Deutsches Zentrum fr Luft und Raumfahrt e'V'

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Integrated Fleet and Traffic Management for
Chinese Cities Ralf-Peter Schäfer German
Aerospace Center (DLR) Institute of Transport
Research Rutherfordstr. 2 D-12489
Berlin Germany e-mail ralf-p.schaefer_at_dlr.de

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DLR is Germanys aerospace research center and
space agency

• 31 research institutes and scientific/technical
  facilities at
• 8 sites and 4 branches,
• 4700 employees (2300 scientists)
• a total budget of 1153 Mio (2002)

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Introduction

• Increasing traffic problems in many Chinese
  cities
• Imbalance between individual and public
  transport
• Fast growing market of individual cars
  (gt20/year)
• Limited resources to enlarge road network in
  urban areas
• To Do
• Enlargement of public transport lines
• Constructions of new strategic roads
• Improvement of the use of current road network
  by telematics systems
• Use of intelligent traffic management strategies

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ACTIVE - Joint Sino-EU Traffic Management
Project (Proposal)

• Exchange of knowledge and technology for urban
  traffic management
• Test Cities Shanghai, Dalian
• 8 core group partners
• DLR, D
• ERTICO, B (project coordinator)
• ITS China, CN
• ITS North Denmark, DK
• Navigation Technologies, NL
• Siemens, D
• Thetis, I
• Tongji University Shanghai, CN
• Several subcontractors from EU and CN

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Project Objectives
Analysis of current situation in the large
Chinese Cities Technology transfer of latest
European traffic management technology and
research activities including the adaptation to
the condition in huge growing Chinese
Cities Development of traffic management tools
and mobility services for large Chinese
Metropolitan areas Integrated approach solving
traffic management problems Set-up of
cost-efficient solutions (look to the business
case) Identification of potential users and
market needs for mobility services
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Fleet Management Systems for commercial
Transport Companies Architecture of a
satellite-based Disposition System

• Advantages
• No Voice Communication
• Faster and more reliable disposition
• Permanent control about the current position of
  the vehicles
• Delay analysis
• Several GPS-based systems up-and-running in
  China (truck management, PT, Taxis etc.)

Dispatcher Terminal
Central Head quarters
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Integrated Fleet Management and Traffic Data
Collection System
Use of GPS data from fleet management
Traffic Management Control Center
Head quarter
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Fleet Management in Public Transport
Systems Automatic Operation Control
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Floating Car Data a traffic sensor

• On-board FCD
• Preprocessing of the positioning data on-board
  of the car incl. map matching, travel time
  calculation, jam detection etc.)
• Off-board (see picture)
• Periodic measurement (e.g. 1 min -1)
• Post-processing of the positioning data on
  central server outside the car
• Reconstruction of driving dynamics

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Principles of Floating Car Data
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GPS-Floating Car Data Analysis

• Example Berlin

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Traffic Monitoring by FCD at Roundaboud Großer
Stern Berlin
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Traffic Detection Stationary Sensor vs. FCD
Berlin, Hofjägerallee, stationary data for a
Monday
Berlin, Hofjägerallee, floating car data for a
typical Monday (blue curve)
Data harmonisation is necessary -gtconsistent
picture of traffic in time and space!
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GSM stations in Berlin from German telecom
provider O2
Base station density follows population
density or business areas

• Comparison GPS vs. GSM
• GSM is less accurate, but always on

Berlin -GSM-stations - 500 m radius
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Traffic data recording from GSM network
stations
Use of existing infrastructure Accuracy up
to 500 m For inner-city regions with a dense
network of base stations Accuracy can be
reduced up to 100 m by intelligent data
analysis Identification of traffic jam cells
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Optical Traffic Sensors
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Traffic sensors I

• Stationary sensors (e.g. inductive loops)
• local traffic volume, local velocity, fleet type
• high infrastructure and maintenance expenses
• no time delay
• Floating Car Data (GPS)
• Travel time, route information
• high accuracy, partly high communication
  expenses
• data quality dependent on car penetration
• no use in tunnels etc.
• partly delayed information
• Floating Car Data (GSM )
• Travel time, route information
• Lower accuracy than GPS
• highest penetration, always available near base
  stations, cost-efficient

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Traffic sensors II

• Optical sensors (ground)
• traffic volume, local velocity, fleet type
• high infrastructure and maintenance expenses
• Separation of all type of road users possible
  (cars, busses, bicycles, pedestrian
• Recognition of vehicles (passive FCD) possible
• Optical sensors (air-borne)
• Velocity, density, fleet type, travel time
• very short delay
• high infrastructure expenses (use synergies!)

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Traffic Management in the Loop
Traffic detection
Data Fusion
Road User Behavior
Traffic Monitoring and Forecast
Control Strategy
Traffic Control e.g. Traffic Lights, Message Signs
Information(individual/collective) e.g. Mobility
Service
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Summary

• Integrated fleet and traffic management could
  save costs and increases the quality
• Combine various types of sensors (data fusion)
• Use Floating car data are as well as stationary
  sensor
• Use other important data (weather, road work,
  events etc.)
• Look for synergies with existing infrastructure
  and services
• Analyse the user behaviour
• Analyse the user needs for Services
• Note The Chinese Market is something different
  than the European ITS market!