Establishing the current road type constitutes a significant assistance to car drivers, as, by default, the road type determines the legal speed limit. Although there are GPS- and map-based navigation systems that can retrieve the actual road type and speed limit and some can even access and indicate current traffic volumes, it was our aim to develop and test a software prototype of a road-type detection (RTD) system that relies solely on video and sensor data collected on board. Such a system can still work during GPS signal outages. The study presents a heuristic approach to RTD that is based on type and distance data relating to traffic control devices (TCDs) installed along a road. The road is used by an ego vehicle with an on-board smart camera looking ahead and with a number of vehicular sensors. A complex processing step—not detailed in the study—detects TCDs with reasonable probability and error rate and locates them with respect to a 3D coordinate frame fixed to the ego vehicle. The prototype system takes data describing the detected TCDs as its input. This data are then evaluated in a multiscale manner by computing empirical statistics of occurrences over short, medium, and long patches of road. Such an evaluation is carried out in conjunction with each considered road type, and the resulting values are compared to respective reference values. Heuristics is then used in decision-making to resolve any interscale and interroad-type disaccords. The proposed decision rules take into account the possibility of TCDs having been missed and of faulty detections. Short preprocessed synchronised video and signal sequences recorded in different countries and road environments were used for testing the prototype system. These short sequences were carefully strung together into coherent chains. Distance-based recognition precisions 78.9% and 88.9% were gained for European (continental) and for UK roads, respectively.


    Access

    Download


    Export, share and cite



    Title :

    Road-Type Detection Based on Traffic Sign and Lane Data


    Contributors:


    Publication date :

    2022




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown





    GLARE PREVENTING TYPE ROAD SIGN BOARD AND TRAFFIC LANE DISCERNING DEVICE FOR MOTORS

    KIM SUG BAE / NAM JIN SOO / HA HONG KI et al. | European Patent Office | 2017

    Free access

    Road sign detection-based driving lane estimation method and apparatus

    JUNG HO GI / SUHR JAE KYU / CHO GAE HWAN | European Patent Office | 2016

    Free access


    Road traffic sign detection and classification

    Escalera, A. de la / Moreno, L.E. / Salichs, M.A. et al. | Tema Archive | 1997