Can highly automated vehicles fare better than traditional cars in traffic gridlock conditions? Cooperation between vehicle intelligent transport systems via connected vehicles may provide a solution.
Drivers’ and passengers’ safety and convenience is at the heart of the development of highly automated vehicles. Yet, despite conjuring up the image of free-flowing city streets, automated vehicles will not mean the end of congestion unless proper traffic management concepts are applied.
Spurred by the potential of emerging intelligent vehicle automation and communication systems (VACS) the TRAMAN21 project which was funded by EU’s European Research Council worked on new traffic management methods and tools suitable for the era of connected transport. The idea is to ensure that traffic flows as smoothly and efficiently as possible potentially avoiding the jams and delays caused by human behaviour.
New models spanning both micro and macro scales
Traffic flow modelling based on VACS is key to the design and testing of efficient traffic management approaches. Vehicle trajectories, time and distance headways are the most important microscopic traffic flow characteristics. Researchers argue that managing individual vehicle behaviour can influence the macroscopic traffic flow characteristics – intensity, density and speed. “Adjusting properly microscopic vehicle movements provides a means to improve the overall traffic flow of city roads,” notes Professor Markos Papageorgiou, head of the Dynamic Systems & Simulation Laboratory at the Technical University of Crete, Greece.
Building on Aimsun Next traffic modelling software, researchers tested the impact of selected onboard cooperative technologies on the vehicle microscopic behaviour. The simulator conducted traffic operation assessments on a large network scale. In addition, they developed advanced first and second-order macroscopic traffic flow models and novel numerical approaches for approximating them. The methodologies were extended to handle multi-lane highways and mixed traffic.
Not only automated, but also cooperative
Traditional stationary sensors collect traffic data of vehicles passing the location in which they are installed on the highway. “Connected and automated vehicles represent a new traffic data source that will be more common in the near future. Mobile data collected by the distributed mobile sensors from vehicles equipped with intelligent technology will not only measure traffic information but also communicate it in real time,” says Prof. Papageorgiou. TRAMAN21 developed reliable and robust traffic flow estimation methods that outperform the state of the art in terms of accuracy and simplicity.
An innovative traffic control concept that was developed and tested in TRAMAN21 was cooperative merging. The system assists drivers in lane-changing manoeuvres in areas where lanes end or merge by creating and maintaining an appropriate time or space gap in traffic for the merging car.
Researchers also looked at how adaptive cruise control can improve traffic flows. The technology adjusts time gaps between cars to cut congestion and reduce phantom traffic jams.
Combining conventional highway control systems
Today’s motorway traffic control practice applies control measures independently of each other, and, for some of them, there is no evidence that they have any positive contribution to congestion mitigation. “Field implementation of novel control strategies that employ ramp metering and variable speed limits in an integrated way can lead to significantly improved travel times, fuel consumption, environmental pollution and traffic safety,” notes Prof. Papageorgiou.
TRAMAN21 has been running tests on a highway near Melbourne, Australia, and is currently using variable speed limits and ramp metering to actively intervene in traffic to improve flows. Researchers expect that tests will prove successful in offering a smoother and more efficient journey for motorists.
Markos Papageorgiou is a Professor at the Technical University of Crete, Chania, Greece. After receiving the Diplom-Ingenieur and Doktor-Ingenieur degrees in Electrical Engineering from the Technical University of Munich, he worked in Germany and France and was a Visiting Professor in Italy and the USA among others. His research focuses on automatic control and optimisation theory and applications to traffic and transportation systems, water systems.