Case Study - DfT/HA: Virtual Motorway Simulator
Department for Transport (DfT)
Virtual motorways to help manage real life jams
Active Traffic Management (ATM) on the UK’s M42 motorway has shown how the ‘managed motorway’ approach delivers reduced congestion, better journey times and improved local air quality. This is achieved by using measures such as opening up the hard shoulder and introducing variable speed limits at peak times. Decisions made by Highways Agency traffic controllers are crucial to the effectiveness of the approach. The aims of the project were to develop a prototype procedural trainer for traffic controllers and explore the capabilities of synthetic environment (SE) technology in transport.
The result was VRSiMM (Virtual Reality Simulation in Motorway Management) which comprises:
Dr Mark Young (a Human Factors expert from Brunel University) provided expert advice on driver behaviour.
Traffic Flow Model
The traffic flow model simulates the flow of individual vehicles over the ATM section of the M42. Individual vehicles are modelled, each governed by specific rules (based on vehicle type and driver characteristics) to control its acceleration, desired speed, braking, headway and lane changing behaviour. Crucially, these rules are modified as traffic or environmental conditions change, speed limits are imposed and lanes are opened/closed.
The model generates real-time information on the location and speed of each vehicle (for use by the synthetic environment), and average speed and flow information for sections of the route.
The SE software presents a photo-realistic Virtual Reality version of the route, created using orthographically corrected satellite imagery in combination with digital terrain mapped landscape tiles. All signage, both temporary and permanent, overhead ATM speed and text displays (with active screen areas) are modelled. The road user population comprises a number of high detail vehicle models including lorries, cars, vans and motorcycles. The SE allows a range of environmental conditions to be simulated including light levels (day, dawn/dusk or night) and weather conditions (fog, rain or snow) with associated degrees of visibility.
The training system comprises a desk unit and two workstations:
The project was procured through the Technology Strategy Board's Small Business Research Initiative and has been selected as one of the TSB 's case study projects.
"An impressive and high quality piece of innovative research delivered to a tight timescale. I was particularly impressed by the speed with which the team developed a working solution in an area that was new and challenging." Mike Bull, NIU Team Leader