4mm sharp abrasive grit to improve wet traction.  In countries where hot dry conditions occur the overbanding can include more asphalt and less bituminous tar for better hot weather performance.

longitudinal grooves, aka rainurages, upset the dynamic stability of motorcycles and bicycles.  Consequential crashes are then multifactorial.  Catastrophic stability upset is just one cause, others will result from rider mis-actions as a result of less than catastrophic stability upsets.  

There is little to no correlation to the type of vehicle, probably much correlation to the way the vehicle is ridden...

You have not mentioned a situation called "target fixation", the rider sees a hazard and looks at it in the process of riding.  The consequence is that the vehicle steers towards the hazard.  It is most often a failing of novice and improver riders.  Experienced riders learn or are taught to "look at the part of the road they want to go up, not the thing they want to avoid!".

All of the hypothesis point you make are errors of low expertise on the part of the rider.  A rider with high expertise will know either intuitively or as a result of training to excercise riding techniques to mitigate the risks you are interested in and have methods to manage situations as they develop.

Inappropriate use of speed probably covers most of the mishaps you wish to investigate.

i suggest you obtain a copy of Roadcraft, published by HMSO in the UK.  It is used as the riding manual by The Institute of Advanced Motorists.  It is available as an ebook.  I am not connected in any way with any of these organisations.  Regards. Jonathan. Motorcyclist for 40years.

In roads I have no experience. In railways we use a fixed person (with radio) on one of the extremes of the curve and a moving person (with radio) on the other extreme that would approach the first one. When they see each other chest fully we would mark it and measure with a measurement wheel

Thank you, Dr Weerasekera. I will read and get back to you if I have comments

A recent Austroads study authored by my colleague at ARRB:

Vissim, the simulation tool I am familiar with, provides for both right and left hand drive facilities selected as part of the development process.

BRSI link to weather and road safety research appears to have been fixed:

As far as I can tell, there are no truly predictive modelling methods, i.e. such that could predict when a crash will occur, or where it will occur.  There are essentially two types of crash modelling methods: frequency and probability. The first method seeks to estimate the most likely mean frequency (e.g. per annum) for a given location type such as a  road section or intersection with a set of attributes. The second method seeks to estimate probability that should an event occur, it will be of certain type. This can be a severity model (e.g. probability a crash will be fatal) or occurrence model (given a vehicle enters an intersection, probability there will be a crash). You would do well googling US authors such as Zegeeer, Harwood, Sayed, or Hauer. 

Still I don't know of a way to estimate the time and location of a random event such as a crash. Perhaps others do....

Dear Gerald and Jose

You are not really surprised, are you? This phenomenon is illustrated by the following example (cited from http://economictimes.indiatimes.com/definition/moral-hazard):

"You have not insured your house from any future damages. It implies that a loss will be completely borne by you at the time of a mishappening [sic] like fire or burglary. Hence you will show extra care and attentiveness. You will install high tech burglar alarms and hire watchmen to avoid any unforeseen event.

But if your house is insured for its full value, then if anything happens you do not really lose anything. Therefore, you have less incentive to protect against any mishappening. In this case, the insurance firm bears the losses and the problem of moral hazard arises."

Moral hazard, as the reaction to insurance is called, has been mentioned many times in recent years in discussions in the United States about problems that might arise (extra burden on the provision of medical assistance) as a result of state-funded medical insurance. A Swedish study found evidence that calling in sick from the job became less frequent when workers' compensation for sick leave were reduced (   ). Moral hazard has also been noticed by several other analysts,  like Boyer, M. and Dionne, G. (1987). The economics of road safety. Transportation Research-B, 21B, 413-431; Worrall, J.D. (198).

Others reported that increases in workers’ compensation payments for injuries may increase the rate of workplace accidents. (Worrall, J.D. (1983). Safety and the workforce: Incentives and disincentives in workers’ compensation. ILR Press, New York State School of Industrial and Labor Relations, Cornell University).

Phrased in simple terms: to offer people protection against the consequences of risky behaviour encourages risky behaviour; to offer people better protection against the consequences of risky behaviour encourages riskier behaviour still.

Automobile and other insurance sells peace of mind, which is nice, but it is also a problem for that very reason. This is, as mentioned earlier, why automobile insurance at one time was forbidden by law in some countries.

This is not to say that we should not have automobile insurance, but obviously the consequences should be seriously considered and insurance practices should take them into account.

Partially or composite ?

The common way is to compare actual conditions and perceptions. You can evaluate  LOS of actual condition based your developed model or HCM guideline then you can investigate how close was the perceptions versus actual conditions.

Option 1 would a validation exercise indeed. You can do this very simply by correlating the model and real outcome. There are several statistical methods depending on what outcomes you are comparing. One example I have is EuroRAP star rating vs. crash rates - two different variables, not directly comparable.

If you went with Option 2, e.g. a statistical modeling (accident prediction model), then you can use various residual plots as long as you got an independent sample not used in modelling. There are more sophisticated methods than that of course.

Option 3 could be modified by adding data from 'safe' sites. Then you are looking cross-tab analysis, the predecessor of statistical models. See answer for Option 2.

Option 3 - you are looking at proxy measures. As far as I understand this subject, it is the next frontier in road safety. Great for developing understanding of combined human, vehicle and road factors involved in crashes, i.e. everything that current statistical models do not do. The near future.

Thanks Edmund 

Thats a great help!

As noted previously, with pre-timed controllers you are typically allowed three different plans, plus a fourth one that consists of flashing operation (during late night, very early hours of the morning when traffic is low).

At isolated intersections, unless you have very heavy turning movements that require protected phases, vehicle-actuated operation (without fancy adaptive algorithms) should handle most fluctuations typically experienced at an isolated intersection effectively, especially if there is a dominant direction (clear major vs. minor). 

I would hope that the test protocol defines what lane change is required.  Suggest that you start by having a look at ISO 3888

there are many factors on roads that may lead to accidents. Though sun glare is an obvious factor for the accident, it is hard to find the correlation relationship between the accident and sun glare. On the book "How Drivers’ Smart Advisory System Improves Driving Performance? A Simulator Imitation of Wireless Warning on Traffic Signal under Sun Glare" the 6th section on "Impacts on mean approach speeds" in Page 61, it is mentioned that "The posterior questionnaire survey tells that, approximately 47% of subjects (14 out of 30 subjects) committed signal violation unconsciously on through movements". The 47% may imply a high risk of accidents for through movement (drive through a signalized intersection). 

In fact, there are many accidents recorded for left-turn movement. The accidents are often involved with the right-turn vehicle and through-movement vehicles from the opposite side. Left-turn vehicles need to yield the traffic flow from the opposite side. However, when they are disturbed visually by sun glare, they may not able to yield the traffic flow. For the through movement, there is still two seconds cleaning time, yellow signal. 

To add to this: in this report

the scientist involved have found that in the age group 20 - 60 years old, male drivers had 1.5 higher risk (accidents/km) of a fatal accident than female drivers. However, for the non-fatal accidents, the risk of the women is 26% higher to get injured and 16% higher to get involved in an accident than men. So, one may in fact assign males a more risky driving-style, but only after proper normalization. However, this analysis was performed for the US in 1990; different areas and different times may provide different numbers.

Yes, congestions also came up my mind... But since AADT is usually used (which is aggregated annually), I would think it is not likely that congestion would influence this.

You can start research by

The Present Serviceability Rating (PSR) is a subjective, ride-based observation on the roughness of the pavement to estimate deterioration, deficiencies, and needed improvements based on early AASHO Road Tests. The higher the PSR value, the smoother the riding surface. So PSR is closely related to PSI.

Good work and good luck

Crash Severity on a urban highway, as on other roads, mainly depends on the kinetic energy. The kinetic energy by the speed. The speed by traffic flow, density, lane width, tortuosity of the route etc.

I would check the following parameters in function of the crash  severity:

number and width of lanes, traffic flows per lane (in passenger car equivalents per hour), composition of traffic flow, speed (85th percentile or speed diagrams for the entire path), speed differences among different types of vehicles (such as cars, vans, trucks etc).

The interdependence of these parameters and the crash severity should give you some good results.

Good work and good luck

Pedestrian traffic island is one of traffic calming measures. Trying Google search with for example "safety impact traffic calming" will give you several interesting links. However note that most of this research is related to "traffic calming boom" which culminated in 1990s. In Europe one of the main proponents was British TRL - their library is also a good source: http://www.trl.co.uk/reports-publications/trl-reports/?search=calming

And another important consideration - accidents are not necessarily the best target variable to focus on when looking for efficiency of these measures. You will see that many studies looked rather on behaviour (in terms of speed, near-misses, etc.). It is not easy to study safety changes based on, for example, rare numbers of accidents on a sample of pedestrian crossings. This is why safety research of vulnerable road users (pedestrians, cyclists...) very often relies on non-accident based indicators. In this regards ICTCT has been the leader in last decades: http://www.ictct.org/workshops/past-workshops/

Hi,

Not only depends on the reaction time T, also it depends on the time t vehicle acceleration trying to follow.

You can see:

Brackstone, M., & McDonald, M. (1999). Car-following: a historical review. Transportation Research Part F: Traffic Psychology and Behaviour, 2(4), 181–196. doi:http://dx.doi.org/10.1016/S1369-8478(00)00005-X

Gazis, D. C., Herman, R., & Potts, R. B. (1959). Car-following theory of steady-state traffic flow. Operations Research, 7(4), 499–505.

Dear Quan Yan,

Yes, you can continuously run the simulation post-crash, depending on your  simulation engine/software. We developed our own for research purposes and thus we are able to control the behaviour of the simulation software like what we want. Perhaps you might want to contact simulation professional software developers ( like drive square above ) for assistance. 

you can look at my paper in my profile on red light running and dynamic distrations that may be of interest

Thank You for your answers!

For Logit models NLOGIT have option for the estimation of elasticity and marginal effects (or) You can use R which you can call with single line command.

You may look on these papers

A general problem with any long-term before-after study on traffic safety is the general trend towards fewer serious accidents by a number of reasons including passive safety, road improvement, increased driver education, and so on. In a simple before-after study, all these effects act as uncontrollable confounding variables. To be able to recognize and possibly eliminate them, one needs at least four data sets: 1. Test site before ITS, 2. test site after ITS, 3. a different reference site at the time of Set 1, 4. reference site at the time of Set 2 and with *unchanged* ITS status. Of course, this four-stage design is only possible if the deployment of ITS can be controlled locally (infrastructure-based ITS, e.g., V2I or I2V) rather than purely vehicle-based ITS (V2V and all sorts of local assistance systems). Furthermore,  the results pertain to ITS with infrastructure components, only.

When discussing correlations you have to keep in mind that correlations do not necessarily imply causal relations. Often, they are a consequence of a common influence by an ignored third factor such as properties of the infrastructure (many or few freeways), regional structure (predominantly urban or countryside), cultural properties,  (liberal or strict) legislation, (sloppy or stringent) control/enforcement. For example, in countries with liberal speed regulations (e.g., 75 or even 85 mph allowed on some roads) and sloppy enforcement (hardly any speed limit monitoring), few speed tickets are issued, i.e., the statistical data show little speeding. Nevertheless, in an objective sense, there may be many drivers driving too fast for the given situation resulting in comparatively many accidents.  This results in a paradoxical correlation with an unexpected sign between speeding and accidents.  This is a variant of the classical Simpson's paradox: The more firefighters are sent to the scene, the more damage the fire will  cause.

Dear Mahdi, I suppose that crash prediction models are what you are looking for. They relate crash frequency to various explanatory variables, which is exposure (traffic volume) and geometrical characteristics, such as median, etc. Since crash frequency is a count variable with non-normal distribution, they are usually developed using generalized linear models with negative binomial distribution. This is also what I am using; however for the work of real guru look for example here - https://www.researchgate.net/publication/239438865_Statistical_Road_Safety_Modeling

Dear Eng. Rusli

There is a lot of literature. I myself is preparing an article regarding design consistency and crash prediction model. Speed in one of the most important factor. You may try this reference. It is comprehensive.

Awatta, M. Highway Design Consistency and Safety: Individual and Overall Evaluation Criteria. Ottawa, Canada: Carleton University; 2003. 

thank you.

Hi Walter

I'm not sure if you have seen the attached - but just in case.

Best wishes

Lisa

Please use step wise multiple regression models and multivariate analysis to know the impact of every variables.

Hi, Maybe this report can be useful for you.

Road Safety Impact of New Technologies, by OCDE

Here there are others...

(2013) The evolution of urban traffic control. changing policy and technology

(2009) Beyond ‘‘best practice” road safety thinking and systems management

Kind regards

Hi,

concerning ITS for motorcycles, the PISa project (www.pisa-project.eu) proposed a prioritisation of safety functionalities to be integrated on powered two wheelers, based on estimated influence in real-world motorcycle crashes.

Attached is a link to related Executive Summary.

This activity was briefly presented at some conferences (see attached), but with poor details. And as far as I know there is not a journal paper on that.

I hope it is of help.

I recommend the following website; it is helpful.

@Xochitl

Experience can certainly be a factor, but one which is hard to disentangle from a general decrease in risk taking behaviour with age (perhaps based on near misses or real accidents)

@Vincenzo

Distraction is certainly one of the top causes cited by cyclists involved in an accident in Belgium. However is it unclear to me why women would be more distracted than men (in Belgium and the other way around in other countries)

@Yves 

The population was limited to those of working age and mainly focussed on commuting so probably not due to differences in time activity pattern.

However on the gender issues I think you may have a point. Some of the men in the study reported really long commuting distances along e.g. canals where accident risk (per km cycled) is probably very low. On the other hand women seem to take trips more often in the rush hour (e.g. AB modelling by Beckx et al) and in town centres with more intersections and therefore higher risk (while their risk aversion while driving/cycling) may still be higher than that of men)

@Henk

Thank you for the Dutch graph. The reversal of male/female risk ratio with age is really interesting. The SHAPES sample was limited to those of working age (<65) and the number of observations in the +50y was indeed very low. On the other hand we are very confident in our assessment of the distance cycled which we observed frequently during a whole year.

Hi.

Your question can be answered by more carefully inspecting the literature.

Post-encroachment time is conventionally defined as the time between the first road user leaving the common spatial zone (in a 2 road user encounter) and the second road user arriving at it.

It is easier to understand its definition by looking at a figure. The attached publication (see reference) contains a figure, a discussion and further material to get you underway.

Hope this helps.

Best

I was wondered if you use GAs for Bus scheduling problems, then in addition to problem specific parameters like waiting time, fleet size, frequency, why you did not consider GA's own parameters like crossover and mutation rates, selection pool size. Without having these parameters you can not control the exploration and exploitation mechanism of GAs. I would suggest you to go through production scheduling problems like single machine, job shop, flow shop or open shop scheduling problems where GAs have been designed and implemented to solve the problem.

Dear Enoch,

I quite agree with Satish Chandra.

The study of traffic safety, urban (or not) starts from the data. These can be at different levels of depth depending on the results you want to achieve: general strategy, action planning, design of the countermeasures. From the statistical data down to single police reports.

You try to give a quick read to ANALYSIS OF ROAD SAFETY: THREE LEVELS OF INVESTIGATION that I have made available now.

Then you let know me.

Fines is the most effective method to improve road safety these days in my country.

Can you send me the web site in which you found this handbook? Maybe i can obtain a copy through the library of my university.

Look at this paper: https://www.researchgate.net/publication/257392971_Investigating_Traffic_Flow_in_The_Nagel-Schreckenberg_Model

The class of models is known as the ``Nagel-Schreckenberg'' model.

I go out every year at least once, or more.

I will still prefer to fly, despite these aircraft incidents. I think flying is less unsafe than driving on highways, more so in my country where the driving habits of most people are not acceptable. Some risk is involved in almost activities that we do.

Admittedly, humans are rational human beings. They sub-consciously take decisions on the basis of cost-benefit analysis. I will vote for flying than driving anywhere.

fuzzy data classification methods are suitable for complex data subject to uncertainties. The uncertain nature of noisy data requires the use of fuzzy methods.

Good luck

For an online questionnaire of motorcycle riders we asked "How many near misses or close calls have you had in the last 12 months while riding on a public road?" and then asked them to describe the most serious one from the last 12 months and provided a text box. Respondents had no problem providing answers, but there was a wide range of numbers - which was okay because this was more of an exploratory aspect rather than the main game for this study.

To be more specific you could add "...near misses or close calls for which you had to brake or swerve unexpectedly". And if near misses are your main focus divide it up "...near misses...brake or swerve...involving a pedestrian" "...involving a car" etc.

Since they are novices you could also use something like "...that really shook you up" or some such. Depends what your hypothesis(es) are I guess.