scholarly journals Traffic Signal Optimization and Vehicle Speed Control at Signalized Intersection

2020 ◽  
pp. 542-547
Author(s):  
S. R. Karthiga ◽  
G. Ramya ◽  
M. Ramya
Keyword(s):  
Arrival Time ◽  
Traffic Signal ◽  
Signalized Intersection ◽  
Traffic Signal Control ◽  
Signal Timing ◽  
Vehicle Speed ◽  
Speed Optimization ◽  
Total Travel Time ◽  
Traffic Signal Timing ◽  
Engine Power

The aim of this project is to promote the significant improvement of transportation efficiency and fuel economy by the cooperative method of traffic signal control and vehicle speed optimization. It formulates the optimal traffic signal timing and vehicles arrival time to minimize the total travel time of all vehicle and to optimize the engine power to minimize the fuel consumption of individual vehicles.

scholarly journals Multi-Objective Optimization of Traffic Signal Timing for Oversaturated Intersection

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Yan Li ◽  
Lijie Yu ◽  
Siran Tao ◽  
Kuanmin Chen
Keyword(s):  
Simulation Software ◽  
Traffic Signal ◽  
Signal Control ◽  
Traffic Signal Control ◽  
Signal Timing ◽  
Simulation Environment ◽  
Multi Objective Optimization ◽  
Good Efficiency ◽  
Multi Objective ◽  
Traffic Signal Timing

For the purpose of improving the efficiency of traffic signal control for isolate intersection under oversaturated conditions, a multi-objective optimization algorithm for traffic signal control is proposed. Throughput maximum and average queue ratio minimum are selected as the optimization objectives of the traffic signal control under oversaturated condition. A simulation environment using VISSIM SCAPI was utilized to evaluate the convergence and the optimization results under various settings and traffic conditions. It is written by C++/CRL to connect the simulation software VISSIM and the proposed algorithm. The simulation results indicated that the signal timing plan generated by the proposed algorithm has good efficiency in managing the traffic flow at oversaturated intersection than the commonly utilized signal timing optimization software Synchro. The update frequency applied in the simulation environment was 120 s, and it can meet the requirements of signal timing plan update in real filed. Thus, the proposed algorithm has the capability of searching Pareto front of the multi-objective problem domain under both normal condition and over-saturated condition.

KNOWLEDGE BASED TRAFFIC SIGNAL CONTROL MODEL FOR SIGNALIZED INTERSECTION

Transport ◽  
2012 ◽  
Vol 27 (3) ◽  
pp. 263-267 ◽  
Author(s):  
Henrikas Pranevičius ◽  
Tadas Kraujalis
Keyword(s):  
Intelligent Transportation Systems ◽  
Control Method ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Traffic Signal ◽  
Signalized Intersection ◽  
Signal Control ◽  
Traffic Signal Control ◽  
Signal Timing ◽  
Traffic Conditions

Intelligent transportation systems have received increasing attention in academy and industry. Being able to handle uncertainties and complexity, expert systems are applied in vast areas of real life including intelligent transportation systems. This paper presents a traffic signal control method based on expert knowledge for an isolated signalized intersection. The proposed method has the adaptive signal timing ability to adjust its signal timing in response to changing traffic conditions. Based on the traffic conditions, the system determines to extend or terminate the current green signal group. Using the information from its traffic detectors of isolated intersection, the proposed controller gives optimal signals to adapt the phase lengths to the traffic conditions. A comparative analysis between proposed control algorithm, fuzzy logic (FLC) and fixed-timed (pre-timed) controllers has been made in traffic flows control, with varying traffic volume levels, by using simulation software ‘Arena’. Simulation results show that the proposed traffic signal control method (EKC) has better performance over fuzzy logic and conventional pre-time controllers under light and heavy traffic conditions.

A Two-Level Model for Traffic Signal Timing and Trajectories Planning of Multiple CAVs in a Random Environment

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Yangsheng Jiang ◽  
Bin Zhao ◽  
Meng Liu ◽  
Zhihong Yao
Keyword(s):  
Random Environment ◽  
Arrival Time ◽  
Traffic Signals ◽  
Traffic Signal ◽  
Signal Timing ◽  
Automated Vehicles ◽  
Gasoline Consumption ◽  
Level Model ◽  
Traffic Signal Timing ◽  
Two Level Model

Connected and automated vehicles (CAVs) trajectories not only provide more real-time information by vehicles to infrastructure but also can be controlled and optimized, to further save travel time and gasoline consumption. This paper proposes a two-level model for traffic signal timing and trajectories planning of multiple connected automated vehicles considering the random arrival of vehicles. The proposed method contains two levels, i.e., CAVs’ arrival time and traffic signals optimization, and multiple CAVs trajectories planning. The former optimizes CAVs’ arrival time and traffic signals in a random environment, to minimize the average vehicle’s delay. The latter designs multiple CAVs trajectories considering average gasoline consumption. The dynamic programming (DP) and the General Pseudospectral Optimal Control Software (GPOPS) are applied to solve the two-level optimization problem. Numerical simulation is conducted to compare the proposed method with a fixed-time traffic signal. Results show that the proposed method reduces both average vehicle’s delay and gasoline consumption under different traffic demand significantly. The average reduction of vehicle’s delay and gasoline consumption are 26.91% and 10.38%, respectively, for a two-phase signalized intersection. In addition, sensitivity analysis indicates that the minimum green time and free-flow speed have a noticeable effect on the average vehicle’s delay and gasoline consumption.

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