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Pages 162-171

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From page 162...
... 161 F U.S. DOT GUIDANCE ON PERFORMANCE MEASURES F.1 CALCULATION PROCEDURES FOR KEY INTEGRATED CORRIDOR PERFORMANCE MEASURES FROM SIMULATION OUTPUTS A core element of the integrated corridor management (ICM)
From page 163...
... 162 INCORPORATING RELIABILITY PERFORMANCE MEASURES INTO THE TRANSPORTATION PLANNING AND PROGRAMMING PROCESSES: TECHNICAL REFERENCE Travel Time Our basic unit of observation in calculating ICM-related performance measures is a trip ๐‘– made between an origin ๐‘œ, finishing at a destination ๐‘‘, starting at a particular time ฯ„ using mode ๐‘š. We record travel time from a single run of the simulation under operational conditions ๐‘˜ for this unit of observation as = ฯ„t ti k o d m k , , , .1 Operational conditions here refer to a specific set of simulation settings reflecting a specific travel demand pattern and collection of incidents derived from a cluster analysis of observed traffic count data and incident data.
From page 164...
... 163 INCORPORATING RELIABILITY PERFORMANCE MEASURES INTO THE TRANSPORTATION PLANNING AND PROGRAMMING PROCESSES: TECHNICAL REFERENCE The average number of trips by mode from o to d starting in interval t over all conditions k โˆˆ K: โˆ‘=ฯ„ ฯ„ โˆˆ n n po d m o d m k k K k, , , , , , (F.2a) Combining across modes, the average travel time of trips from o to d starting in interval t under operational condition k: โˆ‘ =ฯ„ ฯ„ ฯ„ ฯ„ T T n n o d k o d m k o d m k m o d k, , , , , , , , , , (F.3)
From page 165...
... 164 INCORPORATING RELIABILITY PERFORMANCE MEASURES INTO THE TRANSPORTATION PLANNING AND PROGRAMMING PROCESSES: TECHNICAL REFERENCE For this reason, the minimum threshold may also be calculated as the travel time derived in the pre-ICM case under a substantially reduced demand pattern with no incidents or weather impacts. The reduced demand pattern should generate a large enough number of trips to generate travel time statistics by mode for every set of trips from o to d starting in interval t (i.e., ฯ„> โˆ€ฯ„n o d m0 , , ,o d m, , , 0 )
From page 166...
... 165 INCORPORATING RELIABILITY PERFORMANCE MEASURES INTO THE TRANSPORTATION PLANNING AND PROGRAMMING PROCESSES: TECHNICAL REFERENCE To identify the 95th percentile travel time, we first generate an ordered list of travel times by o,d,t: ๏‹ ๏‹= ๏ฃฎ๏ฃฐ ๏ฃน๏ฃป โ‰ค =ฯ„ ฯ„ ฯ„ ฯ„ ฯ„ ฯ„+T T T T T j JT , , , , where for all 1o d o d o d o dJ o dj o dj, , , ,1 , ,2 , , , , , ,1 (F.11) The 95th percentile travel time from this list is identified using the probabilities associated with each operational condition.
From page 167...
... 166 INCORPORATING RELIABILITY PERFORMANCE MEASURES INTO THE TRANSPORTATION PLANNING AND PROGRAMMING PROCESSES: TECHNICAL REFERENCE the calculation of variance also includes the consideration of the probabilities of each operational condition.2 โˆ‘ ( )
From page 168...
... 167 INCORPORATING RELIABILITY PERFORMANCE MEASURES INTO THE TRANSPORTATION PLANNING AND PROGRAMMING PROCESSES: TECHNICAL REFERENCE Equation F.16 finds the average PMT for all trips from o to d starting in interval t over all operational conditions k โˆˆ K: โˆ‘=ฯ„ ฯ„ โˆˆ X X po d o d k k K k, , , , (F.16) Equation F.17 defines the aggregate PMT across all o,d,t: โˆ‘= ฯ„ ฯ„ ฯ„ โˆ€ X X no d o d o d, , , , , , (F.17)
From page 169...
... 168 INCORPORATING RELIABILITY PERFORMANCE MEASURES INTO THE TRANSPORTATION PLANNING AND PROGRAMMING PROCESSES: TECHNICAL REFERENCE Equation F.23 defines the aggregate PMD across all o,d,t: โˆ‘= ฯ„ ฯ„ ฯ„ โˆ€ Z Z no d o d o d, , , , , , (F.23) For example, in the Dallas ICM Corridor, the simulation period is from 5:30 a.m.
From page 170...
... 169 INCORPORATING RELIABILITY PERFORMANCE MEASURES INTO THE TRANSPORTATION PLANNING AND PROGRAMMING PROCESSES: TECHNICAL REFERENCE Estimated total trip travel time for a trip that cannot be completed before the simulation ends is the accumulated travel time, plus the time to travel the remaining distance at average trip speed:    { }( ) = + โˆ’ฯ„t t X x vmax ,0ik ik o d ik ik.

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