Inefficient traffic control is pervasive in modern urban areas, which would exaggerate traffic congestion as well as deteriorate mobility, fuel economy and safety. In this paper, we systematically review the potential solutions that take advantage of connected and automated vehicles (CAVs) to improve the control performances of urban signalized intersections. We review the methods and models to estimate traffic flow states and optimize traffic signal timing plans based on CAVs. We summarize six types of CAV-based traffic control methods and propose a conceptual mathematical framework that can be specified to each of six three types of methods by selecting different state variables, control inputs, and environment inputs. The benefits and drawbacks of various CAV-based control methods are explained, and future research directions are discussed. We hope that this review could provide readers with a helpful roadmap for future research on CAV-based urban traffic control and draw their attention to the most challenging problems in this important and promising field.

https://rosap.ntl.bts.gov/view/dot/42376/dot_42376_DS1.pdf

Urban traffic signal control with connected and automated vehicles: A survey

Existing traffic signal control systems only allocate green time to different phases to avoid conflicting vehicle movements. With advances in connected and automated vehicle (CAV) technologies, CAV trajectories not only provide more information than existing infrastructure-based detection systems, but also can be controlled to further improve mobility and sustainability. This paper presents a mixed integer linear programming (MILP) model to optimize vehicle trajectories and traffic signals in a unified framework at isolated signalized intersections in a CAV environment. A new planning horizon strategy is applied to conduct the optimization. All vehicle movements such as left-turning, right-turning and through are considered. Phase sequences, green start and duration of each phase, and cycle lengths are optimized together with vehicle lane-changing behaviors and vehicle arrival times for delay minimization. Vehicles are split into platoons and are guaranteed to pass through the intersection at desired speeds and avoid stops at stop bars. Exact vehicle trajectories are determined based on optimized vehicle arrival times. For the trajectory planning of platoon leading vehicles, an optimal control model is implemented to minimize fuel consumption/emission. For following vehicles in a platoon, Newell's car-following model is applied. Simulation results validate the advantages of the proposed control method over vehicle-actuated control in terms of intersection capacity, vehicle delays, and CO2 emissions. A sensitivity analysis is conducted to show the potential benefits of a short minimum green duration as well as the impacts of no-changing zones on the optimality of the proposed model.

Integrated optimization of traffic signals and vehicle trajectories at isolated urban intersections

The advancements in communication and sensing technologies can be exploited to assist the drivers in making better decisions. In this paper, we consider the design of a real-time cooperative eco-driving strategy for a group of vehicles with mixed automated vehicles (AVs) and human-driven vehicles (HVs). The lead vehicles in the platoon can receive the signal phase and timing information via vehicle-to-infrastructure (V2I) communication and the traffic states of both the preceding vehicle and current platoon via vehicle-to-vehicle (V2V) communication. We propose a receding horizon model predictive control (MPC) method to minimise the fuel consumption for platoons and drive the platoons to pass the intersection on a green phase. The method is then extended to dynamic platoon splitting and merging rules for cooperation among AVs and HVs in response to the high variation in urban traffic flow. Extensive simulation tests are also conducted to demonstrate the performance of the model in various conditions in the mixed traffic flow and different penetration rates of AVs. Our model shows that the cooperation between AVs and HVs can further smooth out the trajectory of the latter and reduce the fuel consumption of the entire traffic system, especially for the low penetration of AVs. It is noteworthy that the proposed model does not compromise the traffic efficiency and the driving comfort while achieving the eco-driving strategy.

/pdf/a-platoon-based-cooperative-eco-driving-model-for-mixed-5ezm0ieku3.pdf

A platoon based cooperative eco-driving model for mixed automated and human-driven vehicles at a signalised intersection

Road transport consumes significant quantities of fossil fuel and accounts for a significant proportion of CO2 and pollutant emissions worldwide. The driver is a major and often overlooked factor that determines vehicle performance. Eco-driving is a relatively low-cost and immediate measure to reduce fuel consumption and emissions significantly. This paper reviews the major factors, research methods and implementation of eco-driving technology. The major factors of eco-driving are acceleration/deceleration, driving speed, route choice and idling. Eco-driving training programs and in-vehicle feedback devices are commonly used to implement eco-driving skills. After training or using in-vehicle devices, immediate and significant reductions in fuel consumption and CO2 emissions have been observed with slightly increased travel time. However, the impacts of both methods attenuate over time due to the ingrained driving habits developed over the years. These findings imply the necessity of developing quantitative eco-driving patterns that could be integrated into vehicle hardware so as to generate more constant and uniform improvements, as well as developing more effective and lasting training programs and in-vehicle devices. Current eco-driving studies mainly focus on the fuel savings and CO2 reduction of individual vehicles, but ignore the pollutant emissions and the impacts at network levels. Finally, the challenges and future research directions of eco-driving technology are elaborated.

/pdf/eco-driving-technology-for-sustainable-road-transport-a-4poxc6j7sy.pdf

Eco-driving technology for sustainable road transport: A review

Signalized intersections play an important role in transportation efficiency and vehicle fuel economy in urban areas. This paper proposes a cooperative method of traffic signal control and vehicle speed optimization for connected automated vehicles, which optimizes the traffic signal timing and vehicles’ speed trajectories at the same time. The method consists of two levels, i.e., roadside traffic signal optimization and onboard vehicle speed control. The former calculates the optimal traffic signal timing and vehicles’ arrival time to minimize the total travel time of all vehicles; the latter optimizes the engine power and brake force to minimize the fuel consumption of individual vehicles. The enumeration method and the pseudospectral method are applied in roadside and onboard optimization, respectively. Simulation studies are conducted to compare the proposed method with benchmark methods. The results show significant improvement of transportation efficiency and fuel economy by the cooperation method.

Cooperative Method of Traffic Signal Optimization and Speed Control of Connected Vehicles at Isolated Intersections

This research proposed an eco-driving system for an isolated signalized intersection under partially Connected and Automated Vehicles (CAV) environment. This system prioritizes mobility before improving fuel efficiency and optimizes the entire traffic flow by optimizing speed profiles of the connected and automated vehicles. The optimal control problem was solved using Pontryagin’s Minimum Principle. Simulation-based before and after evaluation of the proposed design was conducted. Fuel consumption benefits range from 2.02% to 58.01%. The CO2 emissions benefits range from 1.97% to 33.26%. Throughput benefits are up to 10.80%. The variations are caused by the market penetration rate of connected and automated vehicles and v/c ratio. No adverse effect is observed. Detailed investigation reveals that benefits are significant as long as there is CAV and they grow with CAV’s market penetration rate (MPR) until they level off at about 40% MPR. This indicates that the proposed eco-driving system can be implemented with a low market penetration rate of connected and automated vehicles and could be implemented in a near future. The investigation also reveals that the proposed eco-driving system is able to smooth out the shock wave caused by signal controls and is robust over the impedance from conventional vehicles and randomness of traffic. The proposed system is fast in computation and has great potential for real-time implementation.

Eco approaching at an isolated signalized intersection under partially connected and automated vehicles environment

In urban areas, traffic signals cause unnecessary stops and delays to vehicles resulting in excessive energy consumptions and emissions. The eco-approach technology has been introduced to achieve environment-friendly driving behaviors and to improve energy efficiencies with reduced rapid accelerations or decelerations. However, it is not clear how the behavior of drivers would change while following an eco-approaching vehicle. Especially in the mixed traffic, dynamics behind the interactions between the human–driven vehicle and connected automated vehicle (CAV) that perfectly achieves the eco-approach and the impacts on energy consumptions are not transparent. This research designs a driving simulation environment for the mixed traffic to assess the benefits of the eco-approach. In the experiments, a straight roadway with four signalized intersections equipped with communication devices is developed. An eco-guidance algorithm for human drivers and an eco-approach control algorithm of CAV with the I2-V communication system are designed and compared, where each scenario is tested 50 times with a human driver using a driving simulator. The results indicate that both the eco-guidance scenario and following CAV with the eco-approach scenario could reduce over 6% of fuel consumptions compared with the base-case scenario, which is normal-driving without guidance. This indicates the energy efficiency benefit of the eco-approach of CAVs and its impact on surrounding vehicles in the mixed traffic.

Impact of Automated Vehicle Eco-Approach on Human-Driven Vehicles

This study evaluated the performance of an eco-approach control system at signalized intersections under a partially connected and automated vehicle (CAV) environment. This system has the first eco-approach controller able to function with the existence of surrounding human-driven traffic. A previous evaluation only confirmed its benefits. The purpose of this study was to conduct a further extensive test on the controller to identify room for improvement. Two different networks were tested, including an isolated signalized intersection and a corridor with two signalized intersections. The measures of effectiveness (MOEs) adopted were throughput and fuel consumption. All the before-and-after MOEs were compared using t-tests. The results indicate that the controller generally improved the fuel efficiency without harm to the mobility, and its environmental performance was affected by the minimum CAV speed, green ratio, congestion level, and marker penetration rate of CAVs. A detailed investigation revealed that no significant environmental benefit was generated under high congestion levels when the minimum speed of CAVs was more than 20 mph, and the shockwaves caused by the eco-approach control may result in a gating effect that reduces the throughput at the upstream intersection of the corridor under high congestion levels.

An extensive investigation of an eco-approach controller under a partially connected and automated vehicle environment

In order to ensure the safety and efficiency of emergency transportation process for natural disaster environment and promote the construction of emergency transportation support equipment system, the construction method of road emergency transportation support equipment system is put forward by referring to the construction method of disaster site survival support equipment system in high and cold plateau regions one and combining with the development status of emergency transportation support equipment in China. The boundary, status quo, support objects, support tasks and target capabilities of the emergency transportation support equipment system were analyzed, and framework of the equipment system was constructed, and the evaluation indexes of the system were summarized. Results show that “emergency detection, transportation loading and unloading, special transportation and emergency support are important support objects, their support requirements in the process of emergency transportation for natural disaster environment should be fully demonstrated in combination with the support task and scale. 

Huifu Jiang

Papers

Eco approaching at an isolated signalized intersection under partially connected and automated vehicles environment

Impact of Automated Vehicle Eco-Approach on Human-Driven Vehicles

An extensive investigation of an eco-approach controller under a partially connected and automated vehicle environment

Research on road emergency transportation support equipment system for natural disaster environment