Dash Navigation‘s recent decision to stop marketing its traffic-centric, subscription-based, connected PND confirms the low perceived value of traffic service, according to ABI Research. “Current traffic solutions suffer from a lack of quality and reliability, with dissatisfied customers increasingly reluctant to keep paying recurring fees, according to ABI.

“While there is certainly an issue with convincing consumers to pay monthly fees for navigation content services, in the case of traffic the priority should be to increase the value of the offer before exploring new business models,” says ABI Research director Dominique Bonte.

“Predictive traffic makes time-dependent routing possible and provides customers with more trustworthy information, allowing them to prepare their trips more efficiently on Internet mapping sites and to calculate a more accurate Estimated Time of Arrival (ETA).

NAVTEQ recently launched NAVTEQ Traffic Patterns North America v4.0, including typical traffic speeds on nearly one million miles of primary and secondary roads across the United States, Puerto Rico and Canada. The firm said its traffic data improves travel time accuracy by an average of 41% when compared with typical speeds and posted speed limits on freeways and surface roadways.

NAVTEQ Traffic Patterns is based on multiple years’ observations from GPS probe and sensor data that is aggregated, verified and matched to traffic location codes in the NAVTEQ Map database. Routing applications incorporating NAVTEQ Traffic Patterns give drivers the information they need to decide when and how to avoid typically congested areas. It enables more accurate route planning and improves trip time estimates based on likely traffic conditions.

UK-based Journey Dynamics recently launched traffic speed forecasts for cars and trucks in the UK. It provides greater confidence in the routes selected and journey times enabling consumers and professionals such as logistics companies to avoid congestion and reduce fuel consumption.

According to ABI, INRIX and TrafficCast are also working on predictive traffic models based on historical and real-time speed profiles complemented with weather forecasts, planned events and driving behavior profiles.

Predictive traffic information does not require connected hardware because compact datasets and modeling software will be available for embedded navigation solutions, but connectivity allows the use of more powerful off-board modeling and access to real-time inputs.