Multi-criteria Evaluation of Traffic Signal Control Manfred Boltze and Wei Jiang 1

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Multi-criteria Evaluation of Traffic Signal Control Manfred Boltze and Wei Jiang Transport Planning and Traffic Engineering, Technische Universität Darmstadt Future City 2017: Urban Sustainable Development and Mobility Hanoi (Vietnam), 15 September 2017 Multi-criteria Evaluation of Traffic Signal Control Manfred Boltze and Wei Jiang 1

Background Questions: Value Orientation How to value the delay for pedestrians in comparison to those for cyclists, public transport passengers as well as car drivers and passengers? How many litres additional fuel consumption and how many grams of exhaust emissions can be accepted, in order to accelerate a bus and reduce the delay for each passenger by about 10 s? By which criteria can we decide to interrupt a green wave due to a pedestrian request at roadside, although it may lead to disruption of traffic flow as well as increased energy consumption and emissions? How do we consider the side-effect of a green wave for cyclists that more stops and accelerations of motorized vehicles lead to a significantly higher air pollution concentration? Shall we use traffic signals to influence modal split? How do we consider negative impacts on other road users and on air pollution? Shall we really deteriorate traffic flow to influence the modal share? Multi-criteria Evaluation of Traffic Signal Control Manfred Boltze and Wei Jiang 2

Background General Conclusions A comprehensive consideration of various impacts on the different road user groups is necessary. The impacts must be measured! Planning instruments must partially be further developed. A fair balance is required to deal with goal conflicts. Rules to value and to weight the different impacts must be established. Multi-criteria Evaluation of Traffic Signal Control Manfred Boltze and Wei Jiang 3

Assessment Method Methods to Estimate/Measure Impacts During Planning Traffic volume Traffic flow simulation Delay for vehicles Delay for individuals Queue lengths Number of stops Average travel speed Emission modelling Emissions of air pollutants Fuel consumption CO 2 emissionen Modelling of ambient air quality With dispersion models / statistical models Ambient air quality Geometric design of intersection Saturation degree of green times Method in RLS-90 Noise level Signal timing Accident analysis with data under similar situations Number of traffic accidents Number of slight injuries Number of severe injuries Number of fatalities low / middle / high effort low / middle / high accuracy Source: own illustration Multi-criteria Evaluation of Traffic Signal Control Manfred Boltze and Wei Jiang 4

Assessment Method Overview Costs as the Leading Criteria Average delay per person Delay costs Weighted delay costs Number of accidents Number of slight injuries Number of severe injuries Number of fatalities PM 10 emissions NO x emissions Fuel consumption CO 2 emissions Cost factors Accident costs Fuel and environmental costs Particular weighting Weighted accident costs Weighted fuel and environmental costs Sum of costs Sum of weighted costs Multi-criteria Evaluation of Traffic Signal Control Manfred Boltze and Wei Jiang 5

Assessment Method Cost Factors for Delay Two cost components are considered: value of time in private transport, time-dependent operation cost. Value of time in private transport Time-dependent operation cost Peak hours Walking Cycling Average occupancy rate [p/veh] Value of travel time saving [ /p-h] - - Public transport Motorised private transport Heavy transport Bus, tram Car LCV HDV 40 (bus) 80 (tram) 1.3 4.21 4.40 4.42 4.93 Personnel cost [ /p-h] 20.14 17.64 20.14 Source Own calculation based on BVWP 2030 (Dahl et al. 2016) If possible, the average occupancy rate of public transport vehicles should be estimated site and time specific. In case of dynamic control strategies, the occupancy rate can be measured in real-time and considered in the online optimisation Impending increase in costs due to extra vehicle demand can be taken into consideration through particular weighting (see slide 9). Multi-criteria Evaluation of Traffic Signal Control Manfred Boltze and Wei Jiang 6

Assessment Method Cost Factors for Accident Risks The German Federal Highway Research Institute (BASt) annually caluclates and publishes the economic costs of traffic accidents in Germany. Personal injury Property damage Fatality Severe injury Slight injury Accident with personal injury Accident with fatality Accident with severe injury Accident with slight injury Serious accident just with property damage Other accident (including achohol accident) Cost factor (at 2012 price) 1,161.892 /person 116,151 /person 4,829 /person 15,606 /accident 43,096 /accident 20,782 /accident 13,959 /accident 20,808 /accident 5,951 /accident Source: Baum et al. 2011 and Bundesanstalt für Straßenwesen 2016, own illustration Multi-criteria Evaluation of Traffic Signal Control Manfred Boltze and Wei Jiang 7

Assessment Method Cost Factors for Emissions and Energy Consumption Cost factors for emissions based on the evaluation method for the Greman Federal Transport Infrastructure Plan (BVWP 2030) and another study from the Federal Environmental Agency Air pollutant 1) Source: BVWP 2030 (Dahl et al. 2016, S. 111) 2) Source: Methodenkonvention 2.0 zur Schätzung von Umweltkosten (Schwermer 2012a, p 5) 3) This value correponds to the middle value given in the literature. Specific damage costs (for CO 2 damage and avoidance costs) [ /t] at 2010 price urban rural PM exhaust 364,100 1) 122,800 1) PM 10 resuspension und abrasion 33,700 2) 11,000 2) NO x 15,400 1) 15,400 1) CO 2 80 2)3) 80 2)3) Cost factors for energy consumption according to BVWP 2030 (at 2012 price): Petrol and diesel 0.71 /l (without taxes) Electricity rate for private households 17.84 Cent/kWh (without taxes und fees) Multi-criteria Evaluation of Traffic Signal Control Manfred Boltze and Wei Jiang 8

Assessment Method Particular Weighting A particular weight can be applied due to political or planning reasons (permanent or situation-responsive). A particular weight must always be justified. A particular weight can be applied on: Value of time for pedestrians and cyclists Value of time for public transport passengers Value of time for motorized private transport and heavy transport Accident costs Environmental costs Examples for planning or political reasons: To promote non motorized traffic To promote non motorized traffic Near schools or bus stops etc. To promote public transport To avoid increase in costs due to extra vehicle demand To harmonize traffic flow To promote traffic safety To strengthen environmental and climate protection Impending exceedance of threshold values Multi-criteria Evaluation of Traffic Signal Control Manfred Boltze and Wei Jiang 9

Results from Case Studies Introduction to Case Study 1: Pedestrian Crossing Quelle: Straßenverkehrs- und Tiefbauamt Stadt Darmstadt Pedestrian crossing on coordinated corridor Originally not integrated in the coordination (status: November 2016) Medium number of passing vehicles and low number of crossing pedestrians Long queues in the morning peak hours Features to generate alternative signal programs: cycle time pedestrian request (active/unactive) coordination Multi-criteria Evaluation of Traffic Signal Control Manfred Boltze and Wei Jiang 10

Results from Case Studies Implementation of the Assessment Method: Pedestrian Crossing (1) Current traffic signal program Morning peak hour Variable cycle time Active pedestrian request Uncoordinated (for vehicles) Traffic volume in the investigated hour: 113 Pedestrians 1722 Persons in cars and LCV 17 Persons in HGV Optimum by applying a particular weighting for pedestrian delay (> factor 11) Fuel consumption 46%; 29 /h Walking 3%; 2 /h Fuel and environmental costs 66% Delay costs 34% Motorised private transport 31%; 19 /h Calculated total costs: 63 /h CO 2 Emissions 12%; 8 /h Heavy transport 1%; 0.7 /h PM Emissions 4%; 3 /h NO x Emissions 3%; 2 /h Source: own illustration Multi-criteria Evaluation of Traffic Signal Control Manfred Boltze and Wei Jiang 11

Results from Case Studies Implementation of the Assessment Method: Pedestrian Crossing (2) Cost-effective signal program Morning peak hour Cycle time 90 s Unactive pedestrian request Coordinated (for vehicles) Traffic volume in the investigated hour: 113 Pedestrians 1722 Persons in cars and LCV 17 Persons in HGV Calculated total costs: 38 /h Optimum by the same weighting for all cost components Fuel consumption 55%; 21 /h -8 /h Delay costs 21% Fuel and environmental costs 79% Walking 11%; 4 /h +2 /h Motorised private transport 9%; 3 /h -16 /h Heavy transport 1%; 0.2 /h PM Emissions 6%; 2 /h -1 /h NO x Emissions 3%; 1 /h CO 2 Emissions 15%; 6 /h -2 /h -1 /h Source: own illustration Multi-criteria Evaluation of Traffic Signal Control Manfred Boltze and Wei Jiang 12

Results from Case Studies Introduction to Case Study 2: Four-legged Intersection Typical four-legged intersection in the urban area Medium number of pedestrians Seperated cycle lanes Feature to generate alternative signal programs: transit signal priority Source: Straßenverkehrs- und Tiefbauamt Stadt Darmstadt Multi-criteria Evaluation of Traffic Signal Control Manfred Boltze and Wei Jiang 13

Results from Case Studies Implementation of the Assessment Method: Four-legged Intersection (1) Current traffic signal program Evening peak hour Conditional transit signal priority Fuel consumption 24%; 79 /h Walking 3%; 8 /h Cycling 1%; 3 /h Public transport 7%; 24 /h Traffic volume in the investigated hour: 256 Pedestrians 105 Cyclists 943 Persons in buses 2743 Persons in cars and LCV 33 Persons in HGV Calculated total costs: 333 /h CO 2 Emissions 6%; 21 /h NO x Emissions 2%; 6 /h PM Emissions 2%; 8 /h Fuel and environmental costs 34% Accident costs 13% Delay costs 53% Motorised private transport 40%; 132 /h Accident costs 13%; 44 /h Heavy transport 2%; 7 /h Source: own illustration Multi-criteria Evaluation of Traffic Signal Control Manfred Boltze and Wei Jiang 14

Results from Case Studies Implementation of the Assessment Method: Four-legged Intersection (2) Alternative signal program Evening peak hour No transit signal priority Fuel consumption 23%; 77 /h -2 /h Walking 3%; 8 /h Cycling 1%; 3 /h Public transport 12%; 39 /h +15 /h Traffic volume in the investigated hour: 256 Pedestrians 105 Cyclists 943 Persons in buses 2743 Persons in cars and LCV 33 Persons in HGV Calculated total costs 334 /h CO 2 Emissions 6%; 21 /h NO x Emissions 2%; 6 /h PM Emissions 2%; 8 /h Accident costs 13%; 44 /h Fuel and environmental costs 34% Accident costs 13% Heavy transport 2%; 6 /h -1 /h Delay costs 53% Motorised private transport 36%; 122 /h -10 /h Source: own illustration Multi-criteria Evaluation of Traffic Signal Control Manfred Boltze and Wei Jiang 15

Conclusions A detailed assessment is needed to consider the various impacts of traffic control on different road user groups and to gain a fair balance. Today s simulation tools are very supportive to allow such assessment. The number of people that are present in different modes at intersections has significant impacts on the optimisation of traffic signal control. The distribution of cost components can vary for different intersection types and signal programs. Costs for fuel and emissions are between 1/3 and 2/3 (and unneglectable). There is a correlation between costs of delay and costs of fuel and emissions, but this correlation is specific for each intersection and situation. Additional research is necessary to reflect the impacts of traffic signal control on mode choice, the impacts in a network scale, the impacts on public transport operations. With adaptations of the cost values, the general approach seems to be transferable to other countries. Multi-criteria Evaluation of Traffic Signal Control Manfred Boltze and Wei Jiang 16

Multi-criteria Evaluation of Traffic Signal Control Manfred Boltze and Wei Jiang Transport Planning and Traffic Engineering, Technische Universität Darmstadt Future City 2017: Urban Sustainable Development and Mobility Hanoi (Vietnam), 15 September 2017 Thank you for your attention! Multi-criteria Evaluation of Traffic Signal Control Manfred Boltze and Wei Jiang 17