INCIDENT ANALYSIS USING PROBE DATA Presented by: WG OLIVIER Co-Authors: Dr. J Andersen & M Bruwer

Presentation Structure Aim of research Why do we need to investigate road incidents? How incidents were investigated until now What is probe data? How is probe data used to investigate road incidents? Results discussion Conclusions and Recommendations

Aim of research To propose a first of its kind, simple but accurate, method of determining the effect of a stationary truck on a freeway. Adjacent Corridor Immediate, surrounding network To determine whether this methodology can accurately represent the true state of traffic on any given road. Provided that enough data exist on the particular road for the different time sets.

Why do we need to investigate road incidents? Increasing levels of congestion in cities around the world Economic impact on companies delivering goods & services due to lost time in traffic Freeway Management Save lives Frustration

How incidents were investigated until now Mathematical Models and Simulations: Extended Kalman Filtering Technique Classification Models Data Mining Queueing Analysis etc.… PROBLEM? Many assumptions Complex Limited application Time consuming Often produce unreliable results

What is Probe Data? Any travelling vehicle fitted with sensors = probe vehicle The information collected from those sensors = probe data Examples: Global Positioning System (GPS) Windshield Wiper status Flat Tire Airbag Deployment Status Etc. Focus on real-time historic probe data from TomTom

How is probe data used to investigate road incidents? 1. Custom Area Analysis (CAA) Specify: Boundary Box (Location) Date Set (Day of the incident vs Typical) Time Set (Duration of incident) Obtain: Approximate Area of Influence Approximate Queuing Length

Probe Data use in incident analyses continued… 2. Custom Travel Time analysis (CTT) Specify: Route definition (Location) Alternative route(s) Date Set (Same as for CAA) Time Set (Same as for CAA) Obtain: Segment-specific traffic data parameters Average Travel Time Average Speed Cumulative Travel Time etc.

Summary of Methodology Date Location Time Occured Time Cleared Incident Information Network Impact Queueing Length CAA Corridor impact Alt-route impact CTT

Incidents Analyzed STATIONARY TRUCKS Gauteng Incident Location: N1 NB approximately 500 m before Garsfontein offramp (M30) Date: Monday 25 January 2016 Duration: From 04:39 to 11:26 (6hr 47 mins) Two out of four lanes were closed in the NB direction 2. Western Cape Incident Location: R300 NB approximately 250 m before Van Riebeek offramp (R102) Date: Monday 18 January 2016 Duration: From 07:04 to 08:48 (1hr 44 mins) One out of three lanes were closed in the NB direction

Results Discussion Custom Area Analysis

Results Discussion Continued… 2. Custom Travel Time: R300 NB Increase between 08:00 and 09:00 from 10 minutes to nearly 17 minutes (70% increase)

Results Discussion Continued… 2. Custom Travel Time: R300 Alternative Route Alternative route along Polkedraai Road, New Nooiensfontein Drive and Van Riebeek Road 14 minute increase

Results Discussion Continued… 3. Custom Travel Time: Cape Town R300 NB Old Paarl Road Van Riebeeck Hindle Road Polkedraai Incident

Conclusions The methodology provided the results that were expected The methodology has the ability to represent the true state of traffic during and after a non-recurrent incident event (stationary truck) The methodology is easy to replicate, the results can be quickly produced and it is simple to interpret, unlike many other models Major advantage: Work with real traffic data no assumptions

Recommendations Further research is required on: Different weather conditions Other days of the week and times of the year Unique or special events Fatal crashes A comprehensive benefit-cost analysis

END THANK YOU