Location
London
Event Website
http://www.csce2016.ca/
Description
The ability of the transportation system to continue to serve traffic under disruptive conditions is a resilience characteristic of infrastructure and traffic management. In the context of this research, resilience is defined as the ability to resist the loss of traffic-serving capability by using traffic (including geometric) and control system design advances (i.e. the inherent resilience) and by activating capacity-enhancing measures (i.e. the dynamic resilience). Vulnerabilities in road traffic networks cause the loss of capability to serve demand overloads. On the other hand, intelligent technology and associated methodology can potentially prevent or reduce this loss of capability. An outstanding research question is the role of automation in driving for enhancing the resilience of urban road traffic network. This paper reports research in-progress on improving resilience of adaptive capacity in traffic networks with intelligent systems and advanced methods. An introduction is provided to vulnerabilities in traffic network, and available information is used as empirical evidence of vulnerabilities. Inherent and dynamic resilience measures of the traffic system are defined at the scales of corridors and networks that can potentially overcome vulnerabilities. Features of autonomous driving are presented as resilience-enhancing measures. Finally, conclusions are presented on the potential of automation in driving to enhance the resilience of urban traffic network so that it can withstand high predictive imbalances of demand vs. capacity as well as stochastic traffic overloads and recover functionality at a tolerable level of performance within an acceptable time period.
Included in
TRA-953: AUTOMATION IN DRIVING FOR ENHANCING RESILIENCY IN TRANSPORTATION SYSTEM
London
The ability of the transportation system to continue to serve traffic under disruptive conditions is a resilience characteristic of infrastructure and traffic management. In the context of this research, resilience is defined as the ability to resist the loss of traffic-serving capability by using traffic (including geometric) and control system design advances (i.e. the inherent resilience) and by activating capacity-enhancing measures (i.e. the dynamic resilience). Vulnerabilities in road traffic networks cause the loss of capability to serve demand overloads. On the other hand, intelligent technology and associated methodology can potentially prevent or reduce this loss of capability. An outstanding research question is the role of automation in driving for enhancing the resilience of urban road traffic network. This paper reports research in-progress on improving resilience of adaptive capacity in traffic networks with intelligent systems and advanced methods. An introduction is provided to vulnerabilities in traffic network, and available information is used as empirical evidence of vulnerabilities. Inherent and dynamic resilience measures of the traffic system are defined at the scales of corridors and networks that can potentially overcome vulnerabilities. Features of autonomous driving are presented as resilience-enhancing measures. Finally, conclusions are presented on the potential of automation in driving to enhance the resilience of urban traffic network so that it can withstand high predictive imbalances of demand vs. capacity as well as stochastic traffic overloads and recover functionality at a tolerable level of performance within an acceptable time period.
https://ir.lib.uwo.ca/csce2016/London/Transportation/29
