Santhanakrishnan Narayanan

Mr. Santhanakrishnan Narayanan

Technical University of Munich, Munich, Bavaria, Germany
orcid

Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 February 2020 in Transportation Research Part C: Emerging Technologies
Verified
Journal Article
Closed access
Santhanakrishnan NarayananSanthanakrishnan Narayanan
Santhanakrishnan Narayanan
ECEmmanouil Chaniotakis
Emmanouil Chaniotakis
CAConstantinos Antoniou
Constantinos Antoniou

1 February 2022 in Transport Policy
Verified
Journal Article
Open access
Santhanakrishnan NarayananSanthanakrishnan Narayanan
Santhanakrishnan Narayanan
Constantinos AntoniouConstantinos Antoniou
Constantinos Antoniou

13 January 2023 in Transportation Research Part A: Policy and Practice
Verified
Journal Article
Closed access
Santhanakrishnan NarayananSanthanakrishnan Narayanan
Santhanakrishnan Narayanan
Constantinos AntoniouConstantinos Antoniou
Constantinos Antoniou

2 May 2019 in Transportation Research Record: Journal of the Transportation Research Board
Verified
Journal Article
Closed access
PDF file
JGJohannes Gruber
Johannes Gruber
Santhanakrishnan NarayananSanthanakrishnan Narayanan
Santhanakrishnan Narayanan
Cargo cycles are gaining more interest among commercial users from different business sectors, and they compete with cars in urban commercial transport. Though many studies show the potential of cargo cycles, there is still a reluctance to deploy them. One possible reason for this is the lack of knowledge regarding their suitability in relation to travel time. Therefore, this study aims to explore cargo cycles’ travel time performance by quantifying the travel time differences between them and conventional vehicles for commercial trips. The authors compare real-life trip data from cargo cycles with Google’s routed data for cars. By doing this, the authors explore the factors affecting the travel time difference and propose a model to estimate this difference. The attributes for the model were selected keeping in mind the ease of obtaining values for the variables. Results indicate cycling trip distance to be the most significant variable. The study shows that expected travel time difference for trips with distances between 0 and 20 km (12.4 mi) ranges from -5 min (cargo cycle 5 min faster) to 40 min with a median of 6 min. This value can decrease if users take the optimal cycling route and the traffic conditions are worse for cars. Although what is an acceptable amount of travel time difference depends on the user, practitioners can be certain of the travel time difference they can expect, which enables them to assess the suitability of cargo cycles for their commercial operations.

1 January 2020
Verified
Book Chapter
Closed access
Santhanakrishnan NarayananSanthanakrishnan Narayanan
Santhanakrishnan Narayanan
ECEmmanouil Chaniotakis
Emmanouil Chaniotakis
CAConstantinos Antoniou
Constantinos Antoniou

1 January 2022 in Transportation Research Part A: Policy and Practice
Verified
Journal Article
Open access
Santhanakrishnan NarayananSanthanakrishnan Narayanan
Santhanakrishnan Narayanan
JGJohannes Gruber
Johannes Gruber
GLGernot Liedtke
Gernot Liedtke
Constantinos AntoniouConstantinos Antoniou
Constantinos Antoniou