In a freeway network, traffic congestion initiates at active bottlenecks, when the upstream traffic demand surpasses the downstream capacity. One feature of active bottlenecks is that the upstream freeway is congested, but the downstream carries free flow. Such active bottlenecks can occur at lane drops, merges, tunnels, slopes, and so on. Another distinctive feature is that the maximum discharging flow-rate (or capacity) can significantly drop when a bottleneck is activated. This will further reduce the upstream travel speeds, leads to stop-and-go traffic patterns,  and increase fuel consumption and vehicle emissions. For example, the merge between I-405S and the Jeffrey Road on-ramp, shown in Figure 1, is an active bottleneck in the afternoon peak period between 5 and 7 pm. Observations from the three loop detectors confirm that the maximum discharging flow-rate can reach 8800 veh/hr for the four regular lanes rate before the on-rise of congestion, but drops to 8000 veh/hr after the bottleneck is activated. This represents a 9% drop in capacity, almost half of a lane’s capacity. The average travel speed drops from 40 mph to 25 mph, causing stop-and-go patterns in the upstream congested traffic. Such a capacity drop can increase travel time, fuel consumption, and vehicle emissions, in addition to creating safety issues. Since the Jeffrey Road on-ramp has quite high flow-rates during the peak period, such capacity drop still occurs with activated on-ramp metering. Therefore other strategies are needed in order to delay or prevent the occurrence of capacity drop. Traditional variable speed limits on the mainline freeway can be helpful to achieve the goal. As an alternative, in this research, we propose to investigate In a freeway network, traffic congestion initiates at active bottlenecks, when the upstream traffic demand surpasses the downstream capacity. One feature of active bottlenecks is that the upstream freeway is congested, but the downstream carries free flow. Such active bottlenecks can occur at lane drops, merges, tunnels, slopes, and so on. Another distinctive feature is that the maximum discharging flow-rate (or capacity) can significantly drop when a bottleneck is activated. This will further reduce the upstream travel speeds, leads to stop-and-go traffic patterns,  and increase fuel consumption and vehicle emissions. For example, the merge between I-405S and the Jeffrey Road on-ramp, shown in Figure 1, is an active bottleneck in the afternoon peak period between 5 and 7 pm. Observations from the three loop detectors confirm that the maximum discharging flow-rate can reach 8800 veh/hr for the four regular lanes rate before the on-rise of congestion, but drops to 8000 veh/hr after the bottleneck is activated. This represents a 9% drop in capacity, almost half of a lane’s capacity. The average travel speed drops from 40 mph to 25 mph, causing stop-and-go patterns in the upstream congested traffic. Such a capacity drop can increase travel time, fuel consumption, and vehicle emissions, in addition to creating safety issues. Since the Jeffrey Road on-ramp has quite high flow-rates during the peak period, such capacity drop still occurs with activated on-ramp metering. Therefore other strategies are needed in order to delay or prevent the occurrence of capacity drop. Traditional variable speed limits on the mainline freeway can be helpful to achieve the goal. As an alternative, in this research, we propose to investigate distributed ecodriving strategies based on inter-vehicle communications (connected vehicle technology) to improve the performance of active bottlenecks.
In this research, we will carry out the following studies. First, we will set up a simulation platform by integrating microscopic simulation models of car-following, lane-changing, and merging traffic flow, inter-vehicle communication, and a vehicle emission module. Second, we will develop an ecodriving strategy of individual variable speed limit (IVSL) based on local traffic information shared through inter-vehicle communication. Third, we will quantify the impacts of ecodriving strategies and market penetration rates of connected vehicles on travel time, fuel consumption, and vehicle emissions.