A Strategy for Emergency Vehicle Preemption and Route Selection

Abstract

Emergency vehicle preemption (EVP) aims to give right of way to emergency vehicles (EV) heading toward the incident location through a network of signalized intersections by creating a green wave en-route. The design goals of EVP systems are two folds: first, to avoid any hindrance to the passage of EV along the road and at the intersections and second, to reduce the negative impact of preemption on general traffic. The negative impact of EVP on normal traffic can be minimized by selecting appropriate preemption strategy. The EVP schemes proposed earlier aim to minimize the travel time of the EV with no or little consideration to the negative impact of EVP on the normal traffic. In this study, a joint strategy for optimal path selection and EV preemption is developed. The proposed scheme selects the optimal path for the EV before it departs from its origin and then activates the preemption on each intersection en-route at the right time to clear the intersection before the EV reaches. The proposed EVP scheme also aims to minimize the impact of EVP over normal traffic at both stages (i.e., path selection phase and preemption phase). A major advantage of the proposed method is that once the optimal path is selected, the emergency information can be disseminated to other vehicles using vehicle-to-vehicle and vehicle-to-infrastructure communication in the EV path to clear the entire route or the approaching lane. The strategy was tested using a microscopic simulation environment for a real traffic network. The findings indicated a major reduction in the travel time of the EV while minimizing the impact of preemption on the normal traffic. The proposed strategy and evaluation procedure can be helpful for corresponding agencies and practitioners to assess the impact of implementing preemption on existing or proposed arterials.

SG-TSE: Segment-based Geographic Routing and Traffic Light Scheduling for EV Preemption based Negative Impact Reduction on Normal Traffic

“…A multiagent preemptive longest queue first system has been proposed in [26] to handle the emergency vehicle crossings at interrupted intersections. Further, an efficient preemption strategy is selected to diminish the negative impact of preemption on general traffic in [27]. It utilizes the VANET communication through the emergency vehicle path.…”

Comparative Analysis of Traffic Light Control Mechanism for Emergency Vehicle

“…Moreover, authors have also worked on scheduling of arterial traffic lights in which neighboring traffic lights will coordinated with each other to prepare efficient schedule for entire road network. Shaaban et al [11] proposed mechanism to reduce hindrance on the way of emergency vehicle by selecting an optimal route and applying preemption technique. In proposed mechanism, proper value of green time is calculated using signal switchover time, time required to discharge vehicles at intersection and fixed safety time.…”

“…We have categorized these approaches in two categories namely Sensor based sensing and Message based sensing. Some of the TLC mechanisms [9], [11], [12], [15] discussed here uses different on-road detectors like inductive loop, acoustic sensor, camera, force resistive sensor, magnetic sensor and ultrasonic sensor for detection of EV and few of these sensors are also used for traffic density calculations. However, the challenge lies with these sensors is its deployment and maintenance.…”

Deep Transfer Learning Based Intersection Trajectory Movement Classification for Big Connected Vehicle Data

“…The multipurpose implementation of this technology and consequent safety warning for drivers improve transportation in many ways [4,5]. Some most frequent safety applications of connected vehicle technology include back of queue warning [6], road work warning [7], advanced red light warning [8], red-light running prediction [3], emergency vehicle travel time reduction [9]. In Queensland, Australia, vulnerable road users: pedestrians, bicyclists, and motorcyclist fatality is 12.3%, 3% and 13% respectively of overall road death [10].…”