M25 Stopped Vehicle Detection (SVD) Click on the picture icon or drag an image to add it to the picture placeholder. Then, send it to back by selecting the image and going to the menu “Format > Send to back”, so the logo can be visible. M25 Stopped Vehicle Detection (SVD) Introduction to SVD

Background Problem: Vehicles stopping in live lane on Smart Motorways All Lane Running (SM-ALR) Solution: Radar technology detects stopped vehicles and provids alerts to RCC, en.abling early operator intervention

SVD Radar Schemes M25 J5-6, 27 radar sites,13 km of ALR Smart Motorway Go Live January, 2016 M25 J23-27, 46 Radars covering 25.4 km of ALR Smart Motorway Go Live April, 2018

RCC Operation Integration Hazard warning Incident verification Operational Assessment Stopped Vehicle Detection Incident Alert notification Contains sensitive information

Navtech Radar The units employ a fully enclosed rotating scanning mechanism that continuously scans 360 degrees around the radar four times per second.

The Radar Detector Specification ClearWay CTS350 Operating Frequency 76 – 77GHz Range Resolution 25cm Azimuth Beamwidth 1.8° Measurement Rate 400 per rotation Elevation Beamwidth Spreadbeam Field of View 360°

Planning Coverage A 3D Model is used to plan the radar locations

Future Developments…… SVD Application Algorithms for MIDAS system ? Connected and Autonomous Vehicles Integrated Solution

MIDAS Traditional sensors on UK Motorways for Queue Detection and Congestion Management applications are positioned every 500m If an incident occurs, shown by the red cross on the picture, a resulting traffic queue will be travelling in the opposite direction to traffic. When the queue reaches the first sensor, side-fire radar A in this case, the MIDAS system will initiate signal sequence plans for setting speed limit of 40mph, starting from the signal A.

Combining SVD application with MIDAS Select two SVD sites at the existing M25 J23-27 scheme Update the SVD system with queue detection algorithms Generate off-line MIDAS alerts Verify the results using CCTV as a ground truth and compare with the existing MIDAS.