V2X Based Traffic Light Assistant for Increased Efficiency of Hybrid & Electric Vehicles

Inhalt:
The intelligent amalgamation of diverse sources of on-board and crucially off-board information, in sophisticated predictive energy management systems and Advanced Driver Assistance Systems (ADAS), will play an ever greater role in the development of efficient, safe and increasingly automated vehicles. More effective usage of the overall vehicle and powertrain energy will be realized through accurate evaluation of upcoming road and traffic conditions, using emerging information and communication technologies. In real world driving conditions, overall vehicle energy utilization is strongly influenced by the vehicle speed profile, especially with aggressive or non-anticipatory human drivers. Road restrictions such as Traffic Lights (TL), speed limits and traffic prevent the vehicle from following an optimal speed trajectory, reducing efficiency, whilst increasing journey times, energy demand and driver stress. This paper describes the essential principles of a novel model based and predictive Traffic Light Assistant (TLA) for hybrid and electric vehicles. The TLA presented was conceptually developed in a co-simulation environment, which revealed extremely significant energy saving in cities, for example, energy demand was reduced by 17% on a 4.2 km route with 14 TL. Development was also carried out in a driving simulator to assess human factors. Further development of the TLA for eventual use in a real V2X urban environment continues from 2016 onwards.