The effectiveness of managed lane strategies for the near-term deployment of cooperative adaptive cruise control

Abstract

Traffic simulation is a cost-effective way to test the deployment of Cooperative Adaptive Cruise Control (CACC) vehicles in a large-scale transportation network. By using a previously developed microscopic simulation testbed, this paper examines the impacts of four managed lane strategies for the near-term deployment of CACC vehicles under mixed traffic conditions. Network-wide performance measures are investigated from the perspectives of mobility, safety, equity, and environmental impacts. In addition, the platoon formation performance of CACC vehicles is evaluated with platoon-orientated measures, such as the percentage of platooned CACC vehicles, average platoon depth, and vehicle-hour-platooned that is proposed in this paper under the imperfect DSRC communication environment. Moreover, managed lane score matrices are developed to incorporate heterogeneous categories of performance measures, aiming to provide a more comprehensive picture for stakeholders. The results show that mixing CACC traffic along with non-CACC traffic across all travel lanes is an acceptable option when the market penetration (MP) is lower than 30% for roadways where a managed lane is absent. Providing CACC with priority access to an existing managed lane, if available, is also a good strategy for improving the overall traffic performance when the MP is lower than 40%. When the MP reaches above 40%, a dedicated lane for CACC vehicles is recommended, as it provides greater opportunity for CACC vehicles to form platoons. The facilitation of homogeneous CACC traffic flow could make further improvements possible in the future.

Influence of CAV clustering strategies on mixed traffic flow characteristics: An analysis of vehicle trajectory data

“…The string formation and dispersion mechanism were integrated to the model of Lee et al in an NCHRP study (Transportation Research Board, 2018), including preferential lane logic and platoon size restriction. A CACC control model was developed by Zhong (2018), where E-IDM (Kesting et al, 2010) was adopted jointly with the MOBIL model (Kesting et al, 2007) that prevents the lane changing of a free-agent CAV, which may be potentially disruptive to the surrounding traffic. When a potential platooning opportunity is identified via V2V communication, the CACC system estimates the impacts on the immediate vehicles based on MOBIL should the lane change be initiated.…”

A Safety Collision Avoidance Algorithm Based on Comprehensive Characteristics

“…DSRC is an efficient wireless communication technology that can quickly identify high-speed moving targets and two-way communication within a short distance [21], enabling wireless communication between vehicles and vehicles and vehicles and roads in intelligent transportation systems [22]. DSRC can provide a high data transmission speed, ensuring the low latency and low interference in the transmission process [23].…”

Clustering Strategies of Cooperative Adaptive Cruise Control: Impacts on Human-Driven Vehicles

“…The longitudinal control was a rule-based acceleration selection. Developed from Lee et al's coordination model, Zhong et al [14] implemented the MIXIC [4] as car following model to study the CAV benefits for arterials. Lee et al's [2] CACC algorithm was updated to using the EIDM for simulating CACC string behavior.…”

“…The string formation and dispersion mechanism were enhanced, including preferential lane logic, platoon size restriction [15]. Zhong [16] developed a CACC control model by combining E-IDM and the MOBIL model [17]. The MOBIL model is adopted as the mechanism to prevent lane changing of a free-agent CAV that may be potentially disruptive to the surrounding traffic.…”