Dedicated lanes for connected and automated vehicles (CAVs) can not only provide the technological accommodation, but also the desired market incentive for road user to adapt CAVs. Thus far, the majority of the impact assessment of CAV focused on the network-wide benefits. In this paper, we investigate the change of the traffic flow characteristic with two configurations of dedicated CAV lane across levels of market penetration. The traffic flow characteristics are quantified from the perspectives of headway distribution, communication density, and speed-flow diagram. The results highlight the contributions of the CAV lane. First, CAV lanes significantly improves the speed-flow characteristics by extending the stable region of the speed-flow curve and yielding a greater optimum flow. The highest value of optimum flow is 3400 vehicle per lane per hour at 90 MPR with one CAV lane. Furthermore, the concentration of CAVs at a lane results a narrower headway distribution (with smaller standard deviation), even with partial market penetration. Moreover, the CAV lane creates a more consistent CAV density which maintains the communication density level at a predictable level, hence decreasing the probability of packet drop.
An analytical modeling framework for assessing the benefits of CAV operations was proposed in @cite_10 . The overall results indicated that CAV improved network mobility performance, when the MPR was low, even in the absence of ML policies. Throughput without managed lane increased by 4 Nearly all of the previous studies evaluated the benefits of CAV at a aggregated level with the emphasis of the overall improvement. In this paper, we further the impact analysis to a traffic flow level, aiming to investigate the traffic flow characteristic with the presence of CAV lanes.
@cite_10
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Automated vehicles have the potential to bring about transformative safety, mobility, energy, and environmental benefits to the surface transportation system. They are also being introduced into a complex transportation system, where second-order impacts, such as the possibility of increased vehicle-miles traveled, are of significant concern. Given the complexity of the impacts, a modeling framework is needed to ensure that they are adequately captured. This report presents a framework for estimating the potential benefits and dis-benefits of technologies contributing to the automation of the Nation’s surface transportation system. Components of the framework include (1) Safety: exposure to near-crash situations, crash prevention, and crash severity reduction; (2) Vehicle mobility: vehicle throughput, both in car following situations and at intersections; (3) Energy environment: fuel consumption and tailpipe emissions; (4) Accessibility: personal mobility, for motorists and nonmotorists; (5) Transportation system usage: response of travelers to changes in mobility and accessibility, as well as potential new modes of transportation such as increased car sharing; (6) Land use: effects of automation on land use, and (7) Economic analysis: the macro-economic impacts of all of the above changes.