Connected and autonomous vehicles (CAVs) have become the highlights of traffic. Researchers in this field have proposed various traffic management measures to enhance the capacity and efficiency of traffic with CAVs, especially mixed traffic of CAVs and manual vehicles (MVs). Exclusive lane setting is included. However, exclusive lane policy-related researches for mixed traffic of CAVs and MVs were very limited, and the influence of number and location of exclusive lanes on the mixed traffic was unclear. To fill this gap, this paper aims to study the influence of different exclusive lane policies on mixed traffic and provide recommended lane policies under various traffic volumes and CAV penetration rates. Freeways with two lanes and three lanes in a single direction were taken into consideration, and sixteen lane policies were proposed. Then different lane policies were simulated with a new proposed cellular automata (CA) model, and properties including flux, average speed, and CAVs degradation were analyzed to evaluate the traffic efficiency of each lane policy. The results show that CAV exclusive lanes can improve the capacity, while MV exclusive lanes seem helpless for capacity improvement. Seven lane policies, including GC, GM, and CM for two-lane freeways and GCG, CGC, and CCM for three-lane freeways, outperform the others in terms of average speed. In addition, exclusive lanes can reduce the probability that CAVs degenerate to AVs. Our findings may help to optimize freeways’ lane policies and improve the efficiency of heterogeneous traffic mixed with CAVs and MVs.

Cooperative adaptive cruise control (CACC) is a promising technology to improve traffic efficiency and enhance road safety. In this paper, a modified CACC control model considering the communication time delay is proposed, which is used to investigate the longitudinal safety impacts of the communication time delay to the CACC platoon. Then, the communication time delay model is integrated into the CACC model to simulate the realistic information transfer process in the CACC platoon. Then a microscopic CACC platoon simulation is designed and conducted to verify the feasibility and reliability of the modified CACC control algorithm. The obtained results reveal that the modified CACC control algorithm can not only reduce about 96.6% of inter-vehicle spacing error, but also enhance the vehicles’ ability to sense the upstream traffic changes. Furthermore, to quantitatively analyze the longitudinal safety influence of the time delay caused by representative communication systems, sensitivity analysis experiments of headway time were designed and conducted. In the sensitivity analysis, the time exposed time-to-collision (TET) and the time-integrated time-to-collision (TIT) were introduced as the key performance indicators (KPIs) to quantify the rear-end collision risks. Sensitivity analysis results demonstrate that the performance of the CACC platoon is strictly related to the applied wireless communication style. Furthermore, the CACC system supported by the 5th generation (5G) communication system shows great advantages in narrowing the minimal headway time gap and reducing the rear-end collision risks.

Electric buses are becoming increasingly popular in transit systems by virtue of their great potential in improving environmental sustainability. The electric bus charging scheduling problem (EBCSP) has been widely researched to minimize the operation cost by determining the charging strategies, including when and how much electricity to charge. However, few studies have considered both the battery degradation mechanism and the nonlinear charging. The former should be the implicit operational cost, while the latter should accurately estimate the electricity charged. Considering these two characteristics, this paper addresses the EBCSP with the goal of optimizing costs. First, a rigorous mathematical model is developed, constrained by the electricity quantity, preset timetable, charging facilities, and charging continuity. Then, the battery degradation cost is modeled by introducing the wear cost function, and the nonlinear charging profile is linearized by piecewise affine function. The model is further simplified to mixed integer linear programming with a reduced computational burden. Computational results suggest that the optimization can reduce battery degradation and total cost, especially for those bus routes with higher frequencies and longer travel distances. Finally, sensitive analysis indicates that a low initial state of charge can result in significant savings in degradation costs of about 19% and total costs of about 13%. Large fleet and battery sizes reduce charging costs while increasing battery degradation cost and total cost. Some solid managerial insights are provided for the application of electric transportation systems.

Cooperative adaptive cruise control (CACC) is regarded as a promising approach to improve traffic stability and capacity by operating vehicle-to-vehicle (V2V) communication. However, the beneficial effect of CACC vehicles is greatly reduced due to the influence of manually driven vehicles (MDVs) in the heterogeneous traffic flow, in which the degradation of CACC vehicles is a considerable problem. One proposed solution is to install communication devices for MDVs, called IMDVs, to propagate information to CACC vehicles and prevent the degradation. This study analyzed the traffic flow configuration by introducing IMDVs and considering multiple traffic flow operations, e.g. vehicle degradation and platoon formation. Then, multiple factors, including market penetration rate, platoon length, and information flow topology, were taken into consideration in the theoretical modelling of linear stability and fundamental diagram. Finally, we verified the high accuracy of theoretical analysis by numerical experiments and gave some reasonable recommendations for traffic management.

Cooperative adaptive cruise control is recognised as an effective means to reduce the rear‐end collision caused by the delayed reaction and improper driving behaviours of manually driven vehicles. However, vehicle‐to‐vehicle communication, as the key to collect information for the cooperative adaptive cruise control system, is likely to be interrupted by malicious attacks and equipment failures. When communication interruption occurs, sensors of the adaptive cruise control system will replace vehicle‐to‐vehicle communication for information collection, that is, cooperative adaptive cruise control vehicles degrade to adaptive cruise control vehicles automatically, causing an increased rear‐end collision risk. This study aims to investigate the safety impact of cooperative adaptive cruise control vehicles’ degradation under spatial continuous communication interruption. A mixed platoon, consisting of cooperative adaptive cruise control vehicles, adaptive cruise control vehicles, manually driven vehicles, and improved manually driven vehicles with information‐sending devices, is simulated with the realistic cooperative adaptive cruise control and adaptive cruise control model, and the intelligent driver model. Different platoon forms are discussed by adjusting the quantity and position of manually driven vehicles in the mixed platoon. The results show that manually driven vehicles can effectively block the backward extension of speed fluctuation and reduce the rear‐end collision risk under the spatial continuous communication interruption. Nevertheless, equipping manually driven vehicles with information‐sending devices weakens the ability to defend against communication interruption.