The impact of pre-trip and on-trip traffic information on network performance: case of the Amsterdam network

Road networks make an important part of society and are essential for movement of people and goods. These road networks however also pose negative effects on society one of which is congestion. Congestion of road networks leads to losses especially of time and money and has adverse environmental implications. Information technology is a concept that has found its way into modern society and advancements and new innovations in the sector are emerging more often. The application of this technology in solving traffic related problems like congestion is something has been done and more research into it is going on. One of the ways the technology is being applied is using it to provide traffic information through the advanced traveler information system (ATIS) applications. The provision of this traffic information is done through various means one of which is use of smartphones that are gaining popularity around the world. This whole direction is adopted in traffic management because of the change in trend from just increasing road network capacities to cater for increased traffic to the efficient management and use of existing network facilities. This new technology and its application require testing prior to implementation because of the investment costs that go into making it a reality. To do the tests, carrying out traffic simulations and determining the impact of intended developments is one way to research into the expected impact of traffic information on road network performance. The objective of this research was to determine the impact of on-trip and pre-trip in-vehicle travel time information on network efficiency. The Amsterdam road network was used as the case study area. The Amsterdam road network and the associated demand during the morning peak period of a normal work day were used as a test case. The highway part of the area network was used and the traffic demand for the section was created. The network complete with the demand was then used to run simulations for the cases without information and the cases with information. On-trip and pre-trip information were implemented on the network and relayed to the drivers. The output was then analyzed to determine the efficiency of the network with and without the information. The information being in-vehicle, penetration rates were considered important and different rates were tested under various traffic conditions. The conditions under which the information was tested were varied to replicate occurrences in traffic that could lead to increased demand like accidents/incidents, road works and or events.