Browse Prior Art Database

Smart Traffic Congestion Management Through Automated Road Pricing

IP.com Disclosure Number: IPCOM000202699D
Publication Date: 2010-Dec-23
Document File: 5 page(s) / 33K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed is the design of a real-time automated road pricing system that makes use of price differentiation to incentivize the widespread use of GPS navigation technology as well as other technologies such as seat sensors (to count the passengers) and fuel optimizers that can lead to optimization of transport efficiency. The design includes a central authority that collects real-time traffic condition data and automatically determines optimal fine-grained pricing of roads by taking into account historical data and results of auto-simulations. Individual GPS navigation systems can then determine optimal routing based on drivers' preferences. The GPS navigation systems also provide inputs to the central authority by uploading traffic condition data and fine-grained route information for billing.

This text was extracted from a PDF file.
This is the abbreviated version, containing approximately 23% of the total text.

Page 01 of 5

Smart Traffic Congestion Management Through Automated Road Pricing

Traffic congestion is a problem that affects all cities, and it is one of the main problems that IBM's Smarter Planet initiative aims to address. This is expected to become increasingly problematic as 70% of people are expected to live in cities by 2050. There are multiple ways through which traffic congestion can be alleviated: e.g., building a better road network, enhancing public transport and enticing people to use them, controlling the number of vehicles using the roads, etc. The problem that this invention tries to deal with is that of optimizing traffic flow given a fixed road network.

A simple way to characterize this optimization problem is to maximize the value of T (transport efficiency) = people-distance transported per hour through the road network. Note that it is better to use the product of people and distance rather than vehicle and distance since it is more optimal to the society if more people are transported instead of simply having more vehicles transported. The measurement of distance should, ideally, be the "desired" shortest distance between the start and end points that each person wanted to be transported over. But in the absence of such data, we can use the actual distance travelled as a proxy. If environmental factors should be taken into account, we can further enhance T by adding "per Joule of energy expended" or "per ton of CO2 produced". For goods vehicles, the payload should also be taken into consideration.

It is not quite possible to compute, centrally, the optimal route that each person should take since:

Every person has different objectives with respect to value of time, fuel consumption, total cost of route, use of private vs public transport, etc.

Like the weather, road conditions may evolve rather unpredictably, and so, the optimal route for a person may need to be adjusted while he is still traveling. The cost of building such an infrastructure is prohibitive.

As a result, most governments or transport authorities hope to optimize T by using pricing to change behavior or to provide as much information to drivers as possible so that they can make informed decisions while on the road. Current solutions and drawbacks are as follows:

Fixed-schedule road pricing, such as the Electronic Road Pricing (ERP) system in Singapore. The purpose is to influence general driving behavior by discouraging the use of likely congested roads during peak hours. However, it is very "coarse-grained" in nature: It only takes care of major roads/areas and does not take into account ad hoc congestions. Road pricing is also not based on vehicle efficiency, such as no. of people it is carrying and fuel consumption. Broadcasting congestion information through variable road signs, radio, web, phone apps, etc. The purpose is to give drivers as much information as possible, hoping that they will make the correct decisions. However, they are generally not...