The study proposes a cooperative lane changing strategy to improve traffic operation and safety at a diverging area nearby a highway off-ramp in an environment with connected and automated vehicles (CAVs). The cooperative strategy was implemented by the coordination of behaviors between the diverging vehicle and its cooperative vehicle on the target lane. The Minimizing Overall Braking Induced by Lane Changes Model (MOBIL) and Intelligent Driver Model (IDM) were modified to develop a simulation platform for a CAV environment. The optimal cooperative lane changing zones were firstly calculated by a heuristic algorithm, and then were applied in the simulation platform to implement the cooperative strategy. Various metrics were considered to evaluate the proposed strategy, including: total travel time, surrogate safety measures and traffic waves in the system. The experimental results showed that the length of the optimal cooperative zones obtained in our strategy were smaller than the fixed zone required in modified MOBIL strategy. Moreover, the results indicated that the cooperative strategy with the optimal zones, could improve traffic operation, traffic safety and traffic oscillation as compared to the modified MOBIL strategy with the fixed zone. The cooperative strategy can be potentially implemented nearby highway off-ramps by vehicle-based control, with the applications of the aforementioned cooperative zones.

Vehicle platoon has the potential to significantly improve traffic throughput and reduce fuel consumption and emissions and thus has attracted extensive attention recently. In this study, we propose a vehicle platoon of connected and automated vehicles (CAVs) with a combined spacing policy to enhance traffic performance. First, a combined spacing policy composed of the constant time gap (CTG) and constant spacing (CS) is formulated for the proposed vehicle platoon, where the leader adopts the CTG and the followers use the CS policy. Based on the $h_{2}$ -norm string stability criteria, the notion of exogenous-head-to-tail string stability is newly introduced, and the sufficient conditions of the local stability and string stability in the frequency domain are derived using the Routh-Hurwitz criterion and Laplace transform respectively. Numerical experiments are conducted to validate the string stability. The effectiveness of the proposed vehicle platoons is verified by theoretical analysis and numerical experiments using two typical scenarios and several measurements of effectiveness (MOE) in various performance aspects, including efficiency, safety, energy, and emission. The results show that the proposed vehicle platoon performs better than the CS-based vehicle platoon in all aspects except for efficiency. It also indicates that the proposed vehicle platoon has obvious advantages over the CTG-based vehicle platoon in efficiency and safety aspects. The findings have demonstrated the merits of the combined application of CTG and CS policies for the vehicle platoon in enhancing stability and traffic performance.

The basic operation of delay tolerant mobile sensor network (DTMSN) is for pervasive data gathering in networks with intermittent connectivity, where traditional data gathering methods can not be applied. In this paper, an efficient mobility prediction-based adaptive data gathering protocol (MPAD) based on the random waypoint mobility model tailored for DTMSN is proposed. In MPAD, a node independently makes decision to replicate messages and send them to the neighbor sensor nodes with a higher probability of meeting the sink node. MPAD consists of two components for data transmission and queue management. Data transmission makes decisions on when and where to transmit data messages according to the node delivery probability, and the queue management employs the message survival time to decide whether the message should be transmitted or dropped for minimizing the transmission overhead. Simulation results show that the proposed MPAD achieves the longer network lifetime and the higher message delivery ratio with the lower transmission overhead and data delivery delay than some other previous solutions designed for DTMSN, such as direct transmission, flooding and message fault tolerance-based data delivery protocol (FAD).

Transportation systems serve as a crucial foundation for maintaining the normal operation of cities and satisfying the requirements of public life. With the development of next-generation information technologies, automated driving technologies have brought new opportunities to improve the performance of traffic systems and the intelligence level of cities. Currently, significant research efforts have been conducted to develop automated driving systems in three major industries, i.e., automobile, roadway, and telecommunication. However, the collaboration and integration of automated driving systems among automobile, roadway, and telecommunications are still lacking, especially for collaborative development of system architecture and objectives. To address the need, this study first proposes a system architecture of vehicle–road-cloud collaborative automated driving system (VRC-CADS). Three levels of collaborative development, i.e., collaborative sensing, collaborative decision-making, and collaborative control, are designed for the VRC-CADS. Based on that, the typical scenarios of automated driving for each level of the system are further defined and interpreted. Moreover, feasible and systematic suggestions for the collaborative development of the VRC-CADS are provided, considering the cross-cutting collaboration among government agencies, academia, and industry. The proposed system architecture of the VRC-CADS will facilitate the optimization of urban lifelines and the evolution of intelligent cities.