Early and forward-looking traffic forecasts provide reliable information for road operators and users. It is an important foundation for good management of the road network.
The predictive power of current models is not sufficiently reliable to use for timely decisions on traffic management measures or for use by road users planning their routes. The short-term forecasts used today are generally based on current market sizes (online data) that are projected to the near future based on data known from the past.
The road user knows his goal as a rule at the start of his journey. When setting out on his journey, a 'real' forecast is thus available. It might be recognised immediately at the start of driving and a large sum of individual origin-destination relationships (desire lines) might serve as a basis for forecasting future continuous data.
The questions of whether and to what extent such data can be improved, of what data sources for the online traffic forecast can be compared with conventional forecasting algorithms and improved qualitatively, of which data are available or could be generated, has not been studied.
Today the quality of traffic forecasts is often not sufficient for operational decisions within a traffic control centre, neither for prompt (real-time) traffic control measures nor for reliable traffic information, e.g. for navigation systems.
This project aims at improving traffic forecast quality. It figures out how an increase of forecast quality can be obtained, which data and data quality is necessary for this and a clarification of the technical and organisational aspects for data gathering and distribution as well.
The main purpose (in the scope of traffic management) is to get an improved short term traffic forecast on a local, regional and national level. Further expected results:
- Proposal for adoptions of the legal basis or regulations concerning data availability and the conditions for data use (which has been originally gathered for other purposes).
- Business model that creates a “win situation” for the distributor and receiver of this data.
- Proposal for standardisation concerning data quality requirements.
Beneficiaries of this research are road operators, traffic and system engineers, ITS manufacturers and road users.
The following steps took place:
Step A Part of transport planning: Desk research, interviews / workshops with experts
Step B Technical part: Desk research, interviews with system operators
Step C Organizational and legal aspects: Interviews / workshops with legal experts, privacy advocates, selected data-owner and operators of navigation devices, Directorate General of Customs, etc.
Step D Final Report: Summary of results
The research brought the involved stakeholders and user groups together, which yielded the following benefits:
Road operators obtained information about the data sources for a traffic forecast that are practical and purposeful and they result in a more reliable traffic forecasts, and findings about what needs to be considered at the data and legal conditions. Reliable traffic forecasts allow to respond proactively to expected traffic congestion, in this way to avoid, delay or reduce. Thus increased efficiency and optimal use of the existing capacity in its network can be achieved by various early initiated traffic management measures.
The traffic planners and / or system designers got information about what to consider when planning and what fundamental ways there are to build a traffic forecast (data, interfaces, etc.).
The system manufacturers / suppliers received information on the transportation-functional requirements for online forecasting models on the technology to be used, about possible restrictions in the infrastructure, but also about the data flows and system interfaces.
The road users as users of the transport system obtained improved prognosis online and more reliable traffic information.
Julien Bauer, B+S Banksysteme Aktiengesellschaf: Verkehrsprognosen mit Online-Daten: Forschungsauftrag VSS 2007/905 auf Antrag des Schweizerischen Verbandes der Strassen- und Verkehrsfachleute (VSS). Eidgenössisches Departement für Umwelt, Verkehr, Energie und Kommunikation, Bundesamt für Strassen – Vol. 1363
Information for the road users based on precocious, anticipatory and reliable data provided by a traffic control centrum is the essential base for an optimal management of road networks. The methods for short term traffic forecasting are always based on real time traffic data (online data) and its projection to the near future using known regularities from past experiences (variation curves) and in an optimal way individual “future directed” data in addition. These “future directed” data are origin-destination-information resp. planned routes.
Under what conditions are road users willing to provide their origin-destination- information resp. planned routes to the traffic management in real time? Road users want fast and reliable routes, road operators aim to reach an efficient use of their road infrastructure and navigation providers like to generate an additional value for road users. These goals are most likely seen to be achieved within a cooperation of the three stakeholders (business model, chapter 3). Road users provide online data of the real time traffic flow (Floating Car Data; FCD) via their GPS- (Geo Positioning System) navigation system and mobile telephone system to the service provider. The planned destinations resp. routes are additionally added to this information. The service providers transfer these data anonymously to the road operators in charge resp. the traffic management. Within there, the real time and dynamic traffic model is updated by using the online data from stationary sources (such as inductive loops, speed measuring etc.) and section- related traffic data (FCD). The traffic model projects an area wide view of the traffic situation. In case of adequate quality and quantity of input data, there is also the opportunity to include a traffic forecast after the estimation of the traffic state. The traffic management can minimize forecasted or current traffic bottlenecks by implementing specific measures. The measures involve directly routing of the road users to time saving back-up routes. The routing is done via appropriated signalization or via navigation devices (service providers).
Useful short-term-forecasting methods are selected based on the requirements of the traffic management, the users and the service providers and the specific application area (chapter 4). It is seen that models including dynamic traffic assignment and self-learning (ability) are most effective for area-wide applications. Chapter 5 provide