Traffic management (re)directs traffic flows over the road network with the aim to optimise movements of people and goods in terms of reliability, safety and environmental sustainability. Measures of traffic management become increasingly important because road mobility continues to increase while the mobility demand increases faster than the increase in road capacity. This leads to increasing road network density and an aggravating congestion problem. However, if designed and applied without accounting for human strengths and limitations, the traffic management measures will not have optimal results in terms of throughput and traffic safety. Hence, to achieve high compliance rates for traffic management measures, human factors must be addressed.
This study identifies current best practices as well as knowledge gaps in the area of human factors considerations in traffic management. A literature review on road user needs and behaviours in relation to traffic management points out five key human factors which influence traffic behaviour and related choices:
1. Perception
2. Comprehensibility
3. Skills
4. Willingness
5. Behavioural adaptation
Four of these aspects are conditional for achieving the desired road user behaviour: perception, comprehensibility, skills and willingness. The fifth human factor aspect concerns behavioural adaptation: the collection of behaviours that occur following changes in the road traffic system which were not intended and negatively impact road safety.
The questionnaire survey amongst 11 traffic management and human factors experts across Belgium-Flanders, Denmark, Finland, the Netherlands, Norway and the United Kingdom gains insight into the deployment and effectiveness of current traffic management measures in practice, current use of human factors thinking as standard practice when designing traffic management and potential cultural differences in this respect.
The inventory shows that many practices and experiences of traffic management measures are applied in these 6 countries. Dynamic speed management measures such as dynamic speed limits and variable message signs are most often implemented. Most types of traffic management measures are found in the Netherlands and the fewest in Finland. In the Netherlands traffic management measures are also most frequently applied.
Traffic management measures are assessed to be fairly effective. However, some relevant differences in effectiveness parameters (e.g. improving traffic flow, reducing accidents and cost effectiveness) between clusters of traffic management measures and between countries exist. Local traffic flow management measures are assessed as the most effective cluster of traffic management measures closely followed by dynamic speed management. Further, some between-country differences in the effectiveness assessment were found with Finland assessing their traffic management as most effective and the Netherlands as less effective.
Country experts indicate that the five key human factors are used as standard practice when designing traffic management in Belgium, Denmark and Finland. The Netherlands and the United Kingdom show differences between the use of these human factor aspects as standard practice. Across the countries in this study traffic management operators most frequently use perception and comprehensibility as standard practice when measures of traffic management are designed.
Although most countries indicated (to a different degree) use of human factor aspects as standard practice when designing traffic management measures, the Netherlands is the only country that actually provides documentation on the specific framework used. The 10 Golden Rules (Dutch Ministry of Infrastructure and the Environment, 2008) and the Human factor in Traffic Management framework (Harms, 2012) used in the Netherlands are the best practices found across the six European countries. Both documents can be used as relevant input for Work Package 2 of the METHOD project.
The lack of relevant evaluation studies as a source for the effectiveness assessment of traffic management measures currently applied in the 6 countries and the lack of official documentation and frameworks on the use of human factors as standard practice for designing traffic management are shortcomings of this study. The effectiveness assessments can be dependent on the relatively small sample of experts that were interviewed. Carrying out more interviews with different experts is recommended in further research. This will also contribute to collect more relevant human factors documentation used for designing traffic management measures.
