Abstract
Recently, radar technology has attracted attention for the realization of an intelligent transportation system (ITS) to monitor, track, and manage vehicle traffic on the roads as well as adaptive cruise control (ACC) and automatic emergency braking (AEB) for driving assistance of vehicles. However, when radar is installed on roads or in tunnels, the detection performance is significantly dependent on the deployment conditions and environment around the radar. In particular, in the case of tunnels, the detection accuracy for a moving vehicle drops sharply owing to the diffuse reflection of radio frequency (RF) signals. In this paper, we propose an optimal deployment condition based on height and tilt angle as well as a noise-filtering scheme for RF signals so that the performance of vehicle detection can be robust against external conditions on roads and in tunnels. To this end, first, we gather and analyze the misrecognition patterns of the radar by tracking a number of randomly selected vehicles on real roads. In order to overcome the limitations, we implement a novel road watch module (RWM) that is easily integrated into a conventional radar system such as Delphi ESR. The proposed system is able to perform real-time distributed data processing of the target vehicles by providing independent queues for each object of information that is incoming from the radar RF. Based on experiments with real roads and tunnels, the proposed scheme shows better performance than the conventional method with respect to the detection accuracy and delay time. The implemented system also provides a user-friendly interface to monitor and manage all traffic on roads and in tunnels. This will accelerate the popularization of future ITS services.
Highlights
As the traffic environment and transportation have been improved, the number of roads and tunnels interconnecting cities has increased
The optimal deployment conditions were derived requirements of radar (e.g., Delphi ESR) and designs an architecture in consideration of road by and considering the installation height, tilt angle and so forth, which have the greatest influence on the tunnel environments
The optimal deployment conditions were derived by considering performance of radar as environmental factors on the road surface
Summary
As the traffic environment and transportation have been improved, the number of roads and tunnels interconnecting cities has increased . The authors of Reference [16] present a mapping technique based on measurements from automotive radar to enhance automotive safety functions, for instance trajectory control These works mainly focus on the identification of bridges, guardrails or railway structures and do not consider vehicle tracking in the tunnel. These methods can obtain both the accuracy and the short measurement time in order to tackle the ghost image problem, they mainly focus on RF front-end design and do not deal with the noise filtering over the application layer They do not guarantee good detection performance in tunnel environments.
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