SMART CITY - TRAFFIC EVALUATION AND MANAGEMENT (SMART ANALYTIC PROCESS)



SMART CITY - TRAFFIC EVALUATION AND MANAGEMENT (SMART ANALYTIC PROCESS)

Nominated for The Planning for Sustainable Land Use and Transport Award

Authors

Shaleen Srivastava, Jacobs UK LIMITED

Description

Transportation managers need to actively manage highway networks to achieve greater efficiency and sustainability which supports the need for systems such as SmAP.

Abstract

At present, traffic congestion is a serious problem in most big cities across the globe, with growing economic, social and environmental impact. Transportation managers need to actively manage highway networks to achieve greater efficiency and sustainability, which in turn, means a considerable investment in traffic management system tools. However, traditional means of collecting traffic data, particularly live data, is becoming increasingly expensive, supporting the need for systems such as SmAP (Smart Analytic Process) that make better use of new technologies to achieve the goals of the transportation plan.
While there are several sources for live traffic data, our vision for traffic management and modelling applications is to collect the data through the use of mobile phone technology for the following reasons:
• The infrastructure is already in place for mobile phone coverage and does not require new major investments in equipment installation. By design, mobile phone networks already cover virtually all elements of the transportation network. SmAP can dramatically reduce the costs being incurred by public authorities for physical infrastructure to obtain live data and at the same time provide much wider coverage (higher resolution).
• The sample size with mobile phone data is far higher than any other source of live data like GPS or camera technology. The few exception areas where mobile phone penetration is low often reflect areas with little or no traffic concerns.
SmAP provides not only real time predictions of network performance, but also supports real time decisions on route selection for future journeys, mode selection for future journeys, and real time strategy formation to decongest roads due to events such as road work, poor weather, large events, etc. It is also a ‘GREEN TECHNOLOGY’ as it helps in the reduction of CO2 emissions as a result of reduced congestion on roads.

THE SmAP DIFFERENCE FOR SMART CITIES

SmAP core technology can anonymously locate and track the movement of every mobile handset in a GSM network. Advanced filters can discern which handsets are in vehicles on roadways. By monitoring a handset’s motion over time, SmAP is able to determine the speed at which a handset is moving and thus the flow of traffic along virtually any section of roadway. Anonymously tracking specific handsets through complete phone calls can provide historical data on origins, destinations, and route selection.

SMART CITY TRAFFIC MANAGEMENT

The key processes in the operation of the SmAP traffic management platform include:
• Collection and mapping of the key socioeconomic and transport features of the study region.
• Assembling all useful traffic data from any existing physical infrastructure and/or other real time traffic data source and harmonizing the data.
• Feeding the traffic management platform with live data derived from mobile phones.
• Optimizing real time data and checking for errors (location errors, double counting etc).
• Validating mobile phone data through a series of ground tests.

SMART CITY TRAVELLERS’ PREDICTIONS

The key to real time predictions lies in its ability to “mine” the rich data set provided by SmAP. Using mobile phone “motion” data, we are able to construct “trip chains,” including origins, destinations and inferred “journey purposes,” building a comprehensive live online traffic model for faster than the real-time predictions.
The key processes for real time predictions include:
• Classifying vehicles by type.
• Origin and destination demand matrices by vehicle
• Classifying the origin and destination data by journey purpose.
• Real-time traffic predictions.

Publisher

Association for European Transport