Potential travel cost saving in urban public-transport networks using smartphone guidance

<div><p>Public transport (PT) is a key element in most major cities around the world. With the development of smartphones, available journey planning information is becoming an integral part of the PT system. Each traveler has specific preferences when undertaking a trip, and these preferences can also be reflected on the smartphone. This paper considers transit assignment in urban public-transport networks in which the passengers receive smartphone-based information containing elements that might influence the travel decisions in relation to line loads, as well as passenger benefits, and the paper discusses the transition from the current widespread choosing approach to a personalized decision-making approach based on smartphone information. The approach associated with smartphone guidance that considers passengers’ preference on travel time, waiting time and transfer is proposed in the process of obtaining his/her preferred route from the potential travel routes generated by the Deep First Search (DFS) method. Two other approaches, based on the scenarios reflecting reality, include passengers with access to no real time information, and passengers that only have access to the arrival time at the platform are used as comparisons. For illustration, the same network proposed by Spiess and Florian is utilized on the experiments in an agent-based model. Two experiments are conducted respectively according to whether each passenger’s choosing method is consistent. As expected, the results in the first experiment showed that the travel for consistent passengers with smartphone guidance was clearly shorter and that it can reduce travel time exceeding 15% and weighted cost exceeding 20%, and the average saved time approximated 3.88 minutes per passenger. The second experiment presented that travel cost, as well as cost savings, gradually decreased by employing smartphone guidance, and the maximum cost savings accounted for 14.2% of the total weighted cost.</p></div

Three Competitive Transition States at the Glycosidic Bond of Sucrose in Its Acid-Catalyzed Hydrolysis

The acid-catalyzed hydrolysis of sucrose to glucose and fructose was investigated by DFT calculations. Protonations to three ether oxygen atoms of the sucrose molecule, <b>A</b>, <b>B</b>, and (<b>C</b>, <b>D</b>), were compared. Three (<b>B</b>, the fructosyl-ring oxygen protonation; <b>C</b>, protonation to the bridge oxygen of the glycosidic bond for the glucosyl-oxygen cleavage; and <b>D</b>, protonation to that for the fructosyl-oxygen cleavage) gave the fragmentation. Paths <b>B</b>, <b>C</b>, and <b>D</b> were examined by the use of the sucrose molecule and H₃O⁺(H₂O)₁₃. The path <b>B</b> needs a large activation energy, indicating that it is unlikely. The fragmentation transition state (TS1) of path <b>C</b> needs almost the same activation energy as that of path <b>D</b>. The isomerization TS of Int­(<b>C</b>) → Int­(<b>D</b>), TS­(<b>C</b> → <b>D</b>), was also obtained as a bypass route. The present calculations showed that the path via the fructosyl-oxygen cleavage (<b>D</b>) is slightly (not absolutely) more favorable than that via the glucosyl-oxygen cleavage (<b>C</b>)

Real time information on best route option from Google Maps.

<p>Real time information on best route option from Google Maps.</p

Ratio and the related volume of passengers using three choosing methods (<i>N</i> = 200).

<p>Ratio and the related volume of passengers using three choosing methods (<i>N</i> = 200).</p

Procedure of OAT method.

<p>Procedure of OAT method.</p

Assignment results of average waiting time per stop.

<p>Assignment results of average waiting time per stop.</p

Procedure of choosing departure time using the OAT method.

<p>Procedure of choosing departure time using the OAT method.</p

Example of a transit network with four bus lines and four bus stations.

<p>Example of a transit network with four bus lines and four bus stations.</p

Procedure of generating optimal routes displayed on smartphone.

<p>Procedure of generating optimal routes displayed on smartphone.</p

Route recommendations for travelers with different preferences.

<p>Route recommendations for travelers with different preferences.</p