Road users

R. M. Hanbah, Economic Impact of WinterRoad Maintenance on Road Users, Transportation Research Record 1442, Transportation Research Board, Washington, D.C., 1994. 

Mark roads and warn other road users... 

Best course of action is not to get into the car. Explain your concerns for the driver s safety and that of other road users. Consider informing police of situation to ensure safety of driver and others. 

This would be a challenging task as you would have to understand the Highway Code from the observed behaviour of other road users However, you might come up with a reasonably close model of national traffic rules. And you would not need to give detailed descriptions of individual components of a car to do so. 

Grayson, G.B. and Hakkcrt, A.S. (1988). Accident analysis and conflict behaviour. In J.A. Rothengatter and R.A. de Bruin (eds.), Road Users and Traffic Safety. Van Gorcum, Assen. 

Horst, R. van der (1991), Video analysis of road user behavior at intersections. In T.W. van der Schaaf, D.A. Lucas and A.R. Hale (eds), Near Miss Reporting as a Safety Tool. Butterwortb-Heinemann. Oxford,... 

In order to provide a simple numerical illustration, suppose that a programme reduces the number of people killed in traffic accidents from 7 per 100 000 road users to 5 per 100 000 road users. Suppose that the total number of trafficants isH= 1000 000 so that the programme saves 20 lives,... 

Helmets cannot prevent all head injuries, and the aim is to minimise the social costs of injuries to the population of road users with a wearable product. 

The first expression of the functional evaluation of the pavement was related to the rideability or acceptability of the pavement by road users. The determination of the ride quality was carried out by a group of people who drove over various pavement sections of excellent to unacceptable quality level and then rated the pavement sections on a scale of 0 to 5. Such pavements were those constructed during the AASHTO experiment (AASHTO 1962 Carey and Irick 1960). 

In this thesis, the term "Road Safety" is often used instead of "Traffic Safety" because this thesis focuses on road traffic safefy only including road user safety and vehicle safety. The term Traffic Safety is a general term and could refer to the safety of all traffic modes air traffic, sea, rail and road. 

Although there are many attempts have been made to describe road accident problem, I used to describe the problem as a disease where the causes of road accidents are symptoms as (illness). The road safety problem is a sign of illness in society. To diagnose the problem, there are direct and indirect symptoms (causes). The direct symptoms in road safety can be easily seen in society from simple observation and data such as speed problems, alcohol and driving, vehicle conditions, road user behaviour, etc. The indirect symptoms in road safety are not simply obvious and they need more checking and examination such as the traffic management, education, traffic police enforcement, legislations, etc. 

The lack of detailed and quality exposure data is a challenging issue and therefore, international comparisons are often conducted on the basis of a per-capita population or per-vehicle. There is a need for detailed exposure information on a specific population (e.g. children or elderly road users), non-motoiised modes (e.g. cyclists and pedestrians), motorcycles, and driver information. This information is often less known and available in many developing countries than in highly developed countries. The classifications of roads also differ in their standards from one country to another (e.g. national/regional/motorways). There is a need for special counts of traffic volume by type of vehicle and type of roads. 

Risk is determined as the probability of an accident to happen per units of exposure or it is valuated as the size of consequences (severity) of this accident. The higher the accident risk, the higher is the probability of an accident to occur for a given road user in one particular place and time. Sometimes the term risk of accident is named as accident rate. 

When comparing different countries, the indicators of fatality per population and fatality per vehicle are widely used and they vary from country to country and over time. Both measures do not take into consideration the characteristics of the type of transport modes or the road users. The risk per exposure unit has generally showm a clear decrease over time in most countries. This is an indication of an improvement in the overall accident situation in most countries where they produce lower accident rates for each unit of exposure. However, the exposure unit itself (i.e. number of vehicle or vehicle kilometres travelled) has continued to increase and more casualties occur on... 

Reducing Risk Factors by reducing the accident rate for a given unit of exposure (travel). It is possible to reduce this by improving driver skills, road user education, vehicle performance, road standards, legislation and enforcement. 

Reducing accident severity by protecting people better in vehicles from injury severity. Protecting pedestrians and other vulnerable road users by vehicle design, and protecting two wheelers by using appropriate helmets. 

I. Risk and Road User Behaviour Different studies indicate that the human factor (road users) is the major contributory factor to accidents. At the same time, any error in the system and on roads will lead to unsafe road user behaviour ... 

Illiteracy Bester (2001) has analysed socio-economic factors in different countries and he found that the illiteracy percentage has a statistically significant effect on the national fatality rate. He explained that a country that can read and write is expected to influence the ability of road users to understand the rules of the road and road signs. 

Sixth, we should always use a group of indicators relating to the desired objective we want to describe. But at the same time, we should not allow the set of indicators to become too many because that will take too much time to interpret and analyse (also it is a matter of cost). There is no exact number of indicators rather the number should at least capture the results sufficiently for what we want to obtain. The chosen indicators should be as minimal as possible. For instance, road user behaviour in the coimtry may require many indicators to capture the major aspects. Flowever, we should remember that if we have identified a large number of indicators for single aspect, this might means that the aspect is too complex or more data is being collected than necessary. In brief, it needs a well-balanced set of indicators as possible. 

I have identified eight groups of indicators (see Figure 3.3) of which each corresponds to a special area of road safety. The groups listed are traffic risk, personal risk, socioeconomic indicators, road safety organisational structure, traffic police and enforcement, vehicle safety, roads situation and road user behaviour. The groups measure road safety development in terms of output or input classes. The output... 

Nevertheless, some other studies have tried to explain why the curve of development (fatality rates) declines downwards as been noted in many countries and shown in Smeed s formula. The studies have analysed the factors and measures that influence the development of the curve of road safety. A review of these studies is reported by (Elvik Vaa, 2004) and (Hakim, 1991). Besides, Minter (1987) and Oppe (1991b) showed that Smeed s law is a result of a national learning process over time. The development in society at the national level is the result from the developments at the local level. In other words, the individuals (road users) can learn by experience in traffic where they improve their driving skills and knowledge, while the whole society can learn by better national policy and action plans. The Figure shown here illustrates these factors on the development curve of road safety. 

A high proportion of trips are made by non-motorised modes of traffic (NMT) in ASEAN countries. The casualties in respect of motorcycles constitute the majority of road users in accidents, nearly 90% in Cambodia, 70% in Vietnam and 60% in Malaysia. This group of road users together with pedestrians and cyclists is referred to... 

Not all accidents and exposure variables are available in ASEAN countries, especially for what is considered necessary for meaningful comparisons like (fatalities, km. veh, fatalities by type of road user, by age distribution, by time, driving experience, types of vehicles, types of travel, etc.). 

In principle, eight general themes have been selected in the construction of RSDI, which are traffic risk, personal risk, vehicle safety, roads situation, road user behaviour, socio-... 

The first chosen dimension is the level of traffic risk in a country, which deals with the fatalities rates. The fatality rate per vehicle is currently used, while fatality rate per vehicle-km or per person-km or per type of road user (pedestrians, cyclists, motorcyclists and drivers) are all other indicators of this dimension and they can be used on the long term of RSDI. 

The dimension of road user behaviour is currently based on the percentage of seat belt use, and helmet use. Additional indicators that might be added, include the percentage of drivers above BAG Blood Alcohol Concentration and percentage of all drivers exceeding the speed limits. 

Road user - Percentage of front-seat belt use 0.0 100.0... 

Other interesting features of RSDI include a development of disaggregated indicators across municipalities in the country. This provides a useful basis for local policy makers to address their own problems compared to other municipahties and counties in the country. The prospects using the RSDI approach for big cities are discussed briefly in (A1 Haji Asp, 2004). As might be known, municipality data often has homogenous definitions (standards) and nearly similar socioeconomic conditions and levels of mobility. It is also possible to construct RSDI in terms of homogenous risks by different road users, age groups and types of vehicles. 

By doing this, I rely on earlier studies that indicate accidents caused by a combination of five main dimensions (human-vehicle-environment-road-system). One of the major contributory factors in road accidents is human error. The size of this human error depends on the whole road system and traffic regulations. Rumar (1999) has shown that the major contributory factor in road accidents is the human factor. The results are taken from two in-depth studies and analyses carried out in the UK and USA. Both studies indicate that the hmnan factor (road users), overlapping with other factors, is the major contributory factor in 94/95 % of accidents as shown in Figure 5.6. 

RSDI = 0,25 (traffic risk) + 0,10 (personal risk) + 0,10 (vehicle safety) + 0,10 (road level) + 0,25 (road users behaviour) + 0,05 (urban population level) + 0,05 (income level) + 0,05 (health level) + 0,05 (education level)... 

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