Better Traffic Networks Through Vehicle and Signal Coordination

My friend Phil Spadaro pointed me to two interesting articles on traffic management techniques being studied by BMW and Audi here and here. The idea is to allow traffic lights and cars to communicate, which would yield better traffic flow, reducing time spent at red lights and, as a consequence, reducing fuel consumption. From the Audi article:

The results obtained during the first travolution project in 2006 were immediate and dramatic: reduced waiting times at traffic signals cut fuel consumption by 17 percent…The secret of this success: the traffic signals in Ingolstadt are controlled by a new, adaptive computing algorithm that Audi developed in cooperation with partners at colleges of advanced engineering and in business and industry. Audi has now developed travolution still further, by enabling vehicles to communicate directly with traffic light systems, using wireless LAN and UMTS links…The traffic signals transmit data that are processed into graphic form and shown on the car’s driver information display screen. The graphics tell the driver for instance what speed to adopt so that the next traffic light changes to green before the car reaches it. This speed, which keeps the traffic flowing as smoothly as possible, can then be selected at the adaptive cruise control (ACC) – but the driver can also delegate this task to the car’s control system.

The savings are significant:

When the car is part of a network in this way, the driver can reduce the amount of time spent at a standstill and cut fuel consumption by 0.02 of a litre for every traffic-light stop and subsequent acceleration phase that can be avoided. The potential is enormous: if this new technology were applied throughout Germany, exhaust emissions could be lowered by about two million tonnes of CO2 annually, equivalent to a reduction of approximately 15 percent in CO2 from motor vehicles in urban traffic.

I am sure that there are many parts of this whole coordination process that involve some OR. It must be really cool to work on a project like this. On a different, but related, note I also believe that a lot of traffic jams have psychological reasons. People’s curiosity and lack of advance planning can severely influence their driving behavior. One great example of this is the Golden Glades fork here in Miami:

People going north on I-95 (traffic pattern on the right, going upward in the picture) have to decide among one of three directions: taking the Turnpike (letter A in the picture), continuing on I-95 (letter B), or taking the rightmost exit (letter C). It just so happens that most drivers realize that they have to change lanes at the last minute and this fork is constantly congested (even without accidents). There’s a very simple simulation experiment I always wanted to run but never had the time to: simulate the traffic flow when most people decide to change lanes very close to the fork versus the situation when people change lanes at uniformly distributed points way ahead of the fork. I bet you’d see much better flow in the second case. I hope that one day, when computers can drive for us, the driving algorithms will take care of these issues.


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Filed under Applications, Network Flows, Research, Traffic Management

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