Simulation Study Found That Intelligent Traffic Signal Control for Emergency Vehicles Can Shorten Travel Time by Up to 62.85 Percent.
Microsimulation Study to Evaluate the Effectiveness of On-Demand Traffic Signal Control Strategy on Five Routes under Different Level of Traffic Congestion.
Shanghai, China
A Novel Real-Time Traffic Signal Control Strategy for Emergency Vehicles
Summary Information
Traffic congestion may interfere with the response times of emergency vehicles such as ambulances, fire engines, and police vehicles; shortening travel times is essential to save lives and reduce property losses. This study tested a method for signal control using a microsimulation, aiming to reduce traffic in the directions of the flow of emergency vehicles and provide green light guidance to minimize queues ahead of these vehicles. This control strategy focused on on-demand signal timing based on road saturation, using non-intrusive and intrusive preemption, and restoring the intersection in the shortest time possible.
METHODOLOGY
The researchers proposed a three-step traffic signal control strategy:
- On-demand signal timing was based on a demand for reducing road saturation value made up of three indicators: the emergency response level, the congestion level of the road section, and the time urgency level.
- Signal preemption was optimized and enhanced by adopting an intrusive strategy when non-intrusive preemption was not feasible.
- The recovery cycle strategy restored the road network as soon as possible by using linear programming to find the shortest green time in each phase after an emergency vehicle passes the intersection.
The researchers designed a road network with 25 intersections and compared their proposed signal control method with fixed-time control (FTCM), a flexible signal preemption method (FSPM), and an intrusive signal preemption method (ISPM). The performance was evaluated in terms of shortening travel time on five routes and reducing the average waiting time of all vehicles in the network. The tests were done at four traffic scales: smooth, relatively congestion, moderately congestion, and severely congested.
FINDINGS
- Compared with FTCM, FSPM, ISPM, the proposed method optimized travel time for the four traffic scales by an average of up to 62.85, 50.83, and 11.62 percent, respectively.
- Compared with FTCM, the method reduced the impact on the entire traffic flow (in terms of mean of average waiting time) by 1 percent to 28 percent, depending on congestion levels.
