Driver-in-the-Loop Cyber-Transportation Systems
Abstract
Vehicular cyber-physical technology has already started making inroads into our lives in the present day. Systems such as adaptive cruise control, automated parking and parking assistance which were considered promising directions for future research in automotive research just a few years ago have already started appearing in the vehicles we see on the roads today. More complicated technologies are already being tested and are on their way into our vehicles. However, as we explore this field further, we realize that the human driver, which is usually not a major component in most cutting edge cyber-transportation research today, is in fact, a very crucial factor in deciding whether a technology will be truly successfully or not. The human driver also forms the end point of most of the advanced VANET systems and the quality of their response to the stimulus provided by the system reflects the quality of the system as a whole.
Our research combines four perspectives, namely, Transportation, Networking, Driving Simulation and Human Factors under a single project that considers problems in cyber- transportation systems from these multiple areas simultaneously. We have been working on an integrated Traffic-Network-Driving simulator that also includes human driver models for simulating very realistic background traffic, road networks, wireless networking and human responses to the messages that are exchanged between the vehicles in the simulation. We are also looking into how Human Factors can affect warning systems and message delivery. We have proposed message scheduling algorithms for both safety and infotainment type of applications including personalized delivery of advertisements to potential on-road customers considering factors such as the limited wireless resources, message processing time, driver distraction, and information overload. We have designed fusion algorithms for both, exchanging messages between multiple nodes on the wireless channel (we call this Low Level Fusion), and managing the delivery of a large number of on-board messages to the human driver (High Level Fusion). Other areas that are being explored include delivering video to commuters using a series of Access Points along the route, and green routing to save on fuel and emissions.
Our vision is to create technologies designed around the human driver that make driving a safer and more enjoyable experience for all road users. We have also made good progress on our simulator that allows for the testing of proposed solutions in a very realistic setting which includes real drivers. The experiments can be simultaneously observed and analyzed from all four perspectives (driving, transportation, networking, and human factors) thereby allowing us to observe not only the impact in each area but also the correlation between these in different areas.
Award ID: 1035733
Submitted by Chunming Qiao
on
Abstract
Vehicular cyber-physical technology has already started making inroads into our lives in the present day. Systems such as adaptive cruise control, automated parking and parking assistance which were considered promising directions for future research in automotive research just a few years ago have already started appearing in the vehicles we see on the roads today. More complicated technologies are already being tested and are on their way into our vehicles. However, as we explore this field further, we realize that the human driver, which is usually not a major component in most cutting edge cyber-transportation research today, is in fact, a very crucial factor in deciding whether a technology will be truly successfully or not. The human driver also forms the end point of most of the advanced VANET systems and the quality of their response to the stimulus provided by the system reflects the quality of the system as a whole.
Our research combines four perspectives, namely, Transportation, Networking, Driving Simulation and Human Factors under a single project that considers problems in cyber- transportation systems from these multiple areas simultaneously. We have been working on an integrated Traffic-Network-Driving simulator that also includes human driver models for simulating very realistic background traffic, road networks, wireless networking and human responses to the messages that are exchanged between the vehicles in the simulation. We are also looking into how Human Factors can affect warning systems and message delivery. We have proposed message scheduling algorithms for both safety and infotainment type of applications including personalized delivery of advertisements to potential on-road customers considering factors such as the limited wireless resources, message processing time, driver distraction, and information overload. We have designed fusion algorithms for both, exchanging messages between multiple nodes on the wireless channel (we call this Low Level Fusion), and managing the delivery of a large number of on-board messages to the human driver (High Level Fusion). Other areas that are being explored include delivering video to commuters using a series of Access Points along the route, and green routing to save on fuel and emissions.
Our vision is to create technologies designed around the human driver that make driving a safer and more enjoyable experience for all road users. We have also made good progress on our simulator that allows for the testing of proposed solutions in a very realistic setting which includes real drivers. The experiments can be simultaneously observed and analyzed from all four perspectives (driving, transportation, networking, and human factors) thereby allowing us to observe not only the impact in each area but also the correlation between these in different areas.
Award ID: 1035733