The Cooperative Intelligent Transport Initiative (CITI) is a project currently undertaken by Transport for New South Wales (TfNSW) in partnership with Data61|CSIRO and the Australian Federal Government’s Heavy Vehicle Safety Productivity Program. The main goal of the project is to build Australia’s first semi-permanent test-bed for assessing Vehicle-to-vehicle and Vehicle-to-Infrastructure technology, over an area of 917 km2 in the Illawarra Region of NSW south of Sydney . Avoiding traffic collisions in this area would help reducing accident costs and opens the possibility for deploying the Cooperative Intelligent Transport Systems (CITS) technology on real roads, through Dedicated Short Range Communication (DSRC) systems.
Currently, sixty vehicles (58 heavy vehicles and 2 light vehicles), three signalized intersections and one roadside location have been equipped with DSRC units. In order to ensure road safety, one of the main challenges of the project is to address the generation of false collision alerts which hinder driving and could result in a mistrust of the DSRC on-board-unit warning device. The first step to identify the possible cause of false alerts is to investigate and understand the accuracy of the transmitted positioning between connected vehicles, as reported from Basic Safety Messages (BSMs).
Heavy Vehicles Positioning Investigation
Our current investigations  on positoning accuracy for heavy vehicles are focused on:
- investigating and characterising the error (noise) in the DSRC GPS positioning,
- identifying “noise – prone sections” of the road network that would cause high levels of noise to be registered.
- identifying potential factors that would impact noise in the GPS positioning by applying regression analysis and decision trees.
- analyse the transmission of collision alerts during experiments which simulate real-life incidents.
- identify the factors that might hinder broadcasting collision alerts between connected vehicles.
Light Vehicles – Collision Alert Monitoring
Two light-vehicles belonging to TfNSW and equipped with DSRC systems were involved in various test-case scenarios in which the DSRC system sent alert messages to the driver in order to avoid collision between the two cars . The following driving scenarios were tested:
- Forward collision experiment – testing the forward collision avoidance (first car decelerates, second car (following) receives alert messages);
- Forward collision experiment, reversed roles – testing the forward collision avoidance when the roles of vehicles were reversed;
- Unmarked T-intersection experiment – test of collision avoidance at an unmarked T-intersection (low visibility)
- Signal Phase and Timing (SPaT) Equipped intersections demonstration – successful generation of red light alerts based on traffic signal messages received by both connected vehicles.
Our investigation looked at the difference between successful and failed Collision Alerts vehicles and the external or internal events which lead to a miscommunication between devices, as well as the implications on the driver safety.
Visualization platform for Connected Vehicles Monitoring
We are currently centralizing and monitoring the CV activity by building a visualization platform that would help detect the locations where the DSRC-equipped vehicles are suffering bad positioning accuracies and the reasons why this happens.
We are also looking into building a modelling framework for applying an event-triggered control when the location transmitted by connected vehicles equipped with DSRC is lost due to unforeseen events. Firstly, we model the evolution of the DSRC transmitted positioning as a multi-state stochastic switching system by taking into consideration the distance from the transmitted location to the road center. A control interval is defined for the evolution of the positioning signal by using the road width to establish the boundaries. Secondly, we propose an analytic method for determining the exit probabilities from the control interval, with the scope of anticipating any position anomalies and help applying the event triggered control in advance rather than when the control boundaries have been already reached. Thirdly, we apply a cooperative location estimation method for improving the broadcast position information by using the accumulating trajectory segments from the moment of the anomaly alert.
This work will be presented at the IFAC World Congress in Toulouse, France, from 9 – 14th of July 2017 .
 Mihaita Adriana Simona, Tyler Paul, Menon Aditya, Wen Tao, Ou Yuming, Cai Chen, Chen Fang, "An investigation of positioning accuracy transmitted by connected heavy vehicles using DSRC", Transportation Research Board 96th Annual Meeting, Washington D.C., January 8-12, 2017.
 Mihaita A.S., Tyler Paul, Wall John, Vecovsky Vanessa, Cai Chen, “Positioning and collision alert investigation for DSRC-equipped light vehicles through a case study in CITI”, ITS World Congress Montreal, October 29 – November 2, 2017.
 Mihaita Adriana Simona, Cai Chen, Chen Fang, Event-triggered control for improving the positioning accuracy of connected vehicles equipped with DSRC, International Federation of Automatic Control World Congress (IFAC WC 2017), 9-14 July 2017, Toulouse, France.