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Intersection control with connected and automated vehicles: a review

Purpose: This paper aims to review the studies on intersection control with connected and automated vehicles (CAVs). Design/methodology/approach: The most seminal and recent research in this area is reviewed. This study specifically focuses on two categories: CAV trajectory planning and joint intersection and CAV control. Findings: It is found that there is a lack of widely recognized benchmarks in this area, which hinders the validation and demonstration of new studies. Originality/value: In this review, the authors focus on the methodological approaches taken to empower intersection control with CAVs. The authors hope the present review could shed light on the state-of-the-art methods, research gaps and future research directions

On the impact of connected automated vehicles in freeway work zones: A cooperative cellular automata model based approach

PurposeFreeway work zones have been traffic bottlenecks that lead to a series of problems, including long travel time, high-speed variation, driver’s dissatisfaction and traffic congestion. This research aims to develop a collaborative component of connected and automated vehicles (CAVs) to alleviate negative effects caused by work zones. Design/methodology/approach\ua0The proposed cooperative component is incorporated in a cellular automata model to examine how and to what scale CAVs can help in improving traffic operations. Findings\ua0Simulation results show that, with the proposed component and penetration of CAVs, the average performances (travel time, safety and emission) can all be improved and the stochasticity of performances will be minimized too. Originality/valueTo the best of the authors’ knowledge, this is the first research that develops a cooperative mechanism of CAVs to improve work zone performance

Optimization of Electric Bus Scheduling for Mixed Passenger and Freight Flow in an Urban-Rural Transit System

Transport accessibility and urban-rural connectivity are seen as critical aspects of rural economic development. In the transit network, passenger flow between urban-rural corridors demonstrates directional imbalances and low utilization of scarce resources. Freight transportation, on the other hand, lags due to poor geography, high operating costs, and scattered demand. This paper proposes a new mode of public transit that integrates passenger and freight transport, providing a carrier for logistics while compensating for the low utilization of passenger transport. In this mode, each timetabled round trip is divided into one dedicated passenger trip with high demand and one mixed-flow trip with on-demand requests. A space-time-state network is constructed considering the picking-up time window, loading/unloading service time, and electric bus energy replenishment. A mixed-integer linear programming model is developed to optimize the bus schedule that covers the travel demands and the charging requests with minimized travel costs. A Lagrangian relaxation framework with a dynamic programming algorithm and sub-gradient method is presented for problem-solving. The real-life rural-urban transport instance and a simulated network demonstrate the operation of the new mode and validate the efficiency of the proposed method. The innovative concept and the optimization framework are expected to serve as a reference for public administration to alleviate passenger and freight transportation bottlenecks in the urban-rural context

Development of parametric eco-driving models for fuel savings: A novel parameter calibration approach

The existing conventional traffic flow models aims to simulate human-driven following vehicles in real world. In this era of emerging transport solutions, controlling or intervening traffic flow to achieve high fuel efficiency along with good driving safety and travel efficiency becomes a reality. As such, it is worth exploring the possibility of developing eco-driving models to optimise vehicle movements for fuel consumption minimisation, while maintaining safety and efficiency. In this study, we propose a modified genetic algorithm (GA) based calibration method that enables the calibrated parametric traffic flow (car following) models to simulate or control vehicles in an eco-driving manner. By developing a novel objective function for the GA method based on the widely-used VT-Micro fuel consumption model, the proposed method can calibrate model parameters towards improving fuel efficiency. Besides, by subtly using heavy fuel consumptions as a surrogate index to represent low travel efficiency or dangerous driving strategies, the modified GA method with the novel objective function can guide the calibrated model towards achieving complete eco-driving requirements. Experimental simulation results further indicate that traffic flow models calibrated by the modified GA-based method can also alleviate traffic disturbances and oscillations in a more effective manner

Simulation Analyses of Two On-Ramp Lane Arrangements

Ramps are vital pieces of infrastructure connecting city traffic networks to freeways. The performance of a ramp is to some extent determined by the on-ramp lane arrangement. In this paper, our primary aim is to evaluate the performance in terms of travel time and vehicle emissions for two on-ramp lane arrangements: added lane and zip merging. We estimate the travel time and CO2 emissions on the basis of the speed, and acceleration of vehicles in accordance with the improved comprehensive modal emission model (CMEM), and then analyse the impacts of traffic volume and heavy goods vehicles (HGVs) on travel time and emissions. The impacts of main road traffic flow on travel time and emissions for the two on-ramp lane arrangements are analysed under scenarios with traffic volumes of 800, 1\ua0000, 1\ua0200, 1\ua0400, 1\ua0600 and 1\ua0800 vehs/h/lane. Meanwhile, the relationships between travel time, emissions and various proportions of HGVs (2%, 4%, 6%, 8% and 10%) for both on-ramp lane arrangements are evaluated as well. We eventually present emission contour charts for the two on-ramp lane arrangements based on the possible combinations of traffic volumes and HGV percentages

Consolidating Bus Charger Deployment and Fleet Management for Public Transit Electrification: A Life-Cycle Cost Analysis Framework

Despite rapid advances in urban transit electrification, the progress of systematic planning and management of the electric bus (EB) fleet is falling behind. In this research, the fundamental issues affecting the nascent EB system are first reviewed, including charging station deployment, battery sizing, bus scheduling, and life-cycle analysis. At present, EB systems are planned and operated in a sequential manner, with bus scheduling occurring after the bus fleet and infrastructure have been deployed, resulting in low resource utilization or waste. We propose a mixed-integer programming model to consolidate charging station deployment and bus fleet management with the lowest possible life-cycle costs (LCCs), consisting of ownership, operation, maintenance, and emissions expenses, thereby narrowing the gap between optimal planning and operations. A tailored branch-and-price approach is further introduced to reduce the computational effort required for finding optimal solutions. Analytical results of a real-world case show that, compared with the current bus operational strategies and charging station layout, the LCC of one bus line can be decreased significantly by 30.4%. The proposed research not only performs life-cycle analysis but also provides transport authorities and operators with reliable charger deployment and bus schedules for single- and multi-line services, both of which are critical requirements for decision support in future transit systems with high electrification penetration, helping to accelerate the transition to sustainable mobility