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Vehicle platoons were recently proposed to reduce energy consumption and emissions. However, the majority of platooning studies have focused on pure connected automated vehicle (CAV) environments with limited insights into energy consumption and emissions. This paper quantifies fuel consumption and emissions by studying the microscopic movements of CAVs and human driving vehicles (HDVs) in mixed traffic flows. With an extended cellular automaton model, a four-lane mixed traffic flow of CAVs and HDVs is investigated in detail. The results have shown that ad hoc platoon formation can lead to frequent acceleration and lane changing, resulting in more fuel consumption and emission. With a dedicated CAV lane (DCL) strategy, the interference of CAVs and HDVs is greatly reduced, thereby improving the fuel economy and emission reduction. The findings can benefit the organization of vehicle platoons in the persisting mixed traffic flow environment.

With the development of urban rail transit systems, the operation and management of the system faces various problems, among which the unreasonably long waiting time at transfer stations during the first train period is a major challenge for metro companies. To address this problem, some cities (e.g. Guangzhou, Hefei) are operating inter-regional trains to reduce the waiting time of passengers. With this motivation, we study the first train timetable synchronization problem with multiple departure stations. The problem is first formulated as a mixed integer nonlinear programming (MINLP) model. By using auxiliary intermediate variables, the nonlinear model is reformulated as a mixed integer linear programming (MILP) model, which can be solved directly by the commercial solver COPT. A real-world example of the Hefei urban rail transit network is applied to test the effectiveness of the proposed model. By adjusting the first ordinary train start service times and operating 12 additional inter-regional trains on 2 bidirectional lines, the total transfer waiting time and the number of long waiting time directions decreased by 39.09% and 56.25%, respectively.

In urban traffic systems, alleviating traffic congestion originated from left-turn/U-turn lanes at highly demanded intersections plays an important role in enhancing the traffic efficiency. For a typical intersection, the layout with double left-turn (DLT) lanes is a relatively common geometric feature. However, the effect of DLT scheme on the performance of the entire traffic system is not clear. This paper compares the performance of urban traffic system with different lane function schemes with extended cellular automaton (CA) model considering the car-following, lane-changing, intersection-traversing and route-choice behavior of vehicles. Using the flow-density relation, three macroscopic parameters (average trip completion rate, average traffic flow and average velocity) are examined to evaluate the system performance. With the wide application of DLT scheme, the vehicles can be distributed more evenly among the lanes. As a result, the traffic flow and the trip completion rate will be higher, especially at high density. Case studies of realistic Hefei city network and Sioux Falls networks are also carried out. The results show that the performance of traffic network will be better if more intersections adopt the DLT scheme.

The study of traffic dynamics on couple networks is important for the design and management of many real systems. In this paper, an efficient routing strategy on coupled spatial networks is proposed, considering both traffic characteristics and network topology information. With the routing strategy, the traffic capacity can be greatly improved in both scenarios of identical and heterogeneous node capacity allocation. Heterogeneous allocation strategy of node delivery capacity performs better than identical capacity allocation strategy. The study can help to improve the performance of real-world multi-modal traffic systems.

Enhancing traffic flow plays an important role in the traffic management of urban arterial networks. The policy of prohibiting left-turn (PLT) at selected highly demanded intersections has been adopted as an attempt to increase the efficiency at these intersections. In this paper, we study the impact of PLT by mathematical analysis and simulations based on the cellular automaton model. Using the flow-density relation, three system performance indexes are examined: the average trip completion rate, the average traffic flow, and the average velocity of vehicles. Different route guidance strategies, including the shortest path and the quickest path, are investigated. We show that when left turn is prohibited, vehicles are distributed more homogeneously in the road network, and the system performs better and reaches a higher capacity. We also derive a critical length of link, above which the benefit of PLT will decrease.