Educated sources optimistically declare that autonomous vehicles (AV) could solve traffic problems by driving more efficiently and coordinating with other vehicles and infrastructure. While efficient driving and coordination via V2V and V2X network channels may provide some benefits, a study published in Transport Policy Magazine argues that the presumed benefits of self-driving cars could also be a source of more problems, like moving at slower speeds instead of parking [1] or demonstrate non-optimal behavior of other kinds, in an attempt to increase cost-effectiveness, by factoring in the costs of electricity, depreciation and maintenance. It is difficult to say how often such non-optimal behavior will take place, but many authors indicate that such a possibility is quite likely [2]. Unpredictable behavior of highly automated autonomous vehicles can cause a variety of effects, including significant increase of travel time in highly congested areas [3]. Of course, the progress cannot be stopped, and very soon the autonomous vehicles will start appearing on our streets in increasing numbers. It is possible, however, that as their numbers increase it would become necessary to adjust not only their AI driven software, but also the conditions for their use. It may turn out that certain types of AV demonstrate optimal behavior only in very specific locations or on the roads of certain class, or at certain time, or at various traffic loads. It is hard to envision which factors will be of primary importance. But Ticon technology, specifically the TrafficZoom application, provides the ability to effectively monitor the changes in delays, load, LOS, obtain comprehensive performance metrics and timely establish the impact of autonomous cars on smart city environment.

TrafficZoom Dashboard delivers instant information for each street in the whole city or in any chosen square on the map, including:​

• Areal performance: Travel time and Traffic delay, Speed capacity and performance, Network Bandwidth utilization by hours.

• Streets performance: Travel time and Traffic delay,  LOS for each street and each segment of each street for the entire day or period of time during the day

• Traffic volume and traffic speed with high resolution, up to exact address

So obviously it is advisable to implement TrafficZoom everywhere, where the autonomous vehicles are tested.

1. Adam Millard-Ball. The autonomous vehicle parking problem. Transport Policy, Vol 75, March 2019, Pages 99-108

2. Jason Plautz. Self-driving cars could increase urban congestion. Smart Cities Dive, Feb 4, 2019

3. Reshaping Urban Mobility with Autonomous Vehicles. Lessons from the City of Boston. Boston Consulting Group, 2018