Fact sheet

Police traffic enforcement

Summary

Police traffic enforcement is an important element in road safety policy. The objective risk of apprehension (the actual possibility of being apprehended for a violation) and the subjective risk of apprehension (the estimated possibility of being apprehended) to a large extent determine the success of policing. The severity of the penalty is only of modest influence. 

Traffic enforcement in the Netherlands is carried out by the general basic teams and by the Traffic teams of the police force. This is conducted in close cooperation within the local triangle (mayor, public prosecutor and chief of police), but also with road authorities and partners such as the Dutch Traffic Safety Association. 

For 2016, the police have set five national priorities: speed, alcohol, red light running, distraction and multiple offenders. 

A survey in 2011 among 11,000 inhabitants of the Netherlands found that 92% are in favour of a stricter approach towards alcohol offenders and 51% are in favour of placing more speed cameras. 71% were in favour of placing red light cameras.

Facts

How is police traffic enforcement organized in the Netherlands?

Since 2013, the national police in the Netherlands consists of 10 regional units, 43 districts and 168 basic teams. The traffic enforcement is carried out by the general basic teams and by the Traffic teams, which fall under the Regional Operational Cooperation Service (DROS), Department of Infrastructure. Special traffic enforcement teams within the Traffic teams spend nearly all their time on the enforcement of important traffic rules.

What are the national priorities for traffic enforcement?

As from 2016, the Public Prosecution Service (OM) has set the following national priorities for traffic enforcement [1]:

  • speed
  • alcohol
  • red light running
  • distraction
  • multiple offenders.

The Public Prosecution Service has issued the following guidelines for the enforcement of these priorities [1]:

  • The police will continue to make 659 FTE available exclusively for traffic enforcement. The Public Prosecution Service has set this precondition to the police at the transfer of the budget for the traffic enforcement teams.
  • Being stopped is being breathalysed. In addition to the regular alcohol checks every driver who is stopped by the police will also be breathalysed to increase the subjective risk of apprehension.
  • The driver’s licence of every apprehended driver will be checked. This will increase the subjective as well as the objective risk of apprehension for road users whose driver's license has already been suspended.
  • Helmet and seatbelt enforcement during surveillance duty. For many years, compliance with mandatory helmet and seatbelt wearing has been around 97%; these behaviours have therefore not been set as individual priorities. To keep compliance at this level, it is advised to include the enforcement of helmet and seatbelt wearing in other enforcement activities.
Which enforcement methods are used by the police?

Table 1 shows the different traffic enforcement methods in the Netherlands, those with and those without apprehension of the road user.


Table 1. Survey of the most widely used enforcement methods in the Netherlands.

 

 

 

 

What determines the effectiveness of police enforcement?

Police enforcement works on the basis of the objective and the subjective risk of apprehension. The police checks at the roadside determine the objective risk of apprehension, also called enforcement pressure [2]. Based on the enforcement pressure and on what road users read about in newspapers or hear from friends or acquaintances, they estimate how likely it is that they will be apprehended for a violation: this is the subjective chance of being caught. When road users feel the risk of being apprehended is sufficiently large, they will avoid violations.

To make the subjective risk of being apprehended sufficiently large, it is important that the checks are accompanied with a fair amount of publicity, that they take place quite regularly, and that they are random, well-visible, and difficult to avoid.   

Given a sufficiently high subjective risk of apprehension, the preventive effect of police enforcement is generally stronger when the certainty of punishment is greater, when the punishment follows the offence faster, and when there is much public support for enforcement of this particular offence [2]. Each of these elements is a link in the chain of traffic enforcement.

The severity of the penalty can also affect the effectiveness of the enforcement, but the influence of the penalty is modest. Research has shown that the level of penalty is much less important for influencing traffic behaviour than the risk of apprehension. It is also known that increasing the penalty has no effect on driving under the influence, probably because the existing penalties are already fairly high. The number of lighter offences such as speeding, no seat belt, red light running do decline somewhat as penalties get higher, but only in places where the police frequently checks [3].

Does a change in the number of fines mean that road users started behaving better or worse?

An increase or decrease in the number of fines that are imposed does not necessarily mean that the number of offences has risen or gone down (the red weights in the figure below). For conclusions about this it is necessary to know whether or not the police increased their enforcement activities (blue weights). The traffic volume also plays a role (green weights): when traffic volumes are smaller (e.g. due to economic crisis), the number of fines also decreases.

What is the effect of the enforcement methods per priority?

Below we indicate the effectiveness of police enforcement for each of the priorities (formerly known as spearheads). The focus is nearly always on the effects of a combination of police supervision and information/communication together. For many years the police and the Public Prosecution Service have used the slogan: 'No enforcement without communication and no communication without enforcement ' [4].

Alcohol

Between 2003 and 2013, the percentage of drivers in the Netherlands with a blood alcohol concentration (BAC) above the limit dropped from 3.4% to 1.8%. The share of serious offenders (BAC 1.3 g/ℓ and higher) remained more or less equal for a long time, between 0.6 and 0.4%. In 2011, this declined to 0.3% and in 2013 dropped even further to 0.2% [5]. International research estimates the average safety effect of enforcement of driving under the influence to amount to a 14% reduction in crashes [6].

Distraction

Scientific studies indicate that distraction plays a role in the origin of about 5-25% if the crashes involving passenger cars, see also SWOV Fact sheet Distraction in traffic. No research has yet been done in the Netherlands into the effects of intensified police enforcement of distraction. In the State of New York in the United States, campaigns with television and radio spots accompanied by visible police enforcement of handheld phone use by drivers, have led to a reduction in handheld phone use: from 6.6% to 2.9% in Hartford and 3.7% to 2.5% in Syracuse [7].

Speed

On road sections with speed cameras, the number of injury crashes declines; this has been indicated in several national and international studies [8] [9] [10]. Based on a survey it was estimated that the reduction in crashes is 18% on road sections close to the location of the camera (within about 250 m) and 4% on road sections situated at 1 km or further from the camera [11]. If the number of speed checks in the Netherlands were to be doubled before 2020, particularly on the secondary road network, the estimated number of casualties saved in the year 2020 would amount to a minimum of 70 road deaths and 1,060 serious road injuries [12].

Red light running

International studies show that the use of red light cameras may decrease the number of lateral collisions with injury by 33%, whereas the number of rear-end collisions with injury can increase by 19% [13]. Because rear-end collisions often have less severe consequences than lateral collisions, the result will be a positive safety effect. More recent (American) studies once more indicate that red light cameras can lead to an increase in rear-end collisions, but also to other types of intersection crashes [14] [15] [16] [17]

The results of the recent American studies cannot directly be generalized for the Netherlands due to large differences in traffic system (think of differences in intersection design, speed limits, traffic volume, presence of cyclists). The limited Dutch research into this topic estimates the effects of red light cameras to be positive. An evaluation study in the city of Amersfoort showed positive safety effects – a 20% decrease in the number of injury crashes [18] [19]).This study also found no increase in the number of rear-end crashes.

Multiple offenders

Multiple traffic offenders are road users who do not take account of other road users, fail to comply with traffic rules and are guilty of systematically doing so [20].

SWOV-research indicates that vehicles are more and more involved in crashes as they have received more fines [21]. Dutch research indicates that sending warning letters – signed by the police district manager – to multiple offenders can reduce the number of offences [20]. A written warning extracts multiple traffic offenders from being anonymous and the multiple offenders who are sensitive to sanctions in particular can be motivated to prevent higher fines and losing their driver's license by adjusting their driving behaviour [20].

How does the road user feel about police enforcement?

Public support for alcohol controls is very strong, and it is slightly less for certain types of speed controls. This is shown by the Periodic Regional Road safety Study (PROV) in the Netherlands that describes the support for various road safety measures, including enforcement measures. This survey was last conducted in 2011 among more than 11,000 Dutch road users [22].

At that time 92% were found to be in favour of more and stricter controls on driving under the influence of alcohol and 91% were in favour of a stricter approach to alcohol offences. The same survey indicated that 51% were in favour of placing more speed cameras and 71% were in favour of placing red light cameras.

The ‘enforcement monitor study’ that was repeatedly carried out by the Bureau for Traffic Enforcement of the Public Prosecution Service, indicates which types of speed controls are more or less acceptable for Dutch drivers. The results of the measurements until 2010 can be found in Table 2. After 2010 this enforcement monitor study was no longer carried out.

Table 2. Percentage of respondents that find specific types of speed enforcement methods (very) acceptable [23] [24]. he distinguished types are those used in the enforcement monitor study.
Publications and sources

1. CVOM (2015). Leidraad Handhavingsplan Verkeer 2016-2018. Parket Centrale Verwerking Openbaar Ministerie, Afdeling Beleid & Strategie, Openbaar Ministerie, Utrecht.

2. Goldenbeld, Ch. (2005). Verkeershandhaving in Nederland; Inventarisatie van kennis en kennisbehoeften. R-2004-15. Stichting Wetenschappelijk Onderzoek Verkeersveiligheid SWOV, Leidschendam.

3. Goldenbeld, Ch., Wijk, A.Ph. van & Mesken, J. (2013). Sancties in het verkeer. Een vergelijking tussen het terrein van de verkeersveiligheid en de jeugdcriminaliteit. R-2013-10. SWOV, Leidschendam.

4. Mesken, J. Goldenbeld, C. & Vlakveld, W.P. (2011). Herijking speerpunten van de regionale verkeershandhavingsteams: inventarisatie en analyse van gevaarlijke gedragingen in het verkeer en de mogelijkheden deze te beïnvloeden door verkeershandhaving. R-2011-21. SWOV, Leidschendam. 

5. WVL (2014). Rijden onder invloed in Nederland in 2002-2013; Ontwikkeling van het alcoholgebruik van automobilisten in weekendnachten. Ministerie van Infrastructuur en Milieu, DG Rijkswaterstaat, Water, Verkeer en Leefomgeving WVL, Den Haag.

6. Erke, A., Goldenbeld, C. & Vaa, T. (2009). The effects of drink-driving checkpoints on crashes - A meta-analysis. In: Accident Analysis & Prevention, vol. 41, nr. 5, p. 914-923.

7. Chaudhary, N.K., Casanova-Powell, T.D., Cosgrove, L., Reagan, I., et al. (2012). Evaluation of NHTSA distracted driving demonstration projects in Connecticut and New York. Report No. DOT HS 811 635. National Highway Traffic Safety Administration NHTSA, Washington D.C.

8. Allsop, R. (2013). Guidance on use of speed camera transparency data. Royal Automobile Club Foundation for Motoring Ltd RAC, London.

9. Erke, A., Goldenbeld, C. & Vaa, T. (2009). Good practice in the selected key areas: Speeding, drink driving and seat belt wearing: Results from meta-analysis. Deliverable 9 of the PEPPER project. European Commission, Brussels.

10. Goldenbeld, Ch. & Schagen, I.N.L.G van (2005). The effects of speed enforcement with mobile radar on speed and accidents. An evaluation study on rural roads in the Dutch province Friesland. In: Accident Analysis & Prevention, vol. 37, nr. 6, p. 1135-1144.

11. Høye, A. (2014). Speed cameras, section control, and kangaroo jumps - a meta-analysis. In: Accident Analysis & Prevention, vol. 73, p. 200-208

12. Aarts, L.T., Eenink, R.G., Weijermars, W.A.M., Knapper, A., et al. (2014). Soms moet er iets gebeuren voor er iets gebeurt. Verkenning van mogelijkheden om de haalbaarheid van de verkeersveiligheidsdoelstellingen te vergroten. R-2014-37A. SWOV, Den Haag.

13. Høye, A. (2013). Still red light for red light cameras? An update. In: Accident Analysis & Prevention, vol. 55, p. 77-89.

14. Ahmed, M.M. & Abdel-Aty, M. (2015). Evaluation and spatial analysis of automated red-light running enforcement cameras. In: Transportation Research Part C, vol. 50, p.130-140.

15. Lord, D. & Geedipally, S.R. (2014). Safety effects of the red-light camera enforcement program in Chicago, Illinois. Research report prepared for the Chicago Tribune, College Station, TX.

16. Pulugurtha, S.S. & Otturu, R. (2014). Effectiveness of red light running camera enforcement program in reducing crashes: Evaluation using “before the installation”, “after the installation”, and “after the termination” data. In: Accident Analysis & Prevention, vol. 64, p. 9-17.

17. Wong, T. (2014). Lights, camera, legal action! The effectiveness of red light cameras on collisions in Los Angeles. In: Transportation Research Part A: Policy and Practice, vol. 69, p. 165-182.

18. Dobbenberg, H. (2006). Effecten van roodlichtnegatie op de verkeersveiligheid en veiligheidsverhogende maatregelen. Onderzoeksrapport. Bureau Verkeershandhaving van het Openbaar Ministerie BVOM, Soesterberg.

19. Via Verkeersadvies (2005). Verkeersveiligheidsanalyses Gemeente Amersfoort. Via Verkeersadvies, Vught.

20. Bieleman, B., Boendermaker, M., Mennes, R., & Snippe, J. (2014). Hard op weg. Onderzoek naar verkeersveelplegers. In opdracht van Programma Politie en Wetenschap. Reed Business, Amsterdam.

21. Goldenbeld, Ch., Reurings, M.C.B., Norden, Y. van, & Stipdonk, H.L. (2011). Relatie tussen verkeersovertredingen en verkeersongevallen; Verkennend onderzoek op basis van CJIB-gegevens. R-2011-19. SWOV, Leidschendam.

22. Duijm, S., Kraker, J. de, Schalkwijk, M. , Boekwijt, L., et al. (2012). PROV 2011 Periodiek Regionaal Onderzoek Verkeersveiligheid. TNS-NIPO, Amsterdam.

23. Poppeliers, R., Scheltes, W. & In ’t Veld, N. (2009). Effectmeting regioplannen (perceptieonderzoek). Landelijke rapportage 2008. Onderzoek in opdracht van het Bureau Verkeershandhaving Openbaar Ministerie BVOM. NEA, Rijswijk.

24. Intomart GfK (2010). Effectmeting Regioplannen 2010: Landelijke rapportage. Een internet-onderzoek in opdracht van het Landelijk Parket Team Verkeer van het Openbaar Ministerie. Intomart GfK, Hilversum.

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Updated

28 Jun 2016

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