Throughout Project 1 different ramp metering strategies were used and simulated in order to analyse their benefits or disbenefits to the network. There were several issues regarding the ramp metering strategies implied into the network which will be discussed in this report. A cost benefit analysis will also be discussed involving travel time savings and vehicle operating cost savings.
Issues not considered in group report
• Freeway management techniques
Freeway management techniques allow to maximise traffic flow for vehicles on the on-ramps and freeway mainline. These techniques if successful will lead to increasing vehicle speeds on the freeway and reducing total travel time of vehicles. With the developing of urban framework, latent demand and environmental regulations, the addition of lanes is not the optimum solution to reduce congestion. Hence, freeway management techniques are now a widely accepted management tool for traffic networks around the world.
Ramp metering was the freeway management technique used throughout Project 1. Although, there were several other techniques which could have been implemented in order to reduce congestion and improve the travel time and speeds. Common management techniques for reoccurring traffic conditions include Mainline control, Priority control, Corridor control, Transit subsidies, restriping. These freeway management techniques could have been implemented into the project to further improve congestion which occurs “daily” at the same location (peak hour periods).
For e.g. in mainline control, vehicles are regulated, notified and guided by overhead lane control signals or variable speed control, in order to obtain a more optimum and efficient traffic flow.
Another e.g. of a management strategy which could have been implemented is priority control. The purpose of this technique on a freeway is to provide treatment to prioritise for HOVs (High-occupancy vehicle lane) such as carpools, vanpools, and buses. HOV facilities have proven to increase travel time savings and preserve mobility in congested freeway sections.
As these strategies were not considered in the project, the model in Aimsun will not function as efficiently as the existing network would.
• Handling stochastic variations in traffic
The issue of Stochastic variation in traffic involves the random fluctuations in the number of vehicles that travel along a network. The random fluctuation causes travel time uncertainty in the traffic network, thus leading to issues in the existing ramp metering system.
These conditions include stochastic events such as freeway incidents or special events. This type of congestion is unpredictable and could cause a major hazard and significant delays/queues for travellers on the freeway, on-ramp and arterial roads.
The ramp meters which were added into the network on Aimsun do not account for non-reoccurring traffic conditions. In the Aimsun model, vehicles arrived at a constant rate and traffic was modelled from 4-5pm in project 1. With non-reoccurring conditions, the ramp meters in the network would not be able to predict when they should turn off/on due to the random fluctuations. The Aimsun model was limited in terms of simulating possible stochastic events and their effects on the network.
In order to improve these non-reoccurring traffic conditions certain freeway management techniques could be used. These include; events road managements, incident management, traffic surveillance and SMARTS corridors.
• Safety Concerns
The installation of ramp metering also has some concerns in regards to the safety of travellers. A major safety issue with ramp metering is the potential for rear-end collisions when traffic stops. This issue is lessened with the use of warning signs placed in advance of the metering point. When applying the ramp metering in Aimsun warning signs were not added before the ramp meter point. By adding warning signs, it would be able to decrease the possibility of any rear-end collisions in the network, significantly improving the safety for travellers. Thus, this safety technique should have been implied into the Aimsun network.
• Combinations of setting
Different combinations were available when setting the ramp meter on Aimsun in the project. Limitations could exist here if not enough combinations were simulated when setting the ramp meter. A broad range of combination should be tested, in order to achieve a higher accuracy in terms of the optimum ramp metering choice.
• Network-Wide Ramp Metering Methods
Project 1 involved only local ramp metering strategies to be trialled and tested in the model. Green-time, delay, FLOW and ALINEA were all ramp metering strategies based on a local level. Once these were simulated and the results were analysed it seemed that the only benefits of the ramp meter were on a local level. Therefore, in order to achieve network-wide benefits more than one ramp meter should have been used throughout the model network.
• Route choices
In the project, the Aimsun model does not account for the options for vehicles to change routes. The model vehicles are already pre-programmed into the network and are not able to change routes to avoid congestion. Therefore, causing the model outputs from Aimsun to not be as optimal as those that would be achieved on the real-life network were drivers could change their routes to the destination.