Simple Design of Wireless Sensor Networks for Traffic Jams Avoidance

Abstract

Intelligent transportation systems (ITS) are usually approached by exhaustive measuring and complex signal processing including medium-high cost hardware deployment. In this paper, a novel design of a wireless sensor network system using magnetometers and microphones for the detection and avoidance of traffic jams is described and analyzed. The system, which can also be used for traffic monitoring and surveillance, is simple, energy efficient, and accurate which allows to be implemented with a reduced hardware cost. In order to reduce the maintenance tasks, mini solar panels would also be installed for powering up the motes in the near future.

Internet of Vehicles and Cost-Effective Traffic Signal Control

“…In the sensor-based approach, various types of sensors, like inductive loop detectors, ultrasonic sensors, magnetometers, radar/lidar based sensors, etc., are installed near to intersections for vehicle detection, tracking and counting [11,12,13,14,15,16,17]. Each sensor is equipped with devices like a microphone to collect acoustic, seismic or any signals to classify vehicles.…”

“…In these days, traffic lights can be controlled in real-time by coordinated controllers at intersections which monitor traffic patterns with the assistance of devices like video cameras and sensors (e.g., loop detectors). Video camera-based monitoring [4,5,6,7,8,9,10] requires high computing power for real-time image processing and sensor-based monitoring [11,12,13,14,15,16,17] incurs high sensor installation and maintenance cost. Moreover, these technologies suffer from various environmental obstacles like weather, lighting and road condition, which cannot be completely overcome by any countermeasures.…”

A State-of-the-Art Review of the Sensor Location, Flow Observability, Estimation, and Prediction Problems in Traffic Networks

“…In this context, the role of sensors and their location and the flow observability, estimation, and prediction problems become important. Though sensors can be used for many different purposes in the traffic field (see, e.g., Gil Jiménez and Fernández-Getino García [1], Liu et al [2], and Kong et al [3]), in this paper, we use sensors to determine the traffic flow. In particular, it is important to distinguish between passive and active sensors.…”

“…where is the minimum number of required cameras; is a binary variable that equals one if link contains a sensor and zero; otherwise is a binary variable that equals one if route is observed (can be distinguished from others) and zero; otherwise, y and z are the vectors of the corresponding variables; R is the set of routes; A is the set of links; is the element in th row and th column of the link-route incidence matrix; R obs is the subset of routes that we want to observe; max is the maximum number of available cameras; max is the maximum number of scanned links per route; and 1 is a nonnegative small number. Objective function (1) minimizes the number of cameras and among all solutions chooses the one with the most observed routes. Constraint (2), if the binary variable is equal to 1, guarantees that route is able to be distinguished by the subset of scanned links from the other routes.…”