Use of Dashboards in Traffic Management System
Cities around the world are experiencing major traffic management challenges related to congestion, air pollution, slow journey times, and increased road accidents. However, the investment in roadside infrastructure at key junctions to monitor traffic conditions will not be able to support strategic and real-time responses unless the vast amount of traffic data are converted into actionable insights. As a result, the authorities of all the major cities are implementing various monitoring and visualization dashboards to get insights in a centralized manner.
These centralised dashboards in the Command and Control Center has been the current or most commonly used means of controlling the traffic, while any improvement is being done through post-facto statistical analysis of the traffic data, presenting in suitable formats and taking future decisions, considering the advantages and disadvantages. In this case, what we are typically doing is collecting traffic data through sensors and IoT devices, and presenting the data to the stakeholders in various pre-defined forms, tables and graphs without any embedded intelligence that are intuitive enough to take decisions on the fly. Moreover, it has been observed that the big centralised dashboards with all the data and representations are sometimes scary and difficult to understand, relate and effectively utilize by the users.
Most of the times they are designed for business experts and analysts and don’t make the required impact on the actual users or professionals, who are not necessarily experts in analytics. So, they face a challenge in the adoption of these analytical dashboards in their everyday work life and make intelligent and contextual decisions out of the collected data.
Read this: Singapore’s Intelligent Transport System
How we can overcome the limitations of traditional Dashboards
Normal users of the traffic management systems are actually in need of actionable and easily interpretable insights from the traffic data so that they can make the effective and intelligent decisions on the fly, and don’t have to wait till the end when all the traffic data will be collated, analysed and graphically represented to them for their interpretation and decision-making. They are usually indifferent to the underlying technology platform or the rich look and feel or the interactiveness of the dashboards. Their key objective is to respond fast and in a predictable manner for road incidents in order to streamline the flow of traffic.
In this regard, it will be more effective if we can embed the insights, either one insight at a time or a collection of insights together, within the normal flow of the traffic operations and management system in context. This would help to generate the actionable and easily interpretable insights in the course of the traffic operational flow, as and where required, and enable the users to make decisions on the fly during the process. The users will thereby have much improved, near real-time control and prediction on the traffic flow in order to reduce congestion and accident occurrence as well as optimize the overall traffic system and its dependent business processes, which is of great economic benefit.
This can have a massive difference in the adoption and effective use of analytics in traffic management system and reap the underlying benefits. However, cyber security, system scalability, data privacy concerns and platform standardization, as well as feedback analysis and mistake-proofing are some of the key challenges to be addressed in order to make this successful and sustainable.
