Intelligent Transportation Systems
One of the best ways to pursue a hobby at modern times is to do so at the traffic jams, when the world stops for no understandable reasons; and for the ones without a hobby, there is always a possibility to think about the purpose of everything in life, including traffic jams. It is imperative to think why traffic congestions happen, especially when there is no sight of a traffic light nearby stopping the traffic. To make it simple, let us say that you can happily attend 5 guests per day (capacity flow) and if more guests come, your efficiency reduces, upto 0 when your house is stormed with guests and you have no space to mingle with them. Because you're a lovable person, people keep storming in and you don't chuck them out, leaving out house as choked, when nobody naturally volunteers to come in. It is better to be inefficient serving just 3 guests a day, and getting a lower number of people in. Similarly with traffic, if more vehicles enter the system than ideal, a part of the transportation network dies.
If the number of vehicles entering the roads is more than those serviceable, a congestion will happen. And there is nobody who can stop you from entering the roads. So a congestion will happen, unless someone builds new roads. There is a way out. Take long secret routes that people seldom take and you'll never get into a congestion. And those routes can be calculated algorithmically and traffic metrics adjusted to make those roads look unattractive for the future traffic. The research makes strategies to distribute traffic by changing the routing algorithms, thus anticipating congestion and avoiding it.
This puts a very fundamental question, by what time should you leave to the airport to catch the flight of your next dream holiday? To be very safe, it is good to leave early morning for the late night flight, to be sure that no matter how bad God is upon you, there is plenty of time to spare. For the adventurous, it is always a sight to show some athletics and jump last minute into the airport. The research lets you choose your type/need (the risk level) - going to a boring family function with an incentive of getting late, going to the concert of your favorite star with a need to get the best seats, going for shopping where you're always welcome, or starting business at the time told by the family priest which better not be missed. The research suggests a good starting time based on the anticipated traffic and risk level. Funny enough, to be absolutely sure for the once-a-lifetime moment, it is always suggestive to reach at least a few hours earlier.
No matter how safe you play, the traffic may mess up. You missed that you'd be going through an area with festive traffic, or the football match gets over at the same time, or that the local school had a function at the same time – they will never let you reach on time even if it is your wedding day. If there was a human control, it would be possible to slip in a heavy bribe in return of favors. Luckily, technology has a way out, to let the traffic lights en-route turn magically green and let the vehicles around move away, if possible, in return of favors. The cooperative traffic systems allow the traffic entities to cooperate, when you badly need it.
It is always good to end with a fantasy fairy tale, and therefore, imagine a transportation network with self-driving cars that can gossip between themselves, with traffic lights, with lane managers and also with the transportation authorities. There's a lot that can come out from these chit-chats, like dynamically changing the traffic rules so that everyone is happy, letting rich vehicles take a priority and go through special roads and lanes, letting vehicles elect a traffic light change by a democracy (which is also otherwise efficient), let vehicles cordially distribute lanes and speed limits rather than a boss telling them, etc. This also presents a future where vehicles will amicably and socially solve all real-life traffic problems, just like some civilized human societies do so in some parts of the world.
Related Publications
- R. Kala (2016) On-Road Intelligent Vehicles: Motion Planning for Intelligent Transportation Systems, Elsevier, Waltham, MA.
- R. Kala (2013) Motion Planning for Multiple Autonomous Vehicles (14 videos/13 hours Video Lecture Series), School of Cybernetics, School of Systems Engineering, University of Reading, UK. Available at: http://rkala.in/autonomousvehiclesvideos.php
- R. Kala (2016) Reaching destination on time with cooperative intelligent transportation systems, Advanced Transportation 50(2): 214–227. (Download Paper)
- R. Kala, K. Warwick (2015) Congestion Avoidance in City Traffic. Journal of Advanced Transportation, 49(4): 581–595. (Download Paper)
- R. Kala, K. Warwick (2015) Intelligent Transportation System with Diverse Semi-Autonomous Vehicles, International Journal of Computational Intelligent Systems, 8(5): 886-899. (Download Paper)
- R. Kala, K. Warwick (2014) Computing Journey Start Times with Recurrent Traffic Conditions. IET Intelligent Transport Systems, 8(8): 681 – 687. (Download Paper)
