AmI Technology Helps to Sustain Speed While Merging - A Data Driven Simulation Study on Madrid Motorway Ring M30

Abstract

A considerable increase in road traffic has provoked a total change in the operating paradigms of vehicles, shifting vehicle handling from “just steering” towards a complex adaptation task. With the emergence of wireless communication technology, vehicle operation can now incorporate for the first time ever beside the local driver-vehicle interaction also more significant information obtained from cars in the surrounding. With this foundation it would be possible to build collectively operating driver assistance systems, negotiating the interests of all road participants in a certain area with the final goal to improve global parameters such as road throughput or traffic fluidity, also having an effect on the individual car (driver), e. g. increased travel speed, less congestions, or a reduced level of cognitive load. The question addressed with this paper is whether or not the vehicle speed can be sustained while merging onto a motorway, leading to a more harmonious integration of the merging cars into the flowing traffic on the main road. To achieve this we propose the application of ambient intelligence (AmI) technology operating on the collective behavior of all cars in the periphery of the entrance ramp. To prove our hypothesis we applied the AmI technology to a data driven, true to scale simulation model of the Madrid motorway M30, one of the most busiest roads in Spain. The comparison of simulation runs with high volume of traffic showed that technology assistance could help to increase road throughput and minimize the variance of traffic flow, but on the other side demands solutions for one of the bigger problems of data driven simulation – missing or noisy data compromising simulation results.