Using risk analysis to prioritise intelligent transport systems: a variable message sign case study on the Gold Coast

With perpetual strains on resources, road agencies need to develop network-level decision-making frameworks to ensure optimum resource allocation. This is especially true for intelligent transport systems (ITS), and in particular, variable message signs (VMS), a key component of incident management services. The objective of VMS is to minimise the safety, efficiency, reliability and environmental impacts of incidents on the operations of the transport system. This may be achieved by informing travellers of the incidents so they can adapt their behaviour in a manner that reduces community impacts, such as lateness and the associated vehicle emissions, unreliability of travel times, as well as secondary accidents due to incidents. Generally, road authorities do carry out needs assessments, but qualitatively in many cases. Therefore, this paper presents a framework that is systematic, quantitative and relatively easy to implement. A risk management approach which focuses on minimising the impacts on, and costs to, the community, was taken to prioritise VMS infrastructure deployment. In the framework and case study presented in this paper, safety, efficiency, reliability and environmental impacts are quantified using an economic risk management approach to determine an overall risk score. This score can be used to rank road sections within the network, indicating the road sections with the highest risk of incident network impacts and therefore the road sections with the highest need for intervention. A cost-effectiveness based risk-reduction ranking can then be determined for VMS, comparing the net risk with treatment to that without treatment, and dividing by the net present value of deployment. The two types of ranking, pure risk and cost-effectiveness based risk reduction, will help to minimise the network impacts on the community and optimise resources allocation.