Connected autonomous vehicles (CAV) technologies will be in the market in the near future. This requires that transportation systems are ready to operate in a mixed traffic environment where a portion of vehicles are CAVs and the remaining are human-driven vehicles. This presentation includes two topics. First, a CAV-based microscopic trajectory-smoothing concept is proposed to harmonize traffic and improve mobility and environmental impacts. The proposed algorithm can be used to prevent or mitigate traffic speed drops near highway bottlenecks. The second topic investigates how different features of CAVs and corresponding lane management policies can improve throughput capacity of mixed traffic from a macroscopic perspective. An analytical model is proposed to quantify mixed traffic highway capacity. The proposed capacity analysis is then extended to a managed lane model to determine the optimal number of lanes to be allocated to CAVs. Financially, numerical examples are presented to investigate three different CAV technology scenarios: neutral, conservative, and aggressive CAV headway settings.

Recent advances in traffic signal system technology have led agencies to modify practices and adopt new ways of managing traffic. Traffic signals and the accompanying equipment enable more effective transportation solutions than the industry has seen in the past. The 2nd Edition of the Traffic Signal Timing Manual (STM2) has an increased focus on signal system users and their priorities. In addition to the STM2, there are state DOT manuals and other guidance materials that are changing the way engineers are managing the transportation system. Current signal timing models tend to provide a one-size-fits-all approach to signal timing, which often leads to the incorrect assumption that the model provides the optimum solution. A traffic analyst simply inputs the data required by the model, hits the optimize button, and gives the optimized results to the appropriate person for implementation. The results largely reflect the model's priorities (generally some version of vehicle delay) for system users, which may or may not fit the needs of the actual operating environment or users (including pedestrians, bicycles, and transit). New technology and data (for instance Google Traffic), put a variety of tools in the hands of engineers to solve problems. 

To this end, the use of an outcome based approach to signal timing allows the practitioner to develop signal timing based on the operating environment, users, user priorities by movement, and local operational objectives. Performance measures are then used to assess how well the objectives are being met. Once the objectives and performance measures are established, timing strategies and timing values can be chosen. The final steps of the process involve implementation and observation (i.e., determining if the timing strategies and values are working), as well as sustaining operations that meet the operational objectives through monitoring and maintenance. This webinar familiarizes transportation engineers/planners with the newest innovations in traffic signal timing. The presenter of the webinar discusses recent developments in available design guidance and considerations when designing signal timing and monitoring transportation system performance.