Game 1- Smarter Traffic
Today’s systems need reliable, real-time data and efficient management tools to deal with vexing problem of traffic congestion. This game allows players to use BPM skills (Business Process Management Skills) to solve real world traffic situations in order to improve the way traffic events are handled. By implementing real-time solutions, one can reduce traffic congestion and green house gas emissions in major urban areas.
Current scenario: This city s facing some serious challenges like heavy gridlock. Peak hour commutes from the suburbs into downtown are averaging an hour per driver each day. Vehicle accidents worsen traffic congestion, making movement difficult for critical personnel like First Respondents.
Currents solution: Traffic Prediction Tool- forecasts congestion with up to 90% accuracy. [pic]
The goal here is to modify the dispatching of problematic situations. The alternative I chose was a combination between INPUT FROM CAMERAS ON CONGESTED ROAD and AUTO-REROUTING BASED ON BIZ RULES. It is not suitable to dispatch the info from the camera directly to the police because the police needs to analyze it- be it human operators or even the more costly to implement/ acquire for police, a smart autonomous decision system- and then send the result further into traffic. The intelligent automatic rerouting saves time.
The new solution involves three players:
• Traffic Police is used to reroute traffic around accident scenes. • Smart Roadside Signs can also help divert commuters. • Smart Stoplights control the flow of traffic more efficiently. [pic]
Smarter Traffic – Scenario 1/3- Traffic Accident
Set Rerouting Business Rules
This step involves setting the number of smart stoplights, smart roadside signs and policemen. The criteria used to evaluate the choice is defined by drivers’ satisfaction and environmental impact. The result is shown in the 3 screenshots below.
• The combination employed was: Policemen: 40/100; Smart roadside signs: 16/60: Smart stoplights: 12/20. • Drivers’ satisfaction was 95% while the environmental impact was 700/650.
Smarter Traffic- Scenario 2/3- Environmental Impact
The goal now is to select the ideal time to implement a Smart Tolling System and adjust the bus and toll fares. The Key Performance Indicators are Satisfaction, Environment and Traffic.
Setting rerouting Business Rules
• Rules used: standard toll fare: 2.5$/4$, standard buss toll fare 1$/4$, time to apply: rush hour 6am-9 am (AM Tolling only). • Satisfaction: 94%, Environment: 1500/3000, Traffic 25/200.
This type of solution encourages commuters to use public transport – environmental friendly attitude- while the tax imposed for the people that want to drive to work/ children’s school during the morning hours is above average (2.5 out of 4). This way, the municipality collects money and improves the morning traffic jams problem.
Smarter Traffic- Scenario 3/3- Water Main Break
The goal here is to choose how to mingle three separate solutions. There are Manual and Virtual Operations Centers. There is also the possibility of choosing street instrumentation. The key performance indicators are Satisfaction and Efficiency.
Set routing business rules
I chose the following combination relying on the fact that the most efficient approach seems to rely on the street instrumentation and on the virtual operations center. On site manual operations only provide a slow response to unpredicted and critical situation. A virtual operations center together with street instrumentation prove themselves as a cheaper long term solution. However, manual operators are still needed to improve the flow of action.
1. street instrumentation: 80%
2. virtual operations: 90%
3. manual operations: 70%
• Indicators: Satisfaction 94%,...
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